Retail shrink mitigation and prevention

A method, comprising:

• receiving historical transaction data and security data from a store;
• training a shrink risk factor machine learning (MLM) using the historical data to identify patterns associated with shrink events and generate risk factors;
• training a shrink mitigation recommendation MLM on the risk factors to generate prescriptive actions;
• receiving real-time data from at least one store system during store operations;
• processing the real-time data using the shrink risk factor MLM to identify at least one current risk factor;
• generating, by the shrink mitigation recommendation MLM, at least one prescriptive action to mitigate the at least one current risk factor;
• and
• providing the at least one prescriptive action to the at least one store system via an application programming interface (API).

A system, comprising:

• a cloud server comprising:
• a shrink risk factor machine learning (MLM) configured to process real-time store data and output shrink risk factors;
• a shrink mitigation recommendation MLM configured to generate prescriptive actions based on the shrink factors;
• and
• an application programming interface (API) configured to provide the prescriptive actions to at least one store system of a store;
• wherein the cloud server is configured to perform operations comprising:
• receiving historical and real-time data from at least one store computer vision application and a store transaction system;
• continuously updating the shrink risk factor MLM and the shrink mitigation recommendation MLM based on effectiveness of implemented prescriptive actions at the store;
• and
• providing at least one real-time shrink prevention action generated by the shrink mitigation recommendation MLM to the at least one store system during an ongoing transaction at the store.