A recent Government Accountability Office (GAO) report highlights the dual nature of artificial intelligence (AI) in financial services. While AI enhances operations through improved customer service and fraud detection, it also introduces risks that could threaten data privacy and perpetuate bias in lending. The report emphasizes the need for new risk management protocols from regulatory bodies to address these challenges. Specifically, poor data quality and complex AI models can lead to discriminatory practices and the dissemination of misleading information, putting vulnerable consumers at risk.
According to one consumer advocate, AI could steer borrowers, including those in protected classes, toward inferior or costlier credit products.
Bias in credit decisions is a risk inherent in lending, and AI models can perpetuate or increase this risk, leading to credit denials or higher-priced credit for borrowers.
The function and outputs of AI can be negatively affected by data quality issues, such as incomplete, erroneous, unsuitable, or outdated data.
Complex and dynamic AI models, poor-quality data, and reliance on third parties increase risks associated with AI in financial services.
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