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Four Strategies to Optimize Your Decisioning

Today’s consumers demand speed and convenience. As lending becomes more competitive, it is essential to optimize decisioning to retain market share.
A credit union lending team optimize decisioning discussion.

Today’s consumers demand speed and convenience. They are busier, more distracted, and less willing to wait. Their expectation for obtaining credit is no exception. Progressive financial institutions make credit offers available in minutes, and their success is the result of automated approvals.

When approvals are delayed by a manual review, qualified applicants may accept an offer from a faster lender. As lending becomes more competitive, it is essential to optimize decisioning to retain market share. Consider these vital strategies:

1. Artificial Intelligence (AI)

Traditional risk models may use less than 20 attributes and often only consider information found in a credit report. AI can evaluate hundreds of attributes, including data from applications, credit files, and alternative sources, to create more accurate risk models. These models improve revenue from increased loan production, create cost savings through efficiency gains, and reduce losses. With more precise risk assessments, more decisions can be automated.

2. Configurability and Testing

A configurable decision engine with testing capabilities can improve automation. Credit unions should avoid systems with limited decisioning options and look for ones that offer rule-builders, decision trees, and modeling capabilities to validate decisions before implementation. A testing environment helps administrators make informed changes and improve strategies. Further, instant decision ratios will remain low if the system does not offer adequate tools for setting loan amounts, terms, and conditions appropriate for each consumer’s unique credit experience and capacity to pay.

3. Credit Offers and Services

Many lenders obtain “written instructions” from borrowers during the application process to provide additional offers of credit or services. When applying for credit, the decision engine should evaluate available data to offer relevant products to the borrower. Some systems customize offers based on loans in the credit file to reduce interest and monthly payments. Members are generally receptive to offers that can improve their financial health. They help build better relationships and solidify the credit union’s reputation.

4. Fraud Tools

It’s become easier to falsify information. Fake paystub sites are abundant, easy to use, and common fraud tactics. Income is overstated on roughly 38% of loan applications, leading to a 90% increase in delinquency within the first 60 days, according to Informed.IQ. This impacts the credit union’s ability to assess credit risk and manage portfolio performance, and it can be costly.

Modern fraud solutions leverage application data, behavioral analytics, and device authentication to thwart the new tactics of bad players. By incorporating these tools, credit unions can confidently verify application information and prevent fraudulent activities — a critical component of an automated decision strategy.

Conclusion

By adopting these advanced decisioning strategies, credit unions can approve creditworthy applicants in real-time, increasing revenue, reducing losses, and improving efficiency. Embracing AI, configurable decision engines, customized credit offers, and enhanced fraud tools position credit unions to stay competitive and better meet the needs of borrowers. As technology evolves, optimizing lending processes will be essential for continued success.

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