The threat of fraud hangs over all financial institutions, forcing them to strike a daily balance between maintaining a vital customer experience and protecting their assets.
It's a constant battle, with fraudsters growing more sophisticated to outwit financial institutions. Banks and credit unions need every weapon they can get. Hybrid analytics offers several rolled into one.
It's a model that uses data, high-end analytics and in-house expertise to detect and mitigate fraud. The hybrid analytics model relies on data from the industry and the individual institution, creating a net that captures the breadth of fraud across a consortium as well as specific patterns at a particular bank or credit union.
- Create fraud predictions by customizing for each bank or credit union the weighting of industry and institution trends
- Reduce the number of false positives by drilling down through behavior data to identify individual consumer trends
- Incorporate multiple predictive techniques to boost fraud detection performance by as much as 15 percent
- Leverage multiple data sets, while maintaining flexibility, to create a best-of-breed modeling environment
- Emphasize the experience, intuition and business knowledge of fraud analysts to adjust and enhance the analytic model