What is Fraud Analytics ?
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.
Why it matters now ?
The world has changed. Are your fraud controls still relevant?
These days, nearly everyone engaged in fraud leaves behind a trail of digital fingerprints. This presents a big opportunity for companies to prevent further harm—but it’s often only considered after the damage has been done. 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. This development couldn’t occur at a better time, as events and regulators alike are challenging the controls organizations have used for years. In areas of anti-fraud, anti-bribery, and anti-money laundering, the regulatory environment has tightened. At the same time, fraud, corruption, and abuse are unrelenting—and constantly evolving. It’s a different world out there. And fraud analytics can help make sense of it.
Why Fraud Analytics ?
More data, more opportunities
Anomaly detection and rules-based methods have been in widespread use to combat fraud, corruption, and abuse for more than 20 years. They’re powerful tools, but they still have their limits. Adding analytics to this mix can significantly expand fraud detection capabilities, enhancing the “white box” approach of the rules-based method.1 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.
The Potential Benefits
Identify hidden patterns Unsupervised or non-rules-based analyses driven by analytics technology can uncover new patterns, trends, fraudulent schemes, and scenarios that traditional approaches miss.
Enhance and extend existing efforts Analytics need not replace what you’re already doing—it can be an extra layer to add punch to your existing efforts.
Cross the divide Fraud analytics can pull data from across your organization into one central platform, helping create a true, enterprise-wide approach.
Measure and improve performance What’s working? What’s not? With fraud analytics in place, you don’t have to guess. The data tells the story.