Streamline Low Fraud Risk Loans? Focus on Low-Risk Scores

How can lenders more quickly book low fraud risk loans? It may require a mindset you haven’t considered.

Consider this: At some point in your life, someone probably told you to ‘take the high road’ when faced with a difficult decision. Wise advice. 

However, financial institutions using predictive models to identify fraud and high-risk activity may also find the ‘low’ road beneficial.  By ‘low’ road, we mean leveraging predictive models to focus more on low-risk scores – or ‘what’s NOT risky’.

How Predictive Analytic Models Rank High and Low Fraud Risk Loans

Predictive models of all types have been around for decades. They find fraudulent credit card, check, and wire transactions, as well as mortgages and auto loans. The model uses historical data (from a single institution or a collection of institutions) to generate a predictive element. This is generally displayed as a score (e.g., 001-999). 

It’s easy to see why they’ve become so popular and effective. A good model ranks fraud risk so efficiently that lenders can review only a small percentage of their application volume to catch a significant portion of their potential fraud.

Why Take the ‘Low’ Road to Low Fraud Risk Loan Applications?

For risk managers tasked with reducing fraud losses and operational costs, the ‘low’ road is more important than ever. As we’ve shown above, the beauty of a robust predictive model is that it tells you where the largest clusters of frauds are. That means it also tells you where the frauds likely are not.

Risk managers report that focusing on the lower scores of their existing models can be equally powerful in the drive for operational efficiencies and cost savings. Some of the potential benefits are:

  • Approve more transactions/loans with less friction
  • Perform fewer reviews and require less stipulations for new business
  • Align workload to ensure lower-risk cases are routed to less seasoned analysts. This enables the most highly trained associates to focus on the fraud-rich review populations
  • Adjust pricing based on lower risk

Maximize Your Fraud Model: Take Both the ‘High’ and the ‘Low’ Road

The benefits of maximizing both ends of the score spectrum can be powerful across all production types. As just one example, consider auto lending. 

As a risk manager, you want your fraud analysts and underwriters focused on high-scoring applications to ensure they’re not generating loans to fraudsters or those unlikely to repay. But what if, at the same time, they also identified the lowest-scoring, lowest-risk applications? This would allow them to potentially apply fewer stipulations to those loans. 

Minimizing stipulations on the lowest-risk loans will save valuable time and operational expense. Fewer stipulations also improve the likelihood that the deal will be captured and funded. Finally, in some cases, the total value of fewer stipulations and increased fundings can be more meaningful to the bottom line than finding fraud. 

Learn more about Point Predictive’s Artificial and Natural Intelligence [AI+NI]TM approach to streamlining your low fraud risk loan process.