FairPlay provides fairness analytics tools that integrate into AI decision-making processes to identify and mitigate algorithmic bias in lending practices. By enabling real-time monitoring and analysis, FairPlay enhances compliance and increases approval rates for protected classes without elevating risk.
Funding
$24.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
NPFounders
Product
Problem
Lending practices can inadvertently perpetuate bias against protected classes, leading to unfair loan denials and pricing disparities. Traditional methods for identifying and mitigating algorithmic bias are often slow, complex, and fail to provide real-time monitoring capabilities. This can result in compliance issues, reputational damage, and lost revenue opportunities for lenders.
Solution
FairPlay offers a fairness-as-a-service solution that integrates directly into AI-powered lending decision processes to detect and remediate algorithmic bias. The platform provides fast, actionable results, delivering fair lending and disparate impact analysis in a fraction of the time compared to traditional methods. By continuously monitoring underwriting and pricing decisions, FairPlay helps lenders proactively identify and address potential bias, ensuring compliance with fair lending laws. The software also includes a second-look process that re-evaluates declined applicants, considering additional data to identify creditworthy individuals who may have been overlooked due to incomplete or biased data.
Target Audience
FairPlay primarily serves banks, fintech companies, and other financial institutions that utilize AI in their lending processes and are seeking to ensure fairness, maintain compliance, and expand access to credit for underserved populations.
Features
- Bias detection in credit models to identify algorithmic behavior causing undesired results
- "Fairness through awareness" using additional data about Black applicants, female applicants, people of color, and other disadvantaged groups
- Real-time monitoring of underwriting and pricing decisions to guard against degradation
- Disparate impact analysis to identify and quantify disparities in lending outcomes
- Identification of key drivers of disparity to pinpoint areas for improvement
- Integration via SFTP or API for seamless data transfer and analysis
- Ability to increase approval rates for protected classes without increasing risk