Retailers have relied heavily on monitored/recorded video to identify and pursue theft inside physical retail, sometimes coupled with attached product sensors that alarm at exit and often damage goods if not removed appropriately.
Goals and Objectives
Proactively reduce risk and loss by combining physical loss prevention measures with predictive and prescriptive analytics that quickly identify customer- and employee-driven sources of risk and loss across channels and locations, enabling preventive action. Similarly, automate the process of compiling evidence of crime, risks, and so forth as necessary to drive self-improving processes and actions.
Video, content analytics, AI/cognitive analytics, machine learning, loss prevention systems, IoT, facial recognition, biometrics, multicloud management, serverless computing, and 5G connectivity
Use Case Summary
Next-generation loss prevention proactively reduces risk and loss by applying a variety of risk assessment and loss prevention measures that quickly identify potential sources of risk and loss, enabling preventive action, automating the process of compiling evidence of crime and risks, and driving self-improving processes and actions.