Could Penalties for Good Credit spread to Private Markets?
“Mortgage borrowers with good credit may face higher costs under a new scheme from federal mortgage associations Fannie Mae and Freddie Mac.” Ironically, this was the opening sentence in a recent article in “Reason” Magazine. There is very little “reason” involved in this policy.
Fortunately, these latest changes in credit scoring are confined to a niche market in the home mortgage industry. The Artificial Intelligence algorithms that calculate rates, which were implemented May 1, 2023, will “facilitate equitable and sustainable access to homeownership”, according to the Director of the FHA.
It remains to be seen whether this mindset could spread to private credit markets, but Artificial Intelligence settings based upon individually selected parameters are currently being implemented by many private financial institutions. The Leasing Industry is no exception. However, companies such as Landmark Financial Corporation may be able to offer a better solution.
While there are benefits to auto credit systems, there are also downsides that may unfairly reject or penalize customers based upon questionable settings. Experian explained the benefits: “machine learning models can increase accuracy and effectiveness, allowing lenders to make better decisions. When applied to credit decisioning, lenders can achieve a 25 percent reduction in exposure to risky customers and a 35 percent decrease in non-performing loans.”
Inevitably, some consumers may “fall between the A.I. cracks”. Can they have the best of both worlds though, provided they work with lenders, such as Landmark Financial Corporation who apply a hybrid credit decisioning system? It offers efficiency and also the opportunity for personal communication to explain and clarify economic situations and goals. Forty years of hands-on experience with clients can make all the difference!
Let us know if we can be of service,
Kevin F. Clune, CLFP
kclune@clune.net
Clune & Company, A Division of
Landmark Financial Corporation
