Financial Institutions rely on models for their various business types. What if these models shift, or there is a cause for concern and potential fraud? How does a large firm track these large or small changes quickly? Today’s story shows how a financial institution discovered a trend notably above the expected range. The data points had been steady for several months, but then suddenly jumped for multiple days.
The Outlier Automated Business Analysis platform identified a sudden increase in a risk model score for a large US-based financial institution. The business stakeholders shared how Outlier’s insight reinforced the value that Outlier provides and saves their fraud analysts time in spotting unique changes to their risk models, which they use to track systemic fraud for their credit card clients and merchants.
Reading How A Financial Institution Investigates Potential Fraud
Outlier identified an upswing in the credit score for a certain merchant type, Automobiles and Vehicles. Using Outlier’s Root Cause Analysis feature, this customer immediately knew the exact merchant category, Service Stations, and investigated further to understand why this increase occurred to resolve the issue. Without Outlier, the credit score might have escalated further to an even larger gas fraud incident. This story affirmed to the customer that Outlier is a reliable validation tool for automated business analysis.
You too can identify meaningful trends in your data with Outlier. Outlier empowers businesses to take a deeper look at their data and uncover unexpected trends quickly. Sign up for a custom demo to see how a financial institution investigates potential fraud.