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Crime Scoring & Prediction

Crime often ranks at the top of public concern as it affects the general sentiment of safety and impact us on day-to-day quality of life. Crimes are often reported as crime rates regardless of severity. Clear visibility on the seriousness of crimes, profiling of offenders patterns and accurate prediction of criminal acts provides tremendous benefits to national safety and security. For law enforcement, it allows effective planning, deployment and policing. For immigration and law makers, it helps decision makers in enacting the right policies to restrict potential criminals of certain demographic background from entering the country and crafting effective measures of security screening and clearance.


Development of Crime Severity Index (CSI)

Build a country-level crime index, quantifying each crime, scoring every individual according to the potential security risk to society and track the national crime threat across time and region.

Segmentation of Criminal Profiles

Cluster and/or group criminals based on similarities across perpetuated crimes, creating distinct stratified risk segments of various threat levels from innocent to extremely dangerous  

Profiling of Each Crime Segment

 Developed a profile for each criminal segment detailing dominant trends and persisting patterns associated with each group to better understand drivers and motivation.

Predictive Crime Classification

Build a predictive crime model capable of classifying any new individual into one of the crime segments and assigning a risk score that reflects the potential criminal liability to society

Airport Passenger Analytics

Every year a record number of travelers fly between more cities leaving a trail of data footprints. Passengers data, including demographic, booking and travel behavior reveals much needed insights for security and law enforcement to ensure appropriate management of security risk, potential breaches and unlawful suspicious activities. Using machine learning and social network analysis, Cognitro has been able to help the security apparatus around the world discover seasonal trends, travel anomalies and discover networks of passengers linked through hidden factors. These insights carry a tremendous value to for the designated authorities to enhance the security level in airports and improve the services for the passengers.


Seasonal Travel Trends Analysis (STTA)

 Detect trends in passengers travel origin/destination for given demographics, travel behavior and booking behavior.

Travel Pattern Anomalies Analysis (TPAA)

Detect suspicious travel patterns for a controlled group of passengers in specific flights with common origin / destination patterns.

Travelers Network Analysis (TNA)

 Link travelers in the same flight with demographics and booking behavior. As well as, link specific travelers with other previous flights.