Fraud analytics combines analytic technology and techniques with human interaction to help detect potential improper transactions, such as those based on fraud and/or bribery, either before the transactions are completed or after they occur. The process of fraud analytics involves gathering and storing relevant data and mining it for patterns, discrepancies, and anomalies. The findings are then translated into insights that can allow a company to manage potential threats before they occur as well as develop a proactive fraud and bribery detection environment.
Leaders in fraud prevention are taking advantage of new tools and technologies to harness their data to sniff out instances of fraud, potentially before they fully unfold. Not only can analytics tools enhance rules-based testing methods, but they can also help measure performance to standardize and help fine tune controls for constant improvement. That’s a big deal for companies awash in data—data that could be put to better use.
Fraud analytics tools and technologies;
- Identify hidden patterns
- Enhance and extend existing efforts
- Cross the divide
- Measure and improve performance
It doesn’t take a massive initiative to get fraud analytics up and running. Many find that it works well to start with a limited project, and then expand from there. It can take as little as a few weeks.