Finalist and winning proposals for the Data for Security Contest Bogota 2026

DATA ANÁDIMA, a team composed of Michelt Estefany Guarín Guarín, Ana Sofía Sánchez Segura, and David Alejandro Rodríguez Caballero—students of Political Science and Economics—who, under the guidance of Professor Santiago Neira, argued that infrastructure projects have varying impacts on safety and business performance, and therefore recommend implementing public policies tailored to the specific nature of the impact. First, they propose improving the physical environment through a “Visible Construction” protocol that ensures adequate lighting at construction sites, and complementing this with a “Safe Corridors” program that coordinates cleanup, social services, and surveillance efforts. Additionally, it suggests leveraging available data to build predictive models that identify businesses with a high perception of insecurity and prioritize their attention, using optimized machine learning techniques to detect critical cases.

Together, these measures aim to strengthen the resilience of the business community during construction, demonstrating that proper management of the urban environment can mitigate negative effects and facilitate business adaptation.

RANDOM FOREST, a team composed of Tomás Valderrama, Andrea Figueroa, and David Santiago Rodríguez—all statistics students—who, under the guidance of professor Alexander Trilleras, found that victimization and the perception of business insecurity in Bogotá result from nonlinear interactions between sector, size, reporting behavior, and risk exposure; patterns that a model can decode and translate into micro-segmented early warnings with a gender-focused approach. Based on this finding, they developed Canopy, an analytical platform that integrates the ECN and EPV to assess business insecurity in Bogotá, including the BACANO index to provide actionable recommendations tailored to each business profile.

GEOBIT, a team composed of Hainer Andrés Mejía, Ana Sofía Daza Tellez, and Nelson Andrey Garcia—all data science students—and under the guidance of professor Alber Ferney Montenegro, set out to analyze how major infrastructure projects in Bogotá, such as the Metro and the TransMilenio trunk lines, are having unintended impacts on safety and the business landscape in the affected areas. By integrating multiple data sources, the team identified two distinct effects: on the one hand, an increase in citizens’ perception of insecurity, associated with physical changes in the environment such as poor lighting, detours, and urban disorder, without necessarily corresponding to an increase in actual victimization; and on the other, a more critical impact on business owners, who face higher levels of victimization, particularly through extortion, due to gaps in oversight exploited by criminal actors. This phenomenon is reflected in the disappearance of more than 5,000 businesses concentrated in areas with active construction projects. In response, the proposal outlines a set of solutions that include immediate measures to improve the perception of safety, strategies for the direct protection of business owners, and public policy guidelines aimed at monitoring and mitigating these effects in the medium term.

TULKUNES, a team composed of Laura Valeria Mora, Juan Sebastian Urrea, and Jesus Ignacio Correcha, students of engineering and economics. Their study provides evidence that perceptions of insecurity are positively associated with business closures in Bogotá. This exploratory finding, though not conclusive, points in the theoretically expected direction and suggests that restoring institutional trust could be more cost-effective for protecting the business community than simply increasing the police force.

USTA POWER, a team composed of Ximena Andrea Arias and Natalia González, under the guidance of Carlos Zainea, presented the Urban Territorial Exposure Index for the First Metro Line (IETU-PLM), a quantitative tool that measures the relative exposure of nine neighborhoods in Bogotá to the disruption caused by public transportation infrastructure projects, with an emphasis on the safety of MSME businesses. The findings of the IETU-PLM provide diagnostic insights that can guide management decisions during the PLM construction works.