Stolen Smartphones as an Illicit Market: Trafficking Chains and Policing Limits in Peru

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Drawing on a concurrent mixed-methods design, the study combines national victimisation survey data, telecommunications administrative records, police complaint data, spatial analysis, qualitative interviews with police officers, prosecutors, and former officials, ethnographic observation in illegal resale markets, and documentary review. The findings show that smartphone theft is not a set of isolated street offences but a multi-stage trafficking process involving victimisation, storage, revictimisation, reprogramming, distribution, and resale. This chain enables stolen devices to circulate across local, national, and cross-border markets, while exposing victims to secondary harms such as fraud, identity misuse, and financial losses. The study further finds a structural mismatch between the organisation of this illicit market and state responses. Although police interventions combine prevention and investigation, they remain fragmented across isolated offences, procedural stages, and segmented institutional competencies. As a result, enforcement tends to target visible points of the market, particularly street theft and retail resale, while leaving the broader trafficking chain relatively intact. Reframing smartphone theft as an illicit market highlights the institutional and coordination challenges involved in disrupting high-volume property crime economies. illicit markets smartphone theft trafficking chains stolen goods markets Peru Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Smartphone theft has become a public security issue of increasing magnitude in Latin America. Over the past two decades, studies on property crimes have revealed a notable shift from traditional items like wallets to portable electronic devices, particularly smartphones. This trend suggests an adaptation by criminals to contemporary technologies and the higher value and portability of these devices (Farrell et al. 2011 ; Thompson 2016 ). In Peru, the scale of the problem is alarming: approximately 16 million handsets have been reported stolen in the last seven years (OSIPTEL 2026 ), highlighting the existence of a lucrative illegal market sustained by a value chain involving various actors. This phenomenon not only poses a threat to personal property but also to the privacy and security of users' information. In this context, the present study examines stolen-smartphone trafficking in Peru as an illicit market and analyses how the National Police of Peru (PNP) responds to this complex criminal ecosystem . The literature has evolved in its understanding of property crimes, recognising the importance of factors such as availability, value, and disposability of items in theft rates (Kirchmaier et al. 2019 ; Quinn et al. 2022 ). Smartphones combine these attributes in ways that make them especially attractive within illicit markets. In Peru, this appeal is reinforced by weak criminal justice outcomes: between 2020 and 2024, only 55,339 convictions for theft, robbery, and misappropriation were recorded nationwide (Poder Judicial del Perú 2025 ), representing approximately 0.75% of the roughly 7.4 million smartphones reported stolen to the Supervisory Agency for Private Investment in Telecommunications (OSIPTEL) during the same period (OSIPTEL 2026 ). At the same time, the expansion of illicit markets—particularly through digital platforms—has transformed the commercialisation and circulation of stolen devices, allowing them to move rapidly across local, national, and international circuits (Aniello and Caneppele 2017 ; Munksgaard 2024 ). The police response to this phenomenon presents significant challenges, particularly in resource-constrained contexts where institutional structures may exhibit bureaucratic rigidity. Traditional policing models, focused on reactive responses and preventative patrolling, are increasingly challenged to adapt to a crime that operates on multiple levels and leverages advances in cyber-technology and telecommunications. In this scenario, the literature on predictive policing using big data (Perry et al. 2013 ; Brayne 2017 ) offers promising perspectives for property crime, but its implementation requires not only technological resources but also a shift in organisational culture. Moreover, the transnational nature of stolen mobile phone trafficking challenges traditional jurisdictions and requires closer international cooperation (Farrell 2015 ) involving not only police forces but also other state and private entities within the telecommunications sector. Smartphone Theft as a Trafficking Process Over the past two decades, property crime has shifted from traditional items such as cash and wallets towards portable electronic devices, particularly smartphones. This trend indicates criminals' adaptation to contemporary technologies and the increased value and portability of these handsets (Thompson 2016 ). The rise in smartphone thefts has underscored the need for crime prevention policies specifically targeting electronic devices (Farrell et al. 2011 ). However, the traditional market reduction approach is becoming obsolete in countries where offenders and fences specialise in certain items, leading to a more sophisticated black market, as seen in South Africa (Huigen 2023 ). Situationally preventive tactics, such as concealing valuable items, are increasingly ineffective, especially as smartphones now act as life-loggers and often replace laptops in various activities (Ali et al. 2022 ). This highlights the need for monitoring the availability, value, and disposability of electronic devices over time to assess theft risk accurately (Kirchmaier et al. 2019 ; Quinn et al. 2022 ). The CRAVED model (Clarke 1999 ) explains the frequent theft of items like audio-visual equipment and smartphones (Smith 2017 ). Theft patterns reflect different stages of consumer goods' life cycles, suggesting that crime prevention strategies must adapt to these phases (Wellsmith and Burrell 2005 ). The complexity and ubiquity of illicit markets, combined with methodological challenges, make them difficult to study. State prohibitions create lucrative black markets, fuelled by persistent demand and high prices (Kassab and Rosen 2019 ). The need to understand these markets from a sociological perspective, considering both supply and demand, as well as the cultural aspects that sustain them, is emphasised (Dewey 2019 ). The persistence of illicit markets, despite efforts by the state, highlights the role of intermediaries who convert stolen goods into cash or valuable items, facilitating the supply and demand cycle (Johns and Hayes 2003 ). These dynamics suggest that smartphone theft is better understood as a process sustained by intermediaries, resale infrastructures, and logistical coordination, rather than as a series of isolated theft incidents. The rise of online illicit markets has further transformed the commercialisation of stolen goods, moving away from traditional methods. Classified ad platforms, auction sites, and social networks are now the main channels for reselling stolen goods, challenging traditional explanations of illegal market organisation (Munksgaard 2024 ). In response, collaboration with online platforms to implement provenance verification mechanisms could be effective in preventing the disposal of stolen goods (Quinn et al. 2022 ). In Latin America, smartphone theft is a pervasive security concern. In Peru, "blacklists" have been created to block stolen phones, and the Penal Code has been updated to expand the criminalisation of fencing (Villaorduña and Bürkli 2021 ; Presidencia de la República del Perú 2023 ). In Colombia, state measures to combat mobile phone theft have had short-term success, but offenders quickly adapt their methods (Díaz 2023 ). Understanding the demand for stolen products, as seen in Argentina, is crucial to developing policies that enhance consumer awareness (Heckmann 2018 ). Smartphone theft therefore extends beyond property loss. Stolen devices expose victims to secondary harms, including financial fraud, identity misuse, and privacy violations. The technology industry has developed solutions to address this issue, such as wristwatch-type devices with sensors to detect suspicious movements and systems for remote location, locking, and data destruction (Yu et al. 2013 ; Jin et al. 2018 ; Nagata and Seki 2019 ). Additionally, machine learning algorithms now enhance theft detection through accelerometer data analysis, integrating technologies like SIM card detection and contextual behaviour analysis (Liu et al. 2018 ). Despite the development of solutions like kill-switches and blacklisting, their effectiveness is limited by implementation challenges and international trafficking. Taken together, existing evidence suggests that smartphone theft should be understood not as a simple street crime but as a trafficking process sustained by organised logistics, intermediaries, and cross-border flows. Addressing such processes requires responses comparable to those applied to other organised illicit markets (Farrell 2015 ). Data and Methods This study employed a concurrent mixed-methods design. Quantitative evidence was drawn from three main sources. First, the analysis addressed victimisation trends using data from the National Survey of Budgetary Programmes (ENAPRES), conducted by the National Institute of Statistics and Informatics (INEI 2026 ). Second, administrative records from the OSIPTEL served to examine reports of smartphone theft (OSIPTEL 2026 ). Third, the research utilised police report data from the Police Complaint Information System (SIDPOL) and georeferenced data from 1,332 basic police stations (Observatorio Nacional de Seguridad Ciudadana 2025 ). The latter a spatial statistical analysis of reported smartphone theft incidents and police coverage. Simultaneously, qualitative data were collected to examine how smartphone theft is understood and addressed operationally within the Peruvian National Police (PNP), specifically within the Criminal Investigation Directorate (DIRINCRI) and the Criminal Investigation Departments (DEPINCRI). Fieldwork conducted between 2022 and 2025 involved twenty-four semi-structured interviews and one focus group with eight police officers experienced in the investigation of property-related offences and crime prevention. The qualitative component was augmented by interviews with nine prosecutors and four former public officials from the Ministry of the Interior. Ethnographic observation took place in five markets dedicated to the sale of stolen smartphones in Lima and Callao, the cities with the highest concentration of smartphone thefts. Finally, a documentary analysis examined ministerial and police plans related to prevention and investigation, alongside a systematic review of press reports on police operations, seizures, and arrests involving the illegal sale of handsets. Results The Scale of the Phenomenon Smartphone theft in Peru has evolved from episodic street-level crime into a structural phenomenon of mass victimisation (Figure 1). Following a sharp decline during the COVID-19 pandemic—reaching a low of 18.2% for general victimisation and 5.3% for smartphone theft in 2020—the data reveal a robust recovery of illicit markets. By 2024, general victimisation stabilised at 27.1%, while smartphone theft remained a primary driver of property crime at 9.1%, following a 10% peak in 2023. This resurgence underscores the resilience of the stolen device economy; despite temporary mobility restrictions and policing efforts, the smartphone remains the central commodity of urban insecurity in Peru, affecting approximately 2.8 million citizens in urban areas annually. OSIPTEL’s administrative records further illustrate the magnitude and persistence of smartphone theft. Between 2017 and 2025, reports of stolen devices declined during the pandemic and increased steadily thereafter, reaching approximately 1.7 million stolen smartphones in 2023 alone (Figure 2). Across this period, more than 16 million smartphones were reported stolen. Despite the existence of blocking and recovery mechanisms since 2017, the sustained volume of stolen devices suggests that these measures have had a limited impact on disrupting the circulation of stolen goods. Despite the scale of smartphone theft, reporting rates have remained stagnant, with only about 15% of victims reporting the incident to the PNP annually (INEI 2023, p. 40). Consequently, approximately 67,236 reports were recorded between 2018 and 2025. In 2022, the police handled approximately 12,000 reports—representing a mere 0.42% of total victims estimated by ENAPRES and 0.71% of cases reported to OSIPTEL. This structural under-reporting, rooted in mistrust of the justice system, implies that the police possess only a marginal fraction of the information necessary to plan and execute investigations. Analysis of the SIDPOL database indicates that reported cases are heavily concentrated in urban areas, particularly in Lima and Callao. However, a methodological triage of the data reveals a drastic reduction in usable records, dropping from 67,235 to just 12,905 valid cases (19.2%). This substantial loss underscores systemic under-registration and a lack of geographic precision in police reporting. Despite this limitation, the available data reveal statistically significant hotspots (Figure 3) that are not randomly distributed but clustered in less than 8% of the urban grid, with 308 cells identified at a 99% confidence level. A pivotal finding is the 'proximity paradox' (Figure 4). These hotspots are significantly closer to police stations (median distance of 611 m) than isolated reports (median distance of 774 m), a difference confirmed as statistically significant by the Wilcoxon rank sum test (W = 6,126,762, p<0.001). Furthermore, density-based clustering (Figure 5) identifies that 80.7% of all events are grouped into distinct clusters, with a single dominant 'megacluster' accounting for nearly 50% of metropolitan victimisation. Rather than simple deterrence failure, this structural continuity suggests that spatial concentration is driven by victim accessibility to report crime and the persistent location of consolidated illicit smartphone markets that operate with high visibility near urban and security nodes. Of all complaints filed nationwide, according to police statistics officials, only about 15% are investigated by specialised criminal investigation units. For example, DIRINCRI received only 630 cases of theft and robbery in 2022, of which only 28% were solved. Compared to victimisation estimates, according to ENAPRES, the Directorate effectively solved less than 0.01% of smartphone theft incidents affecting the population. This gap underscores a structural limitation in investigative capacity and indicates that criminal policy measures are disconnected from the scale and organisation of this criminal phenomenon. The Trafficking Value Chain The victimisation stage marks the starting point of the criminal cycle involving stolen smartphones. Offenders primarily employ two methods: theft (without violence) and robbery (with violence). Theft typically occurs in crowded places such as markets, public transportation, and large events. "Offenders take advantage of victims' distraction in crowded spaces to steal smartphones," explains an investigator from a specialised criminal investigation unit. Robbery, by contrast, involves the use of force or intimidation and is more common in contexts with lower police presence. Interviews indicate that offenders adapt their methods strategically, selecting victims and locations based on perceived risk and opportunity. This includes vehicle-based snatching, firearm-enabled assaults, and coordinated gang robberies in commercial establishments. Once the stolen smartphones are obtained, they move to the storage phase, where they are organised and stored before reprogramming and distribution. "Devices are usually sorted by brand, model, and condition to facilitate subsequent handling," explained a detective from a specialised criminal investigation unit. This activity can be carried out by the original offenders or by other actors. They store the handsets to deliver them directly to reprogramming technicians or through intermediaries linked to the sales phase once they have amassed a significant quota. As observed from case reviews, storage is not an isolated activity but is supported by a well-structured network of contacts and storage points. "We have identified that the storage handlers work in coordination with criminal groups and have connections with sales points to ensure a continuous supply," affirmed an officer. Typically, the process continues with the reprogramming phase of the devices. However, with the proliferation of financial operations through mobile banking apps and the emergence of digital wallets from Apple, Google, banks, and other electronic money issuers, the revictimisation stage has emerged. Offenders, upon accessing stolen smartphones, also obtain the personal information stored on them, allowing them to exploit various criminal modalities. A senior officer specialising in high-technology crimes states: "It's not just the phone they're taking; it's everything inside it. The photos, contacts, banking data [...] all of that is gold for them. It's a double hit: first, they take the phone, and then they drain your money." Among the most prevalent criminal modalities is carding, where offenders illegally access victims' bank card data to make small purchases, thus avoiding immediate detection. They also impersonate individuals with good credit histories to make high-value purchases on e-commerce sites. Another modality is SIM Swapping, in which fraudsters obtain victims' personal data and block the SIM card by contacting mobile phone companies, subsequently duplicating it to access digital banking and make transfers to recipient accounts and loan applications. Similarly, a thief transfer involves extracting the SIM card from the stolen or lost device and placing it in another to access information and commit fraud. Next, the process advances to the reprogramming stage, essential for removing traces of origin and making stolen smartphones appear new or legal. “Unlocking the phone and altering the IMEI are key steps for these devices to be back in circulation,” explains a senior police commander. The process, known as flashing, involves erasing all data from the phone and reinstalling the same or an updated operating system. However, “when a device is reported stolen, the phone operator uses the IMEI to deactivate it,” explains a specialist from the telecommunications regulatory agency. Therefore, to “resurrect” these phones, technicians use programmes that allow them to change or tamper with this device identity or reuse those that have been associated with devices that were decommissioned or discarded due to obsolescence. The reprogrammed and ready-for-sale smartphones then move on to the distribution stage. This stage is crucial in the criminal cycle of stolen smartphones, as it involves transporting and delivering the devices to local, national, and international markets. “The distribution [of stolen smartphones] is a well-organised process that includes several layers of intermediaries and specific routes to avoid detection,” notes a specialised investigator from a criminal investigation directorate. Smartphones can be transported through human couriers, private vehicles, and formal transportation services. Locally, the devices are distributed in informal markets and repair shops, typically through small retail stands. While the highest concentration of criminal activity occurs in Lima, distribution also extends to other regions, reflecting the nationwide scope of victimisation (INEI 2023). For example, smartphones stolen in Ayacucho are sold in Apurímac (Jornada 2024). International distribution adds an additional level of complexity, as devices are trafficked to neighbouring countries through contraband networks. These operations often rely on weak border controls and corruption. As one high-ranking officer noted, police investigations have identified transnational trafficking routes connecting Peru to Ecuador, Bolivia, and Chile. The sales stage represents the final link in the criminal chain, where reprogrammed devices re-enter the market. Smartphones are sold in popular markets, second-hand stores, and through online platforms and social networks. In physical markets, stallholders frequently coordinate both reprogramming and sales. In markets such as Las Malvinas in central Lima, prosecutors have identified dozens of stalls dedicated to this activity (La República 2023). According to officers, this is a highly lucrative business: although prices are lower than those of new devices, the price differential is often marginal. Depending on brand and condition, a stolen smartphone may sell for only 800 to 1,000 PEN less than its retail equivalent. Field verification confirmed these dynamics, with high-end devices such as an iPhone 13 Pro Max selling for approximately 3,850 PEN and a Samsung S22 Ultra for around 2,500 PEN. Field information obtained from DIRINCRI reveals that there are at least 21 points of sale for stolen smartphones distributed across various districts of Lima. Officers from the Directorate indicate that these locations form a well-structured network of illicit commerce, as they continue to operate despite efforts to dismantle them. Inspections by local municipalities manage to close down stalls, and police- and prosecutor-led operations have resulted in arrests and seizures. Police officers comment that stallholders and workers have strong connections to assert their interests. As one retired general commander explained, “Thousands of people are well-organised and have good legal defence that keeps them without any convictions to date.” These six stages allow for a comprehensive synthesis of the complexity inherent in the illicit supply chain of stolen smartphones (Figure 6). Different criminal networks, characterised by varying levels of expertise, propensity for violence, and territorial reach, are embedded in this process. Actors range from offenders engaged in street-level victimisation to technicians capable of unlocking devices and committing cybercrimes, intermediaries who transport smartphones across cities and transnational borders, and vendors who reinsert devices into formal and semi-formal markets. In other words, smartphone theft operates as a trafficking process sustained by coordinated roles rather than isolated criminal acts. How Police Respond: Fragmentation by Design The PNP addresses smartphone theft through two formally distinct approaches: prevention and investigation, as defined by its organisational regulations and the National Citizen Security Policy. Preventive actions are primarily carried out through the National Directorate of Order and Security (DIRNOS), particularly via the Directorate of Citizen Security (DIRSECIU). According to senior police officials, the preventive response relies mainly on motorised and foot patrols as deterrence and rapid-response mechanisms, complemented by coordination with municipalities and organised community groups. Police patrols, as outlined in the official protocols (PNP 2019), follow a hierarchical structure with the sector chief as the principal authority. The protocol details specific actions for patrolling, including tactical parking in high-risk zones and citizen contact. However, the implementation of these directives faces significant challenges that undermine their preventive intent, as described by a senior officer responsible for public-order operations: "In theory, the Sector Chief should maintain constant communication with various actors and effectively coordinate patrols. But the reality is that we face severe budgetary limitations. Often, we lack sufficient operational vehicles in good condition. Additionally, the shortage of personnel forces us to prioritise certain areas, leaving others with less coverage than we should have. This directly affects our ability to prevent crimes like smartphone theft, which require a constant and visible presence." The protocol also establishes guidelines for patrol monitoring, with the precinct chief reviewing patrol routes daily and the sector chiefs submitting weekly reports. However, the effectiveness of this monitoring system is compromised by various factors, as explained by a senior officer with extensive experience in citizen-security operations: "We're supposed to use technologies like the 24/7 app [...] and the SIPCOP [Police Patrol Planning and Control Information System] to monitor patrol routes. The reality is that many police stations, especially in peripheral or rural areas, lack this technology because they are not equipped with GPS-enabled radios. Even where it's available, we often face connectivity issues or lack adequate training for its use. Additionally, the bureaucratic burden makes it difficult for precinct chiefs to devote the necessary time to effective monitoring. These budgetary and logistical limitations mean that, in practice, our patrol and monitoring system falls far short of what is outlined on paper." Police stations coordinate with local governments to carry out integrated patrols, in line with the priority objective of “Reducing victimisation by theft and robbery in public spaces” (MININTER 2022). "The coordination between the police and local governments is stipulated within the policy, as the idea is not only to increase surveillance presence on the streets but also to adapt police strategies to the specific needs of each locality," notes a specialist who has worked in the Ministry of the Interior (MININTER). Despite this, the reality is that in many jurisdictions, the lack of municipal patrol units, well-maintained municipal vehicles, and trained personnel impedes compliance with the established routes. The specialist further elaborates on the institutional friction hindering these joint efforts, even though there are legislative decrees (Ministerio del Interior 2023a, b) authorise local governments to allocate resources to fund activities that benefit the police: "Not all authorities are willing to support or work together with their precinct chiefs. There can often be rivalry or competition over who provides better services to the public. But from the Ministry, we insist that local governments coordinate their budget execution with their precincts." Collaboration with municipalities is also reflected in the implementation of community preventive programmes carried out by police stations nationwide, following directives issued by DIRSECIU. These programmes focus on engaging with educational institutions, parents, students, and organised neighbours to promote a general culture of prevention and protection. Analysis of these initiatives indicates that they primarily aim to strengthen ties between the police and the community and to guide young people towards legality, rather than addressing specific crimes such as smartphone theft. In practice, however, many of these preventive programmes are only partially implemented. Persistent resource scarcities, a dearth of trained personnel, and logistical constraints hinder their execution. Coordination between police stations and municipalities is frequently affected by institutional rivalries and uneven political commitment, which undermines collaboration and the efficient use of available budgets. As a result, these preventive efforts often fall short of their intended impact. Regarding investigation, the PNP operates under the National Directorate of Criminal Investigation (DIRNIC) as the primary regulatory authority. Among its various line directorates, DIRINCRI stands out. The ROF stipulates that this directorate is responsible for planning and commanding the investigation strategies and operations for offences outlined in the penal code at the national level (Ministerio del Interior 2017, p. 52). "We are mandated to thoroughly investigate every reported theft case. Additionally, we conduct operations alongside the Public Prosecutor's Office, to dismantle resale networks in markets and sales points," mentions a senior commander. Within this Directorate, we find the Robbery Division, the Fraud Division, and the High Technology Division, which have reported some level of action in recent years concerning smartphone trafficking. In a focus group with departmental heads and senior leadership, it was concluded that the investigative model strictly follows the Penal Code and the Criminal Procedure Code. "Here, we operate based on the law [...] Non-compliance with these statutes could result in charges by the Public Prosecutor's Office," notes a high-ranking officer. This observation underscores the legalistic and regulatory approach of the PNP in its daily operations. It also highlights that police actions are aligned with procedural adherence and the protection of fundamental constitutional guarantees. Within the framework of these investigative functions, the PNP plays a pivotal role in the Peruvian criminal process, acting as the technical investigative arm under the supervision of the Public Prosecutor's Office. Its responsibilities include receiving complaints, crime scene management, collecting evidence, identifying perpetrators, and securing exhibits related to the offence, among others (Presidencia de la República del Perú 2004). In cases of flagrante delicto, it is authorised to make arrests, always immediately informing the prosecutor. "The police are essential from receiving the complaint to presenting evidence to the Public Prosecutor's Office. This ensures that investigations are conducted in accordance with the law," notes a senior officer from a specialised criminal investigation unit. Regarding smartphone trafficking, the approach remains predominantly legalistic, with a critical observation: each stage is addressed in isolation. The focus is primarily on the victimisation stage, handled by local police stations that undertake initial procedural measures in cases of theft and non-aggravated robbery. When cases involve firearms or gang-related activity, the responsibility is transferred to district-level Criminal Investigation Departments (DEPINCRI). These departments, in coordination with public prosecutors, conduct investigations aimed at identifying the offenders and accomplices, taking statements, generating audio-visual evidence, and apprehending suspects. The Public Prosecutor's Office, for its part, directs the criminal investigation. Secondly, commercialisation is addressed. In this case, operational units formulate operational plans that are classified and approved by their respective police commands. According to the police, more than a hundred operations against smartphone theft are carried out annually in Lima and a similar number across the rest of the country since 2018. These operations exhibit significant variance in outcomes; in some cases, only 50 smartphones are seized, while in others, thousands are reported. Thirdly, reprogramming is addressed, but with greater emphasis since the legal amendment in 2023 (Ministerio del Interior 2023c), as those who clone or tamper with terminal equipment now fall under the criminal offence of fencing. Fourthly, revictimisation—including computer fraud and extortion—is addressed by units specialising in cybercrime. Stolen smartphone trafficking can be addressed using special investigative techniques if the investigative units have information that the actors operate as a criminal organisation. Certainly, this would allow for a more robust process, as special investigative techniques stipulated in the Criminal Procedure Code could be applied. However, only five cases have been addressed in this manner to combat stolen smartphone trafficking, according to information obtained from DIRNIC. As evidence, personnel who were part of the High Complexity Division (DIVIAC) team, created in 2016, believe that smartphone trafficking should primarily be handled by criminal investigation departments. "DIVIAC deals with high-complexity crimes, not just complex ones [...] related to illicit economies of greater national and international significance," explains a senior officer with experience in elite investigations. Police investigation is fragmented both in terms of competencies and methodology. At the district investigation level, investigations follow a basic investigative approach guided by the General Criminal Investigation Methodology, but regulatory constraints prevent these units from addressing organised crime. Within DIRINCRI divisions, police operational intelligence is applied, combining investigative and intelligence functions with support from specialised intelligence structures. DIVIAC, by contrast, utilised a model of Prospective Complex Investigation, in which police officers themselves conduct intelligence activities to generate robust evidence capable of sustaining judicial proceedings. Despite this methodological diversity, these specialised units have played only a limited role in addressing stolen smartphone trafficking. Instead, interventions have been largely concentrated within the State Security Directorate, particularly at the commercialisation stage (Ministerio del Interior 2022). Finally, although stolen smartphone trafficking operates as a structured process, it is not currently recognised in law as such or as an organised crime offence. This lack of recognition constrains police authorities and investigators from deploying the full suite of tools stipulated in the Criminal Procedure Code. A senior intelligence officer explains the operational impact of this legal vacuum. "It's a pretty complex issue; there isn't a visible leader directing everything [...] It's a dispersed crime, which makes it harder to tackle. Even in drug trafficking, there is a clearer criminal structure. Moreover, since it's not legally classified as an organised crime offence, the police cannot deploy special investigative techniques. The law limits the approach to this problem." Discussion The literature on property crime indicates that portable electronic devices, particularly smartphones, have become principal theft targets due to their high value, portability, and rapid resale potential (Thompson 2016). This pattern is reflected in Peru, where approximately 1.7 million individuals reported smartphone theft in the most recent year of observation. Although the PNP relies heavily on patrol-based prevention strategies, these interventions are not specifically tailored to the dynamics of smartphone theft as an illicit market. Budgetary and logistical constraints—such as personnel shortages and a deficit of operational fleet—undermine the capacity to sustain preventive presence in high-risk areas. This operational gap is particularly critical given that smartphones fit the definition of "craved" goods (Clarke, 1999)—items whose concealability and availability make them highly resistant to intermittent deterrence. As previous research suggests, effective crime prevention requires adaptation to market conditions and resource availability rather than generic deterrence strategies (Kirchmaier et al. 2019). The incorporation of information technologies such as the 24/7 application and SIPCOP reflects broader global trends towards data-driven and predictive policing (Perry et al. 2013; Brayne 2017). However, consistent with findings in other policing contexts, the Peruvian case illustrates how technological adoption alone does not guarantee improved effectiveness. Implementation gaps related to organisational adaptation, training deficits, connectivity hurdles, and administrative overload curtail the operational utility of these tools (Mohler et al. 2015; Ferguson 2017). In practice, digital systems often reinforce existing departmental silos rather than enabling coordinated responses across the disparate stages of smartphone trafficking. Coordination between police institutions and local governments—formally promoted through the National Citizen Security Policy—also presents significant challenges. While integrated patrols and community-based prevention programmes are mandated, rivalries between municipalities and police stations, resource asymmetries, and uneven operational capacities frequently undermine collaboration. As the policing literature has noted, effective prevention depends on genuine partnerships and shared problem definitions rather than formal coordination alone (Herbert et al. 2017). In this context, community programmes such as School Police ( Policía Escolar ) or Neighbourhood Watch Groups ( Juntas Vecinales ) tend to prioritise relationship-building and social legitimacy, but remain weakly connected to specific crime markets such as smartphone theft. From an investigative perspective, the PNP’s response remains predominantly legalistic and segmented, closely aligned with the Penal Code and the Criminal Procedure Code. While this framework safeguards due process and citizens’ rights, it fragments police intervention by addressing victimisation, commercialisation, reprogramming, and revictimisation as separate problems. By failing to address the continuous six-stage trafficking process, investigators miss the connections between street-level theft and the organised logistics of resale. This approach contrasts with insights from the literature on illicit markets, which emphasise the importance of integrated strategies capable of addressing interconnected criminal processes (Kassab and Rosen 2019; Dewey 2019). Moreover, the internal fragmentation of competencies and investigative methodologies within the police generates uneven effectiveness across units. Although special investigative techniques—such as telecommunications interception or undercover operations—could enhance responses to smartphone trafficking, their limited use reflects broader constraints in operational intelligence and institutional design (Banister et al. 2015; Valer and Reyes 2022). Collectively, these implications suggest that the constrained efficacy of state and police responses to smartphone theft in Peru is not a function of individual effort or commitment, but of institutional architecture. Policing models organised around isolated incidents and legal categories are ill-equipped to address offences that operate as distributed, adaptive illicit markets. More broadly, the Peruvian case shows how high-volume property crime can acquire the organisational features of a trafficking economy, with specialised roles, resilient resale channels, and cross-border circulation. This misalignment has direct consequences for both prevention and investigation and raises broader questions about how police institutions adapt to high-volume property crimes that increasingly resemble trafficking processes. Conclusion In this article, we have evaluated how the Peruvian state, and especially the police, responds to smartphone trafficking, demonstrating that it relies on a conjunction of preventive and investigative strategies rather than a single, coherent approach. Police interventions range from patrol-based prevention and market inspections to criminal investigations and technological measures such as IMEI blocking. However, despite the incorporation of information technologies and periodic operational efforts, these responses remain curtailed by logistical limitations, human resource shortages, and uneven implementation capacity—challenges that mirror broader difficulties identified in the policing literature regarding the effective translation of crime prevention strategies into practice. Our findings demonstrate that the policing response to smartphone trafficking is structurally fragmented. Police actions are organised around isolated offences and procedural stages rather than the integrated criminal process through which stolen smartphones circulate. Although the Criminal Procedure Code mandates police intervention to guarantee access to justice, this legalistic framework has proven insufficient to address the scale and complexity of the problem. Over 16 million smartphones have been trafficked in Peru in the past eight years, while the predominant response has consisted of intermittent market interventions and device seizures. Such case-by-case and stage-specific approaches fail to match the magnitude of the illicit market and allow criminal networks to adapt, reconfigure, and become increasingly difficult to detect and dismantle. The study further underscores the limitations of recent regulatory and technological measures, including the blocking of devices with altered IMEIs by the Ministry of the Interior and OSIPTEL. Despite these efforts, technicians continue to reactivate devices, and intermediaries successfully commercialise stolen smartphones both domestically and internationally. This persistence underscores the sophistication and adaptability of the illicit smartphone market, consistent with research on high-demand illicit markets that rapidly adjust to enforcement pressures (Aniello and Caneppele 2017 ; Munksgaard 2024 ). Taken together, these findings suggest that the limited effectiveness of state responses to smartphone theft in Peru is not primarily a matter of enforcement intensity, but of institutional design. Conceptualising smartphone theft as a series of discrete property offences obscures its operation as a trafficking process sustained by organised logistics, intermediaries, and transnational flows. This misrecognition is replicated not only within police institutions but also across the broader constellation of public agencies involved in regulation, prosecution, telecommunications oversight, and border control. Recognising this misalignment points to the need for a reconfiguration of legal and operational frameworks that enable coordinated action across the criminal justice system and related regulatory bodies, allowing smartphone theft to be addressed as an integrated illicit market rather than as fragmented offences. While grounded in the Peruvian case, these conclusions speak more broadly to how contemporary policing and state institutions confront high-volume, adaptive property crime in an era where consumer technologies have become central commodities in illegal economies. Declarations Author Contribution N.L. conceived the study, conducted the research, performed the analysis, and wrote the manuscript. Data Availability The data that support the findings of this study are not publicly available due to confidentiality and security restrictions. De-identified data may be available from the author upon reasonable request and subject to institutional approval. 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Deviant Behav 1–18. https://doi.org/10.1080/01639625.2024.2323526 Nagata K, Seki Y (2019) A Method for Smartphone Theft Prevention When the Owner Dozes Off. IEICE Trans Inf Syst E102.D:1686–1688. https://doi.org/10.1587/transinf.2018OFL0001 Observatorio Nacional de Seguridad Ciudadana (2025) Ubicación de las comisarías básicas de la Policía Nacional del Perú 2025 OSIPTEL (2026) Punku OSIPTEL. In: Punku El Portal Inf. Las Telecomunicaciones. https://punku.osiptel.gob.pe/. Accessed 7 July 2024 Perry WL, McInnis B, Price CC, et al (2013) Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations. RAND Corporation PNP (2019) Resolución de la Comandancia General de la Policía Nacional N 764-2019-CG-PNP Poder Judicial del Perú (2025) Estadísticas de la criminalidad 2020 - 2024. Lima Presidencia de la República del Perú (2023) Decreto Legislativo N° 1578 Presidencia de la República del Perú (2004) Decreto Legislativo N 957. Nuevo Código Procesal Penal. Quinn L, Clare J, Lindley J, Morgan F (2022) Explaining Offenders’ Longitudinal Product-Specific Target Selection Through Changes In Disposability, Availability, And Value: An Open-Source Intelligence Web-Scraping Approach. Crime Sci 11:2. https://doi.org/10.1186/s40163-022-00164-1 Smith BT (2017) Understanding Shoplifting of Fast-Moving Consumer Goods: An Application of the CRAVED Model. Secur J 31:428–450. https://doi.org/10.1057/s41284-017-0108-z Thompson R (2016) Portable Electronics and Trends in Goods Stolen from the Person. J Res Crime Delinquency 54:276–298. https://doi.org/10.1177/0022427816660743 Valer C, Reyes A (2022) Mejoramiento del servicio policial de esclarecimiento de denuncias por parte de los departamentos de investigación criminal de Lima Metropolitana. Pontificia Universidad Católica del Perú Villaorduña J, Bürkli H (2021) Estrategias para la prevención del hurto y robo de celulares con un enfoque situacional: El caso de las listas negras de telefonía en Perú. Rev Escpogra PNP 1:46–69 Wellsmith M, Burrell A (2005) The Influence of Purchase Price and Ownership Levels on Theft Targets. Br J Criminol 45:741–764. https://doi.org/10.1093/bjc/azi003 Yu H, Wu S, Zhang Y (2013) Phones’ Theft-Prevention Technology Based on Android OS. In: Proceedings of the 2013 Fifth International Conference on Multimedia Information Networking and Security (MINES ’13). USA, pp 97–100 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 15 Apr, 2026 Reviewers agreed at journal 18 Mar, 2026 Reviewers invited by journal 16 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Submission checks completed at journal 16 Mar, 2026 First submitted to journal 15 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9129978","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607003890,"identity":"94c30fa8-2990-4137-92ea-a7681b5d1059","order_by":0,"name":"Noam López","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBACPgST+QCUkYBfCxsSE6aUeC08BkRqYe89+PAHwx05/mlnvj3mqbnDwM+eY8BcUIFHC8+5ZAMJhmfGErdztxvzHHvGINnzxoB5xhk8WiRyzCQMGA4nNtzO3SbN23CYweAG0BbeNrxazH8kALXMv53zDKzFHqzlH35bGA4AtWy4ncMGsUUCpKUBv18kGwwOGxveTjM3nHPsGY/EmWcFh2ccw62FHxhiH39UHJaTu5387MGbGmDQtSdvfFxQg1sLMDqAGBIjoDg6AOIyHManAaKFAaEFzGLGr2UUjIJRMApGGAAAtWRMv6PLJJ0AAAAASUVORK5CYII=","orcid":"","institution":"Pontifical Catholic University of Peru","correspondingAuthor":true,"prefix":"","firstName":"Noam","middleName":"","lastName":"López","suffix":""}],"badges":[],"createdAt":"2026-03-15 16:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9129978/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9129978/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104919245,"identity":"6026c4d3-5da6-41fd-8f28-e04267410589","added_by":"auto","created_at":"2026-03-18 17:05:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTrends of victimisation in Peru (2014 – 2024)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Author’s elaboration based on data from the National Survey of Budgetary Programmes (ENAPRES) – National Institute of Statistics and Informatics (INEI).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/43ee4a7dc2fff9a985c8c4a9.png"},{"id":104919248,"identity":"b342ef86-1799-479b-a3a4-87d7ca57dabc","added_by":"auto","created_at":"2026-03-18 17:05:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79943,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStatus of Mobile Devices Reported to the Regulator OSIPTEL (2017 – 2025)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Author’s elaboration based on data from the PUNKU Open Data Platform – Supervisory Agency for Private Investment in Telecommunications (OSIPTEL).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/8b9e79b262c77e1440c9cef6.png"},{"id":104919244,"identity":"69304508-a237-4363-91e7-5b4a0c40acde","added_by":"auto","created_at":"2026-03-18 17:05:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":97753,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStatistical Hotspots (Getis–Ord Gi) of Smartphone Theft in Lima and Callao (2018 – 2025)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNote: Statistically significant grid cells at 99% and 95% confidence levels (n=12,791). The vast majority of the urban area (4,483 cells) shows no significant clustering. \u003cem\u003eSource:\u003c/em\u003e Author’s elaboration based on data from the Police Complaint Information System (SIDPOL) – National Police of Peru (PNP), retrieved from the National Observatory of Public Safety (OBNSC) of the Ministry of the Interior (MININTER).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/804478e7e913e97105278b0e.png"},{"id":105034503,"identity":"aed38a66-c148-433d-80fb-d46301dc7506","added_by":"auto","created_at":"2026-03-20 07:23:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":22022,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eEuclidean Distances to the Nearest Police Station: Hotspots vs. Non-Hotspots in Lima and Callao (2018 – 2025)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNote: Comparison between reports within hotspots (n=1,526) and non-hotspots (n=11,267). Boxplots show medians, quartiles, and outliers of distance in meters. \u003cem\u003eSource:\u003c/em\u003e Author’s elaboration based on data from the Police Complaint Information System (SIDPOL) – National Police of Peru (PNP), retrieved from the National Observatory of Public Safety (OBNSC) of the Ministry of the Interior (MININTER).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/fb1f35d8fb061003a603b341.png"},{"id":104919246,"identity":"da8dbde3-aef0-41ba-9673-dc3f6c890686","added_by":"auto","created_at":"2026-03-18 17:05:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":152136,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDensity-Based Spatial Clustering (DBSCAN) of Smartphone Theft in Lima and Callao (2018 – 2025)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNote: Identification of 76 density-based clusters (eps=400m, minPts=15). The central 'megacluster' represents 49.59% of the total georeferenced reports. \u003cem\u003eSource:\u003c/em\u003e Author’s elaboration based on data from the Police Complaint Information System (SIDPOL) –National Police of Peru (PNP), retrieved from the National Observatory of Public Safety (OBNSC) of the Ministry of the Interior (MININTER).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/99f711addc51d8fe4f4515c6.png"},{"id":104919247,"identity":"14c09e98-4849-43a6-942d-478e4b292039","added_by":"auto","created_at":"2026-03-18 17:05:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":684850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe Cycle of Stolen Smartphone Trafficking\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSource:\u003c/em\u003e Author’s elaboration.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/25d24377ce3af40012d615b2.png"},{"id":105562583,"identity":"43df05dd-f080-4515-8f7e-1b3e97ad2c63","added_by":"auto","created_at":"2026-03-27 12:43:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1424109,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9129978/v1/abe06960-4408-4344-86a7-c05c920dba0f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stolen Smartphones as an Illicit Market: Trafficking Chains and Policing Limits in Peru","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSmartphone theft has become a public security issue of increasing magnitude in Latin America. Over the past two decades, studies on property crimes have revealed a notable shift from traditional items like wallets to portable electronic devices, particularly smartphones. This trend suggests an adaptation by criminals to contemporary technologies and the higher value and portability of these devices (Farrell et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Thompson \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). In Peru, the scale of the problem is alarming: approximately 16\u0026nbsp;million handsets have been reported stolen in the last seven years (OSIPTEL \u003cspan class=\"CitationRef\"\u003e2026\u003c/span\u003e), highlighting the existence of a lucrative illegal market sustained by a value chain involving various actors. This phenomenon not only poses a threat to personal property but also to the privacy and security of users' information. In this context, the present study examines \u003cb\u003estolen-smartphone trafficking in Peru as an illicit market and analyses how\u003c/b\u003e the National Police of Peru (PNP) responds to \u003cb\u003ethis complex criminal ecosystem\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe literature has evolved in its understanding of property crimes, recognising the importance of factors such as availability, value, and disposability of items in theft rates (Kirchmaier et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Quinn et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Smartphones combine these attributes in ways that make them especially attractive within illicit markets. In Peru, this appeal is reinforced by weak criminal justice outcomes: between 2020 and 2024, only 55,339 convictions for theft, robbery, and misappropriation were recorded nationwide (Poder Judicial del Perú \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), representing approximately 0.75% of the roughly 7.4\u0026nbsp;million smartphones reported stolen to the Supervisory Agency for Private Investment in Telecommunications (OSIPTEL) during the same period (OSIPTEL \u003cspan class=\"CitationRef\"\u003e2026\u003c/span\u003e). At the same time, the expansion of illicit markets—particularly through digital platforms—has transformed the commercialisation and circulation of stolen devices, allowing them to move rapidly across local, national, and international circuits (Aniello and Caneppele \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Munksgaard \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe police response to this phenomenon presents significant challenges, particularly in resource-constrained contexts where institutional structures may exhibit bureaucratic rigidity. Traditional policing models, focused on reactive responses and preventative patrolling, are increasingly challenged to adapt to a crime that operates on multiple levels and leverages advances in cyber-technology and telecommunications. In this scenario, the literature on predictive policing using big data (Perry et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Brayne \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) offers promising perspectives for property crime, but its implementation requires not only technological resources but also a shift in organisational culture. Moreover, the transnational nature of stolen mobile phone trafficking challenges traditional jurisdictions and requires closer international cooperation (Farrell \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) involving not only police forces but also other state and private entities within the telecommunications sector.\u003c/p\u003e\n\u003ch3\u003eSmartphone Theft as a Trafficking Process\u003c/h3\u003e\n\u003cp\u003eOver the past two decades, property crime has shifted from traditional items such as cash and wallets towards portable electronic devices, particularly smartphones. This trend indicates criminals' adaptation to contemporary technologies and the increased value and portability of these handsets (Thompson \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). The rise in smartphone thefts has underscored the need for crime prevention policies specifically targeting electronic devices (Farrell et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, the traditional market reduction approach is becoming obsolete in countries where offenders and fences specialise in certain items, leading to a more sophisticated black market, as seen in South Africa (Huigen \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Situationally preventive tactics, such as concealing valuable items, are increasingly ineffective, especially as smartphones now act as life-loggers and often replace laptops in various activities (Ali et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). This highlights the need for monitoring the availability, value, and disposability of electronic devices over time to assess theft risk accurately (Kirchmaier et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Quinn et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe CRAVED model (Clarke \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e) explains the frequent theft of items like audio-visual equipment and smartphones (Smith \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Theft patterns reflect different stages of consumer goods' life cycles, suggesting that crime prevention strategies must adapt to these phases (Wellsmith and Burrell \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). The complexity and ubiquity of illicit markets, combined with methodological challenges, make them difficult to study. State prohibitions create lucrative black markets, fuelled by persistent demand and high prices (Kassab and Rosen \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The need to understand these markets from a sociological perspective, considering both supply and demand, as well as the cultural aspects that sustain them, is emphasised (Dewey \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The persistence of illicit markets, despite efforts by the state, highlights the role of intermediaries who convert stolen goods into cash or valuable items, facilitating the supply and demand cycle (Johns and Hayes \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). These dynamics suggest that smartphone theft is better understood as a process sustained by intermediaries, resale infrastructures, and logistical coordination, rather than as a series of isolated theft incidents.\u003c/p\u003e \u003cp\u003eThe rise of online illicit markets has further transformed the commercialisation of stolen goods, moving away from traditional methods. Classified ad platforms, auction sites, and social networks are now the main channels for reselling stolen goods, challenging traditional explanations of illegal market organisation (Munksgaard \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). In response, collaboration with online platforms to implement provenance verification mechanisms could be effective in preventing the disposal of stolen goods (Quinn et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Latin America, smartphone theft is a pervasive security concern. In Peru, \"blacklists\" have been created to block stolen phones, and the Penal Code has been updated to expand the criminalisation of fencing (Villaorduña and Bürkli \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Presidencia de la República del Perú \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). In Colombia, state measures to combat mobile phone theft have had short-term success, but offenders quickly adapt their methods (Díaz \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Understanding the demand for stolen products, as seen in Argentina, is crucial to developing policies that enhance consumer awareness (Heckmann \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSmartphone theft therefore extends beyond property loss. Stolen devices expose victims to secondary harms, including financial fraud, identity misuse, and privacy violations. The technology industry has developed solutions to address this issue, such as wristwatch-type devices with sensors to detect suspicious movements and systems for remote location, locking, and data destruction (Yu et al. \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Jin et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Nagata and Seki \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, machine learning algorithms now enhance theft detection through accelerometer data analysis, integrating technologies like SIM card detection and contextual behaviour analysis (Liu et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite the development of solutions like kill-switches and blacklisting, their effectiveness is limited by implementation challenges and international trafficking. Taken together, existing evidence suggests that smartphone theft should be understood not as a simple street crime but as a trafficking process sustained by organised logistics, intermediaries, and cross-border flows. Addressing such processes requires responses comparable to those applied to other organised illicit markets (Farrell \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e "},{"header":"Data and Methods","content":"\u003cp\u003eThis study employed a concurrent mixed-methods design. Quantitative evidence was drawn from three main sources. First, the analysis addressed victimisation trends using data from the National Survey of Budgetary Programmes (ENAPRES), conducted by the National Institute of Statistics and Informatics (INEI \u003cspan class=\"CitationRef\"\u003e2026\u003c/span\u003e). Second, administrative records from the OSIPTEL served to examine reports of smartphone theft (OSIPTEL \u003cspan class=\"CitationRef\"\u003e2026\u003c/span\u003e). Third, the research utilised police report data from the Police Complaint Information System (SIDPOL) and georeferenced data from 1,332 basic police stations (Observatorio Nacional de Seguridad Ciudadana \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). The latter a spatial statistical analysis of reported smartphone theft incidents and police coverage.\u003c/p\u003e\u003cp\u003eSimultaneously, qualitative data were collected to examine how smartphone theft is understood and addressed operationally within the Peruvian National Police (PNP), specifically within the Criminal Investigation Directorate (DIRINCRI) and the Criminal Investigation Departments (DEPINCRI). Fieldwork conducted between 2022 and 2025 involved twenty-four semi-structured interviews and one focus group with eight police officers experienced in the investigation of property-related offences and crime prevention. The qualitative component was augmented by interviews with nine prosecutors and four former public officials from the Ministry of the Interior. Ethnographic observation took place in five markets dedicated to the sale of stolen smartphones in Lima and Callao, the cities with the highest concentration of smartphone thefts. Finally, a documentary analysis examined ministerial and police plans related to prevention and investigation, alongside a systematic review of press reports on police operations, seizures, and arrests involving the illegal sale of handsets.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eThe Scale of the Phenomenon\u003c/h2\u003e\n\u003cp\u003eSmartphone theft in Peru has evolved from episodic street-level crime into a structural phenomenon of mass victimisation (Figure 1). Following a sharp decline during the COVID-19 pandemic—reaching a low of 18.2% for general victimisation and 5.3% for smartphone theft in 2020—the data reveal a robust recovery of illicit markets. By 2024, general victimisation stabilised at 27.1%, while smartphone theft remained a primary driver of property crime at 9.1%, following a 10% peak in 2023. This resurgence underscores the resilience of the stolen device economy; despite temporary mobility restrictions and policing efforts, the smartphone remains the central commodity of urban insecurity in Peru, affecting approximately 2.8 million citizens in urban areas annually.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOSIPTEL’s administrative records further illustrate the magnitude and persistence of smartphone theft. Between 2017 and 2025, reports of stolen devices declined during the pandemic and increased steadily thereafter, reaching approximately 1.7 million stolen smartphones in 2023 alone (Figure 2). Across this period, more than 16 million smartphones were reported stolen. Despite the existence of blocking and recovery mechanisms since 2017, the sustained volume of stolen devices suggests that these measures have had a limited impact on disrupting the circulation of stolen goods.\u003c/p\u003e\n\u003cp\u003eDespite the scale of smartphone theft, reporting rates have remained stagnant, with only about 15% of victims reporting the incident to the PNP annually (INEI 2023, p. 40). Consequently, approximately 67,236 reports were recorded between 2018 and 2025. In 2022, the police handled approximately 12,000 reports—representing a mere 0.42% of total victims estimated by ENAPRES and 0.71% of cases reported to OSIPTEL. This structural under-reporting, rooted in mistrust of the justice system, implies that the police possess only a marginal fraction of the information necessary to plan and execute investigations.\u003c/p\u003e\n\u003cp\u003eAnalysis of the SIDPOL database indicates that reported cases are heavily concentrated in urban areas, particularly in Lima and Callao. However, a methodological triage of the data reveals a drastic reduction in usable records, dropping from 67,235 to just 12,905 valid cases (19.2%). This substantial loss underscores systemic under-registration and a lack of geographic precision in police reporting. Despite this limitation, the available data reveal statistically significant hotspots (Figure 3) that are not randomly distributed but clustered in less than 8% of the urban grid, with 308 cells identified at a 99% confidence level.\u003c/p\u003e\n\u003cp\u003eA pivotal finding is the 'proximity paradox' (Figure 4). These hotspots are significantly closer to police stations (median distance of 611 m) than isolated reports (median distance of 774 m), a difference confirmed as statistically significant by the Wilcoxon rank sum test (W = 6,126,762, p\u0026lt;0.001). Furthermore, density-based clustering (Figure 5) identifies that 80.7% of all events are grouped into distinct clusters, with a single dominant 'megacluster' accounting for nearly 50% of metropolitan victimisation. Rather than simple deterrence failure, this structural continuity suggests that spatial concentration is driven by victim accessibility to report crime and the persistent location of consolidated illicit smartphone markets that operate with high visibility near urban and security nodes.\u003c/p\u003e\n\u003cp\u003eOf all complaints filed nationwide, according to police statistics officials, only about 15% are investigated by specialised criminal investigation units. For example, DIRINCRI received only 630 cases of theft and robbery in 2022, of which only 28% were solved. Compared to victimisation estimates, according to ENAPRES, the Directorate effectively solved less than 0.01% of smartphone theft incidents affecting the population. This gap underscores a structural limitation in investigative capacity and indicates that criminal policy measures are disconnected from the scale and organisation of this criminal phenomenon.\u003c/p\u003e\n\u003ch2\u003eThe Trafficking Value Chain\u003c/h2\u003e\n\u003cp\u003eThe victimisation stage marks the starting point of the criminal cycle involving stolen smartphones. Offenders primarily employ two methods: theft (without violence) and robbery (with violence). Theft typically occurs in crowded places such as markets, public transportation, and large events. \"Offenders take advantage of victims' distraction in crowded spaces to steal smartphones,\" explains an investigator from a specialised criminal investigation unit. Robbery, by contrast, involves the use of force or intimidation and is more common in contexts with lower police presence. Interviews indicate that offenders adapt their methods strategically, selecting victims and locations based on perceived risk and opportunity. This includes vehicle-based snatching, firearm-enabled assaults, and coordinated gang robberies in commercial establishments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnce the stolen smartphones are obtained, they move to the storage phase, where they are organised and stored before reprogramming and distribution. \"Devices are usually sorted by brand, model, and condition to facilitate subsequent handling,\" explained a detective from a specialised criminal investigation unit. This activity can be carried out by the original offenders or by other actors. They store the handsets to deliver them directly to reprogramming technicians or through intermediaries linked to the sales phase once they have amassed a significant quota. As observed from case reviews, storage is not an isolated activity but is supported by a well-structured network of contacts and storage points. \"We have identified that the storage handlers work in coordination with criminal groups and have connections with sales points to ensure a continuous supply,\" affirmed an officer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTypically, the process continues with the reprogramming phase of the devices. However, with the proliferation of financial operations through mobile banking apps and the emergence of digital wallets from Apple, Google, banks, and other electronic money issuers, the revictimisation stage has emerged. Offenders, upon accessing stolen smartphones, also obtain the personal information stored on them, allowing them to exploit various criminal modalities. A senior officer specialising in high-technology crimes states:\u003c/p\u003e\n\u003cp\u003e\"It's not just the phone they're taking; it's everything inside it. The photos, contacts, banking data [...] all of that is gold for them. It's a double hit: first, they take the phone, and then they drain your money.\"\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the most prevalent criminal modalities is carding, where offenders illegally access victims' bank card data to make small purchases, thus avoiding immediate detection. They also impersonate individuals with good credit histories to make high-value purchases on e-commerce sites. Another modality is SIM Swapping, in which fraudsters obtain victims' personal data and block the SIM card by contacting mobile phone companies, subsequently duplicating it to access digital banking and make transfers to recipient accounts and loan applications. Similarly, a thief transfer involves extracting the SIM card from the stolen or lost device and placing it in another to access information and commit fraud.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, the process advances to the reprogramming stage, essential for removing traces of origin and making stolen smartphones appear new or legal. “Unlocking the phone and altering the IMEI are key steps for these devices to be back in circulation,” explains a senior police commander. The process, known as flashing, involves erasing all data from the phone and reinstalling the same or an updated operating system. However, “when a device is reported stolen, the phone operator uses the IMEI to deactivate it,” explains a specialist from the telecommunications regulatory agency. Therefore, to “resurrect” these phones, technicians use programmes that allow them to change or tamper with this device identity or reuse those that have been associated with devices that were decommissioned or discarded due to obsolescence.\u003c/p\u003e\n\u003cp\u003eThe reprogrammed and ready-for-sale smartphones then move on to the distribution stage. This stage is crucial in the criminal cycle of stolen smartphones, as it involves transporting and delivering the devices to local, national, and international markets. “The distribution [of stolen smartphones] is a well-organised process that includes several layers of intermediaries and specific routes to avoid detection,” notes a specialised investigator from a criminal investigation directorate. Smartphones can be transported through human couriers, private vehicles, and formal transportation services. Locally, the devices are distributed in informal markets and repair shops, typically through small retail stands.\u003c/p\u003e\n\u003cp\u003eWhile the highest concentration of criminal activity occurs in Lima, distribution also extends to other regions, reflecting the nationwide scope of victimisation (INEI 2023). For example, smartphones stolen in Ayacucho are sold in Apurímac (Jornada 2024).\u0026nbsp;International distribution adds an additional level of complexity, as devices are trafficked to neighbouring countries through contraband networks. These operations often rely on weak border controls and corruption. As one high-ranking officer noted, police investigations have identified transnational trafficking routes connecting Peru to Ecuador, Bolivia, and Chile.\u003c/p\u003e\n\u003cp\u003eThe sales stage represents the final link in the criminal chain, where reprogrammed devices re-enter the market. Smartphones are sold in popular markets, second-hand stores, and through online platforms and social networks. In physical markets, stallholders frequently coordinate both reprogramming and sales. In markets such as \u003cem\u003eLas Malvinas\u003c/em\u003e in central Lima, prosecutors have identified dozens of stalls dedicated to this activity\u0026nbsp;(La República 2023).\u0026nbsp;According to officers, this is a highly lucrative business: although prices are lower than those of new devices, the price differential is often marginal. Depending on brand and condition, a stolen smartphone may sell for only 800 to 1,000 PEN less than its retail equivalent. Field verification confirmed these dynamics, with high-end devices such as an iPhone 13 Pro Max selling for approximately 3,850 PEN and a Samsung S22 Ultra for around 2,500 PEN.\u003c/p\u003e\n\u003cp\u003eField information obtained from DIRINCRI reveals that there are at least 21 points of sale for stolen smartphones distributed across various districts of Lima. Officers from the Directorate indicate that these locations form a well-structured network of illicit commerce, as they continue to operate despite efforts to dismantle them. Inspections by local municipalities manage to close down stalls, and police- and prosecutor-led operations have resulted in arrests and seizures. Police officers comment that stallholders and workers have strong connections to assert their interests. As one retired general commander explained, “Thousands of people are well-organised and have good legal defence that keeps them without any convictions to date.”\u003c/p\u003e\n\u003cp\u003eThese six stages allow for a comprehensive synthesis of the complexity inherent in the illicit supply chain of stolen smartphones (Figure 6). Different criminal networks, characterised by varying levels of expertise, propensity for violence, and territorial reach, are embedded in this process. Actors range from offenders engaged in street-level victimisation to technicians capable of unlocking devices and committing cybercrimes, intermediaries who transport smartphones across cities and transnational borders, and vendors who reinsert devices into formal and semi-formal markets. In other words, smartphone theft operates as a trafficking process sustained by coordinated roles rather than isolated criminal acts.\u003c/p\u003e\n\u003ch2\u003eHow Police Respond: Fragmentation by Design\u003c/h2\u003e\n\u003cp\u003eThe PNP addresses smartphone theft through two formally distinct approaches: prevention and investigation, as defined by its organisational regulations and the National Citizen Security Policy. Preventive actions are primarily carried out through the National Directorate of Order and Security (DIRNOS), particularly via the Directorate of Citizen Security (DIRSECIU). According to senior police officials, the preventive response relies mainly on motorised and foot patrols as deterrence and rapid-response mechanisms, complemented by coordination with municipalities and organised community groups.\u003c/p\u003e\n\u003cp\u003ePolice patrols, as outlined in the official protocols (PNP 2019), follow a hierarchical structure with the sector chief as the principal authority. The protocol details specific actions for patrolling, including tactical parking in high-risk zones and citizen contact. However, the implementation of these directives faces significant challenges that undermine their preventive intent, as described by a senior officer responsible for public-order operations:\u003c/p\u003e\n\u003cp\u003e\"In theory, the Sector Chief should maintain constant communication with various actors and effectively coordinate patrols. But the reality is that we face severe budgetary limitations. Often, we lack sufficient operational vehicles in good condition. Additionally, the shortage of personnel forces us to prioritise certain areas, leaving others with less coverage than we should have. This directly affects our ability to prevent crimes like smartphone theft, which require a constant and visible presence.\"\u003c/p\u003e\n\u003cp\u003eThe protocol also establishes guidelines for patrol monitoring, with the precinct chief reviewing patrol routes daily and the sector chiefs submitting weekly reports. However, the effectiveness of this monitoring system is compromised by various factors, as explained by a senior officer with extensive experience in citizen-security operations:\u003c/p\u003e\n\u003cp\u003e\"We're supposed to use technologies like the 24/7 app\u0026nbsp;[...]\u0026nbsp;and the SIPCOP\u0026nbsp;[Police Patrol Planning and Control Information System]\u0026nbsp;to monitor patrol routes. The reality is that many police stations, especially in peripheral or rural areas, lack this technology because they are not equipped with GPS-enabled radios. Even where it's available, we often face connectivity issues or lack adequate training for its use. Additionally, the bureaucratic burden makes it difficult for precinct chiefs to devote the necessary time to effective monitoring. These budgetary and logistical limitations mean that, in practice, our patrol and monitoring system falls far short of what is outlined on paper.\"\u003c/p\u003e\n\u003cp\u003ePolice stations coordinate with local governments to carry out integrated patrols, in line with the priority objective of “Reducing victimisation by theft and robbery in public spaces” (MININTER 2022). \"The coordination between the police and local governments is stipulated within the policy, as the idea is not only to increase surveillance presence on the streets but also to adapt police strategies to the specific needs of each locality,\" notes a specialist who has worked in the Ministry of the Interior (MININTER). Despite this, the reality is that in many jurisdictions, the lack of municipal patrol units, well-maintained municipal vehicles, and trained personnel impedes compliance with the established routes. The specialist further elaborates on the institutional friction hindering these joint efforts, even though there are legislative decrees (Ministerio del Interior 2023a, b) authorise local governments to allocate resources to fund activities that benefit the police:\u003c/p\u003e\n\u003cp\u003e\"Not all authorities are willing to support or work together with their precinct chiefs. There can often be rivalry or competition over who provides better services to the public. But from the Ministry, we insist that local governments coordinate their budget execution with their precincts.\"\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCollaboration with municipalities is also reflected in the implementation of community preventive programmes carried out by police stations nationwide, following directives issued by DIRSECIU. These programmes focus on engaging with educational institutions, parents, students, and organised neighbours to promote a general culture of prevention and protection. Analysis of these initiatives indicates that they primarily aim to strengthen ties between the police and the community and to guide young people towards legality, rather than addressing specific crimes such as smartphone theft.\u003c/p\u003e\n\u003cp\u003eIn practice, however, many of these preventive programmes are only partially implemented. Persistent resource scarcities, a dearth of trained personnel, and logistical constraints hinder their execution. Coordination between police stations and municipalities is frequently affected by institutional rivalries and uneven political commitment, which undermines collaboration and the efficient use of available budgets. As a result, these preventive efforts often fall short of their intended impact.\u003c/p\u003e\n\u003cp\u003eRegarding investigation, the PNP operates under the National Directorate of Criminal Investigation (DIRNIC) as the primary regulatory authority. Among its various line directorates, DIRINCRI stands out. The ROF stipulates that this directorate is responsible for planning and commanding the investigation strategies and operations for offences outlined in the penal code at the national level (Ministerio del Interior 2017, p. 52). \"We are mandated to thoroughly investigate every reported theft case. Additionally, we conduct operations alongside the Public Prosecutor's Office, to dismantle resale networks in markets and sales points,\" mentions a senior commander. Within this Directorate, we find the Robbery Division, the Fraud Division, and the High Technology Division, which have reported some level of action in recent years concerning smartphone trafficking.\u003c/p\u003e\n\u003cp\u003eIn a focus group with departmental heads and senior leadership, it was concluded that the investigative model strictly follows the Penal Code and the Criminal Procedure Code. \"Here, we operate based on the law\u0026nbsp;[...]\u0026nbsp;Non-compliance with these statutes could result in charges by the Public Prosecutor's Office,\" notes a high-ranking officer. This observation underscores the legalistic and regulatory approach of the PNP in its daily operations. It also highlights that police actions are aligned with procedural adherence and the protection of fundamental constitutional guarantees.\u003c/p\u003e\n\u003cp\u003eWithin the framework of these investigative functions, the PNP plays a pivotal role in the Peruvian criminal process, acting as the technical investigative arm under the supervision of the Public Prosecutor's Office. Its responsibilities include receiving complaints, crime scene management, collecting evidence, identifying perpetrators, and securing exhibits related to the offence, among others (Presidencia de la República del Perú 2004). In cases of flagrante delicto, it is authorised to make arrests, always immediately informing the prosecutor. \"The police are essential from receiving the complaint to presenting evidence to the Public Prosecutor's Office. This ensures that investigations are conducted in accordance with the law,\" notes a senior officer from a specialised criminal investigation unit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding smartphone trafficking, the approach remains predominantly legalistic, with a critical observation: each stage is addressed in isolation. The focus is primarily on the victimisation stage, handled by local police stations that undertake initial procedural measures in cases of theft and non-aggravated robbery. When cases involve firearms or gang-related activity, the responsibility is transferred to district-level Criminal Investigation Departments (DEPINCRI). These departments, in coordination with public prosecutors, conduct investigations aimed at identifying the offenders and accomplices, taking statements, generating audio-visual evidence, and apprehending suspects. The Public Prosecutor's Office, for its part, directs the criminal investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecondly, commercialisation is addressed. In this case, operational units formulate operational plans that are classified and approved by their respective police commands. According to the police, more than a hundred operations against smartphone theft are carried out annually in Lima and a similar number across the rest of the country since 2018. These operations exhibit significant variance in outcomes; in some cases, only 50 smartphones are seized, while in others, thousands are reported. Thirdly, reprogramming is addressed, but with greater emphasis since the legal amendment in 2023 (Ministerio del Interior 2023c), as those who clone or tamper with terminal equipment now fall under the criminal offence of fencing. Fourthly, revictimisation—including computer fraud and extortion—is addressed by units specialising in cybercrime.\u003c/p\u003e\n\u003cp\u003eStolen smartphone trafficking can be addressed using special investigative techniques if the investigative units have information that the actors operate as a criminal organisation. Certainly, this would allow for a more robust process, as special investigative techniques stipulated in the Criminal Procedure Code could be applied. However,\u0026nbsp;only five cases have been addressed in this manner to combat stolen smartphone trafficking, according to information obtained from DIRNIC. As evidence, personnel who were part of the High Complexity Division (DIVIAC) team, created in 2016, believe that smartphone trafficking should primarily be handled by criminal investigation departments. \"DIVIAC deals with high-complexity crimes, not just complex ones [...] related to illicit economies of greater national and international significance,\" explains a senior officer with experience in elite investigations.\u003c/p\u003e\n\u003cp\u003ePolice investigation is fragmented both in terms of competencies and methodology. At the district investigation level, investigations follow a basic investigative approach guided by the General Criminal Investigation Methodology, but regulatory constraints prevent these units from addressing organised crime. Within DIRINCRI divisions, police operational intelligence is applied, combining investigative and intelligence functions with support from specialised intelligence structures. DIVIAC, by contrast, utilised a model of Prospective Complex Investigation, in which police officers themselves conduct intelligence activities to generate robust evidence capable of sustaining judicial proceedings. Despite this methodological diversity, these specialised units have played only a limited role in addressing stolen smartphone trafficking. Instead, interventions have been largely concentrated within the State Security Directorate, particularly at the commercialisation stage (Ministerio del Interior 2022).\u003c/p\u003e\n\u003cp\u003eFinally, although stolen smartphone trafficking operates as a structured process, it is not currently recognised in law as such or as an organised crime offence.\u0026nbsp;This lack of recognition constrains police authorities and investigators from deploying the full suite of tools stipulated in the Criminal Procedure Code. A senior intelligence officer explains the operational impact of this legal vacuum.\u003c/p\u003e\n\u003cp\u003e\"It's a pretty complex issue; there isn't a visible leader directing everything\u0026nbsp;[...]\u0026nbsp;It's a dispersed crime, which makes it harder to tackle. Even in drug trafficking, there is a clearer criminal structure. Moreover, since it's not legally classified as an organised crime offence, the police cannot deploy special investigative techniques. The law limits the approach to this problem.\"\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003e\u003c/h1\u003e\n\n\n\n\n"},{"header":"Discussion","content":"\u003cp\u003eThe literature on property crime indicates that portable electronic devices, particularly smartphones, have become principal theft targets due to their high value, portability, and rapid resale potential (Thompson 2016). This pattern is reflected in Peru, where approximately 1.7 million individuals reported smartphone theft in the most recent year of observation. Although the PNP relies heavily on patrol-based prevention strategies, these interventions are not specifically tailored to the dynamics of smartphone theft as an illicit market. Budgetary and logistical constraints—such as personnel shortages and a deficit of operational fleet—undermine the capacity to sustain preventive presence in high-risk areas. This operational gap is particularly critical given that smartphones fit the definition of \"craved\" goods (Clarke, 1999)—items whose concealability and availability make them highly resistant to intermittent deterrence. As previous research suggests, effective crime prevention requires adaptation to market conditions and resource availability rather than generic deterrence strategies (Kirchmaier et al. 2019).\u003c/p\u003e\u003cp\u003eThe incorporation of information technologies such as the \u003cem\u003e24/7\u003c/em\u003e application and SIPCOP reflects broader global trends towards data-driven and predictive policing (Perry et al. 2013; Brayne 2017). However, consistent with findings in other policing contexts, the Peruvian case illustrates how technological adoption alone does not guarantee improved effectiveness. Implementation gaps related to organisational adaptation, training deficits, connectivity hurdles, and administrative overload curtail the operational utility of these tools (Mohler et al. 2015; Ferguson 2017). In practice, digital systems often reinforce existing departmental silos rather than enabling coordinated responses across the disparate stages of smartphone trafficking.\u003c/p\u003e\u003cp\u003eCoordination between police institutions and local governments—formally promoted through the National Citizen Security Policy—also presents significant challenges. While integrated patrols and community-based prevention programmes are mandated, rivalries between municipalities and police stations, resource asymmetries, and uneven operational capacities frequently undermine collaboration. As the policing literature has noted, effective prevention depends on genuine partnerships and shared problem definitions rather than formal coordination alone (Herbert et al. 2017). In this context, community programmes such as School Police (\u003cem\u003ePolicía Escolar\u003c/em\u003e) or Neighbourhood Watch Groups (\u003cem\u003eJuntas Vecinales\u003c/em\u003e) tend to prioritise relationship-building and social legitimacy, but remain weakly connected to specific crime markets such as smartphone theft.\u003c/p\u003e\u003cp\u003eFrom an investigative perspective, the PNP’s response remains predominantly legalistic and segmented, closely aligned with the Penal Code and the Criminal Procedure Code. While this framework safeguards due process and citizens’ rights, it fragments police intervention by addressing victimisation, commercialisation, reprogramming, and revictimisation as separate problems. By failing to address the continuous six-stage trafficking process, investigators miss the connections between street-level theft and the organised logistics of resale. This approach contrasts with insights from the literature on illicit markets, which emphasise the importance of integrated strategies capable of addressing interconnected criminal processes (Kassab and Rosen 2019; Dewey 2019). Moreover, the internal fragmentation of competencies and investigative methodologies within the police generates uneven effectiveness across units. Although special investigative techniques—such as telecommunications interception or undercover operations—could enhance responses to smartphone trafficking, their limited use reflects broader constraints in operational intelligence and institutional design (Banister et al. 2015; Valer and Reyes 2022).\u003c/p\u003e\u003cp\u003eCollectively, these implications suggest that the constrained efficacy of state and police responses to smartphone theft in Peru is not a function of individual effort or commitment, but of institutional architecture. Policing models organised around isolated incidents and legal categories are ill-equipped to address offences that operate as distributed, adaptive illicit markets. More broadly, the Peruvian case shows how high-volume property crime can acquire the organisational features of a trafficking economy, with specialised roles, resilient resale channels, and cross-border circulation. This misalignment has direct consequences for both prevention and investigation and raises broader questions about how police institutions adapt to high-volume property crimes that increasingly resemble trafficking processes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this article, we have evaluated how the Peruvian state, and especially the police, responds to smartphone trafficking, demonstrating that it relies on a conjunction of preventive and investigative strategies rather than a single, coherent approach. Police interventions range from patrol-based prevention and market inspections to criminal investigations and technological measures such as IMEI blocking. However, despite the incorporation of information technologies and periodic operational efforts, these responses remain curtailed by logistical limitations, human resource shortages, and uneven implementation capacity\u0026mdash;challenges that mirror broader difficulties identified in the policing literature regarding the effective translation of crime prevention strategies into practice.\u003c/p\u003e \u003cp\u003eOur findings demonstrate that the policing response to smartphone trafficking is structurally fragmented. Police actions are organised around isolated offences and procedural stages rather than the integrated criminal process through which stolen smartphones circulate. Although the Criminal Procedure Code mandates police intervention to guarantee access to justice, this legalistic framework has proven insufficient to address the scale and complexity of the problem. Over 16\u0026nbsp;million smartphones have been trafficked in Peru in the past eight years, while the predominant response has consisted of intermittent market interventions and device seizures. Such case-by-case and stage-specific approaches fail to match the magnitude of the illicit market and allow criminal networks to adapt, reconfigure, and become increasingly difficult to detect and dismantle.\u003c/p\u003e \u003cp\u003eThe study further underscores the limitations of recent regulatory and technological measures, including the blocking of devices with altered IMEIs by the Ministry of the Interior and OSIPTEL. Despite these efforts, technicians continue to reactivate devices, and intermediaries successfully commercialise stolen smartphones both domestically and internationally. This persistence underscores the sophistication and adaptability of the illicit smartphone market, consistent with research on high-demand illicit markets that rapidly adjust to enforcement pressures (Aniello and Caneppele \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Munksgaard \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTaken together, these findings suggest that the limited effectiveness of state responses to smartphone theft in Peru is not primarily a matter of enforcement intensity, but of institutional design. Conceptualising smartphone theft as a series of discrete property offences obscures its operation as a trafficking process sustained by organised logistics, intermediaries, and transnational flows. This misrecognition is replicated not only within police institutions but also across the broader constellation of public agencies involved in regulation, prosecution, telecommunications oversight, and border control. Recognising this misalignment points to the need for a reconfiguration of legal and operational frameworks that enable coordinated action across the criminal justice system and related regulatory bodies, allowing smartphone theft to be addressed as an integrated illicit market rather than as fragmented offences. While grounded in the Peruvian case, these conclusions speak more broadly to how contemporary policing and state institutions confront high-volume, adaptive property crime in an era where consumer technologies have become central commodities in illegal economies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eN.L. conceived the study, conducted the research, performed the analysis, and wrote the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not publicly available due to confidentiality and security restrictions. De-identified data may be available from the author upon reasonable request and subject to institutional approval.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAli S, Khusro S, Khan A, Khan H (2022) Smartphone-Based Lifelogging: Toward Realization of Personal Big Data. 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USA, pp 97\u0026ndash;100\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"trends-in-organized-crime","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tioc","sideBox":"Learn more about [Trends in Organized Crime](http://link.springer.com/journal/12117)","snPcode":"12117","submissionUrl":"https://submission.springernature.com/new-submission/12117/3","title":"Trends in Organized Crime","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"illicit markets, smartphone theft, trafficking chains, stolen goods markets, Peru","lastPublishedDoi":"10.21203/rs.3.rs-9129978/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9129978/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article examines stolen smartphones as an illicit market in Peru, sustained by trafficking chains, specialised intermediaries, and adaptable resale infrastructures. Drawing on a concurrent mixed-methods design, the study combines national victimisation survey data, telecommunications administrative records, police complaint data, spatial analysis, qualitative interviews with police officers, prosecutors, and former officials, ethnographic observation in illegal resale markets, and documentary review. The findings show that smartphone theft is not a set of isolated street offences but a multi-stage trafficking process involving victimisation, storage, revictimisation, reprogramming, distribution, and resale. This chain enables stolen devices to circulate across local, national, and cross-border markets, while exposing victims to secondary harms such as fraud, identity misuse, and financial losses. The study further finds a structural mismatch between the organisation of this illicit market and state responses. Although police interventions combine prevention and investigation, they remain fragmented across isolated offences, procedural stages, and segmented institutional competencies. As a result, enforcement tends to target visible points of the market, particularly street theft and retail resale, while leaving the broader trafficking chain relatively intact. Reframing smartphone theft as an illicit market highlights the institutional and coordination challenges involved in disrupting high-volume property crime economies.\u003c/p\u003e","manuscriptTitle":"Stolen Smartphones as an Illicit Market: Trafficking Chains and Policing Limits in Peru","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 17:05:55","doi":"10.21203/rs.3.rs-9129978/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-15T14:37:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2400187927294523666189906824065964577","date":"2026-03-18T20:23:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-16T14:29:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T14:22:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-16T14:21:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Trends in Organized Crime","date":"2026-03-15T16:06:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"trends-in-organized-crime","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tioc","sideBox":"Learn more about [Trends in Organized Crime](http://link.springer.com/journal/12117)","snPcode":"12117","submissionUrl":"https://submission.springernature.com/new-submission/12117/3","title":"Trends in Organized Crime","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4ffb93c4-5af7-4ebb-82cc-885fefb36621","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T17:05:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 17:05:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9129978","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9129978","identity":"rs-9129978","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}