Algorithmic Credit Scoring and FICO's Role in Developing Accurate, Unbiased, and Fair Credit Scoring Model

FICO® Score considers objective factors predictive of credit performance based on a consumerís credit bureau file, with a model free of bias, resulting in a ìcredit score that is objective and more accurate.î The launch of FICO Score to lending helped expand consumer credit access by reducing subjective biases in manual underwriting adversely affecting lending decisions. Many Machine Learning advances in credit scoring surface unfair lending concerns not present in the FICO Score.

• Expanded consumer credit access by increasing model accuracy 
• A score that is based on neutral objective factors and is not biased against protected groups 
• The model does not score individuals in protected groups lower than individuals in the population as a whole
• Human-in-the-loop approach captures some of the benefits of machine learning without the fair lending and lack of transparency risks 
• Fully supports using reliable alternative data in the credit scoring