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Changing The Economics Of Fraud With Fraud Loss Insurance

Mar 24, 2025 - forbes.com
In 2023, identity fraud cost financial institutions $23 billion, with new account and account takeover fraud accounting for $18 billion of these losses. As digital banking grows, fraud attempts are expected to increase, exacerbated by potential financial deregulation. Traditional fraud prevention methods, such as identity verification and account security, are prone to errors and inefficiencies, often resulting in high costs and customer friction. To mitigate these challenges, many institutions have adopted stricter customer acceptance criteria, which can stifle growth and revenue. Fraud loss insurance, supported by AI and machine learning, offers a new solution by allowing financial institutions to transfer fraud loss liability off their balance sheets, improving capital efficiency and reducing the burden of fraud management.

Fraud loss insurance, a growing category within property and casualty insurance, enables financial institutions to manage fraud risk more effectively by using AI to assess and underwrite fraud loss exposure in real time. This insurance is backed by partnerships with leading insurers and offers a streamlined claims process, typically providing payouts within 30 days. By incorporating fraud loss insurance into their risk management strategies, banks can enhance their defenses against fraud, improve margins, and support growth. The future of fraud loss management will likely involve a combination of advanced detection tools, predictive analytics, and comprehensive insurance, allowing institutions to better navigate the evolving risk landscape.

Key takeaways:

  • Fraud loss insurance AI is a new solution that allows financial institutions to shift fraud loss liability off their balance sheets, enhancing their fraud risk management programs.
  • Traditional identity fraud cost financial institutions $23 billion in 2023, with new account fraud and account takeover fraud accounting for nearly $18 billion of these losses.
  • Fraud loss insurance, supported by machine learning and AI, enables insurers to price and underwrite a business's fraud loss exposure in real time, offering a more efficient way to manage fraud risks.
  • Implementing a layered defense strategy, including advanced detection tools, predictive analytics, and comprehensive fraud loss insurance, can help financial institutions better navigate the risk environment and improve capital ratios and margins.
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