In 2023, traditional identity fraud cost banks, credit unions and financial institutions $23 billion, an increase of 13% from the year prior. With such staggering amounts, it’s crucial for businesses to consider Fraud Loss Insurance. New account fraud and account takeover fraud accounted for nearly $18 billion in losses. And this number is on the rise. The unfortunate truth is that fraud is normal, and as digital banking continues to grow, so too will the number of attempts to defraud customers and financial institutions, perhaps more so with impending financial deregulation.
Though many banks, credit unions and financial institutions have programs and technology to help mitigate fraud risk, fraud evolves continuously. The data highlights how addressing identity fraud in line of business operational silos results in increased costs and customer friction, with the inevitable fraud losses being held on a business’s own balance-sheet, hedged by millions of dollars in self-insurance treasury capital reserves.
The best-known example of a self-insurance treasury is the FDIC, the deposit insurance company managed by the Fed and funded by all the banks holding deposit accounts.
Following the 2008 financial crisis, banks agreed to comply with the Basel III accord, which requires them to maintain capital reserves based on a risk-weighted ratio. As a result, most top banks routinely hold billions of dollars in reserves.
That is set to change with the arrival of fraud loss insurance AI, a new solution in the marketplace. This innovation allows banks, credit unions and financial institutions to enhance their in-house fraud risk management programs by shifting fraud loss liability off their balance sheets. As part of a more comprehensive strategy, it offers a more capital-efficient approach to keeping fraud at bay.
Managing fraud risk, particularly identity fraud, is not a new challenge for financial institutions. However, its scale has grown significantly, becoming increasingly complex and resource-intensive. Traditional identity fraud risk prevention relies on a combination of customer identity verification technology at account opening to confirm whether an applicant is a real human being, followed by account security software monitoring and labor-intensive manual reviews. These processes are all prone to errors, leading to friction and inefficiencies.
The most commonly used strategy to stop fraud is to squelch growth; the fewer new customers or transactions processed and accepted, the lower the overall fraud losses. In fact, most institutions operate on less than 40% net acceptance rate of new customers, turning away a lot of potentially good customers acquired with costly marketing spend, just to keep fraud losses at bay.
To counteract some of these challenges, many financial institutions have adopted stricter criteria for accepting new customers, shifting the burden to the customer, who may be required to undergo lengthy reapplication processes each time they seek a new product, even with a bank where they already hold accounts. It reduces growth and revenues, and it also means that banks carry the cost of fraud on their books.
Understanding Fraud Loss Insurance
Financial institutions have long managed risks through a combination of reducing exposure themselves and transferring risks through insurance. However, fraud risk is unique in that it has traditionally been a non-insurable problem.
After all, each business decides how much fraud loss is acceptable for the various products they offer, the specific customers they target, their choice of fraud prevention tools, the orchestration waterfall logic they implement and the coverage and accuracy of each tool in their toolbox. With varying levels of risk assurance across products, there has been no easy or consistent way to manage fraud losses between businesses—or even across different lines of business within the same institution.
That’s where machine learning and artificial intelligence play a critical role, enabling fraud loss insurers to price and underwrite a business’ fraud loss exposure while assessing expected losses in real time. As financial institutions accept or reject customers, whether for new accounts or transactions, these advanced technologies help refine risk evaluation.
Fraud loss insurance, a growing category within property and casualty insurance, is supported by partnerships with leading AM Best A+ rated insurers. With a streamlined digital claims process, policyholders typically receive payouts in under 30 days, helping insured institutions improve margins, cash flow and capital ratios.
Adding Fraud Loss Insurance To Your Risk Playbook
Adding fraud loss insurance is easy for banks and financial institutions looking to shore up their risk playbook this year. It starts with a quick coverage needs assessment by a fraud loss provider or through the institution’s own insurance broker to get a preliminary non-binding quote for the amount of fraud losses that will be shifted off the institution’s books, factoring in desired growth.
Organizations should consider factors such as their aggregate loss and per-incident limits relative to their current fraud losses, integration requirements with existing systems and whether their fraud profile aligns with available insurance products.
Once approved, the provider will underwrite the fraud loss insurance policy, using historical data for AI analysis. If everything looks good, the financial institution will receive an insurance policy and a service agreement, along with instructions for setting up the technology.
How Does the Future Look?
As identity fraud continues to be a risk that banks and financial institutions manage daily, it’s paramount that these organizations look for solutions rooted in advanced technologies and adaptive strategies. AI-driven fraud detection and predictive analytics are transforming how banks and financial institutions identify and mitigate risks. These tools can help banks more proactively protect themselves and their customers at the point of customer acquisition and help organizations stay ahead of ever-changing regulations.
Looking ahead, the synergy between fraud loss management and insurance will be enhanced. Organizations that implement a layered defense strategy—combining advanced detection tools, predictive analytics and comprehensive fraud loss insurance—will be better equipped to navigate the upcoming risk environment with improved capital rations, margins and top-line growth.
