More business than ever is conducted online, creating more opportunities for expensive and brand-damaging fraudulent activity, from credit card theft to account hijacking to money laundering. While rules engines and machine learning can signal a suspect transaction, a "human in the loop" is needed to avoid false positives that drain productivity and upset customers. And time matters, since fraudsters exploit stolen assets quickly and repeatedly until they are detected and shut down.
Most analytics systems respond too slowly to support quick interactive investigation and timely disposition of flagged transactions. This is especially true for large fraud operations departments involving hundreds of fraud investigators. Slow response leads to lower productivity for fraud teams and a longer time to resolution for each case.
Imply is purpose-built for hot analytics, where fresh data and fast query response across large numbers of users is critical. Fraud operations is a quintessential hot analytics use case, as suspicious events need to move from source to detection to investigation and disposition quickly. With Imply, fraud teams process more cases with higher accuracy, saving money and reducing risk for the business.
Specifically, Imply provides: