AI in banking presents both risks and rewards, with success hinging on data quality. Risks include poor data leading to $406 million in average annual revenue losses, AI hallucinations with error rates up to 27%, bias in 85% of projects, and rising privacy threats where over half of institutions lost $5–25 million to AI-driven attacks. Mistrust also looms, as only 26% would embrace AI if poorly managed. Yet rewards are substantial: AI could unlock $1 trillion in annual banking value, improve efficiency by cutting $300 billion in costs, boost credit approvals by up to 30% without higher losses, and deliver fraud detection and personalization at scale.

Join for free to read