Risk assessment is crucial for any enterprise that extends credit to customers. Commonly known as credit scoring, the process helps lenders make confident, informed decisions on whether prospective customers will honor their debt. Credit scoring is typically associated with the banking and financial service sectors, but is required across a wide array of businesses, including telecoms, retail, and insurance. In most cases, credit scoring isn’t just a business tool, it’s a regulatory necessity. And credit scoring is a vast industry. In the U.S. alone, recent consumer debt valuations hover over $14 trillion.
Credit scoring is a complex task that involves wrangling a diverse range and large volume of data. Based on predictive modeling, the use of artificial intelligence (AI) and machine learning (ML) is well established and widespread. And because of the data burden, credit risk firms were some of the earliest organizations to adopt the technology. As such, the credit risk sector can claim to be a pioneer in AI and ML utilization.