TAMPA, Fla.– Trellance, a provider of analytics, cloud and talent solutions, has announced a new Fair Lending Solution it said is designed to help credit unions identify potential issues prior to audits and “prepare to answer auditors’ questions accordingly.”
What Solution Can Do
Trellance said the solution reviews credit union data and identifies potential instances of:
- Disparate treatment by reviewing for notation of explicitly considered prohibited factors affecting protected ages, races and genders.
- Redlining by geocoding credit unions’ loan portfolios and mapping them against underserved zip codes.
- Disparate impact by analyzing credit union practices and testing the impact of otherwise neutral policies that disproportionately impact persons of protected classes.
Determining Factors at Play
“Once identified, credit unions can use the software to determine if bias factored into the final lending decision, or if there were other factors at play,” Trellance said. “Identifying these instances before an audit can help credit unions to ensure they are prepared for auditor questions as they arise.”
In addition, Trellance said the new solution reviews all levels of a credit union’s lending portfolio, not just the mortgage portfolio. It uses Bayesian Improved Surname Geocoding to identify the race of applicants, even when such data is unable to be collected on application forms, the company added.
Adding ‘Context’
“We know that credit unions strive to treat every member fairly,” said Dan Price, VP of Lending & Regulatory Analytics at Trellance. “But publicly available data, that doesn’t include context and other contributing factors, tends to create an image of bias. We built the Fair Lending Solution so that credit unions can identify trends and add context where the raw data doesn’t tell the whole story.”
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