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Focus on fairness in your lending processes

Focus on Fairness in Your Lending Processes

Lenders who have not integrated digital elements into the lending process are at a disadvantage in both the speed of churning out loans and in satisfying the customer’s ever-growing desire for a completely digital interface. A great digital experience involves understanding customer needs and designing an interface with empathy to the user. With this in mind, have you considered the role digital processes also play in combatting bias in the loan origination process?

Discrimination: Costly to All

Discrimination in the loan origination process affects people in terms of race, gender and disability as well as other marginalized people groups. In cases where banks were found guilty of discriminatory practices, investigators uncovered that lenders were treating minority borrowers unfairly—such as holding certain people groups to a higher standard of qualification or charging higher rates for mortgages. Despite the passage of legislation meant to combat discrimination in lending—such as the 1968 Fair Housing Act and the 1974 Equal Credit Opportunity Act—discriminatory practices persist across the financial services industry. Lenders alleged of such practices face costly lawsuits and loss of reputation. In 2012, Wells Fargo paid $175 million to resolve allegations that it engaged in a pattern of discrimination against Blacks and Hispanics in its mortgage lending.

Algorithms Diminish Bias

Discrimination in lending is falling thanks to fintech algorithms according to a study co-authored by Dr. Nancy Wallace, a chair in real estate capital markets at Berkeley’s Haas School of Business. Dr. Wallace found that fintech algorithms diminished bias in loan pricing by 40 percent and did not discriminate at all against minority groups in acceptance or rejection of loans. While AI tools can greatly increase efficiency in automating the loan application process, there’s still room for improvement to ensure technology doesn’t discriminate against minority groups.

Retooling Toward a More Equitable Future

At first glance, you would think algorithms in digital decision-making tools should be more objective than a flesh-and-blood decision-maker. However, the systems in which the algorithms are applied need to be continually tested and re-tooled to protect against discrimination. AI algorithms don’t understand what discrimination is so financial professionals need to be ready to minimize the risk of bias as effectively as possible by continually monitory and auditing their digital systems.

Complex Lending Decisions With A Human Touch

For all of the advantages AI-driven systems provide, there still needs to be a human element to ensure that no one is at a disadvantage due to race or disability in the loan application process. Financial institutions can utilize solutions that ensure extra layers of defense are built in to prevent bias from creeping into its machine-driven technologies. Partnering with a financial software services provider who understands your ongoing lending needs is essential to success in a digital world.

Lenders are increasingly facing a critical challenge—keeping up with regulatory changes, mitigating risk, providing equal access to everyone, and all while keeping up with customer expectations in a highly digital economy. At Accutive, our decades of experience in providing end-to-end solutions in lending can help you meet your many objectives. Now more than ever, we can help your lending team digitally transform the way you do lending—with fairness for all. Discover more about our comprehensive solutions here and get on the path to a streamlined digital lending future.

Accutive FinTech is the financial technologies arm of Accutive, a boutique firm for end-to-end cybersecurity and financial technologies services and solutions. Accutive FinTech specializes in MuleSoft Integrations for Financial Services, Temenos Journey Manager, Temenos LMS, AML Solutions, HID IDV, and LOS solutions. Accutive’s test data management platform, Accutive Data Discovery and Data Masking, is a powerful tool for data discovery, data subserving, data masking, data automation, and data tokenization.
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