Artificial intelligence (AI) is making rapid inroads into many aspects of our financial lives. Algorithms are being deployed to identify fraud, make trading decisions, recommend banking products, and evaluate loan applications. This is helping to reduce the costs of financial products and improve th…
Through a case study of mortgage applications, this article shows how bias might be introduced to AI systems by either bias within historical data, and/or inherent biases of AI programmers and employers. This article gives reasons why this presents a risk to businesses in terms of missing out on customers (refusing credit to creditworthy people) and legal or regulatory compliance risk. Therefore it argues that financial firms must ensure bias considerations are core to their AI development process.