The Impact of Alternative Data on Credit Risk Assessment

Abstract

Traditional credit scoring models rely on financial data such as income, employment history, and debt-to-income ratio. However, with the rise of big data, there is a growing interest in using alternative data sources to assess credit risk. This data can include social media activity, online shopping history, and utility bill payments. This paper will explore the potential benefits and challenges of using alternative data in credit risk assessment, and how it can be used to improve the accuracy and efficiency of lending decisions.