Balancing convenience and security in financial services
Instantaneously completed financial transactions are quickly becoming an expectation across all financial services industries. Customers want the convenience of a frictionless experience, with the tremendous popularity of newer instant payment systems like Venmo and Zelle driving this expectation.
Customers now expect these platforms to manage links with traditional banks without hassle. This expectation of low friction in our everyday transactions — in retail, payment for services, or accessing digital platforms — has placed increasing pressure on traditional banks to develop less complicated verification and monitoring systems for quicker onboarding. And those digital services that enter into agreements with banks must take on aspects of the banks’ regulatory compliance rules — and many are falling short.
Simultaneously, traditional banks are struggling with slow onboarding as they race to meet consumers’ demand for fast transactions. The Bank Secrecy Act of 1970 supports the security and stability of the U.S. banking system, helping customers trust that their banks remain vigilant and free from major legal risks and conflicts of interest. As banking becomes more digital and global, compliance analysts and staff have taken on broader roles, aided by next-generation digital tools.
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| Context for the growing fraud problem |
| The same scams, but upgraded |
| How can financial institutions fight back? |
| Going forward on verification |
Context for the growing fraud problem
Fraudsters are rapidly expanding their capabilities with the help of AI-enabled tools and large language models. As a result, financial crime such as fraud and money laundering have surged in recent years, while customers, businesses, and financial institutions are left scrambling for ways to protect themselves and their customers.
In 2023, many fast-payment industry leaders recognized their vulnerabilities, according to Alloy’s Annual State of Compliance Benchmark Report. 90% of financial services struggled with regulatory compliance without automated tools, and over 60% had paid fines exceeding $250,000 in the previous year. Now, most of these digital financial services firms are looking for AI-driven solutions going forward.
Zelle is eliminating the ability of consumers to use their service independently of a consumer bank account at an affiliated institution. Most Zelle customers already did have bank accounts, but this stronger directive came on the heels of its owners — JPMorgan Chase, Bank of America, and Wells Fargo — being sued in December 2024 by the Consumer Financial Protection Bureau (CFPB) for failing to adequately protect Zelle customers from financial fraud and scams in its rush to release its platform in order to compete against other fast-payment platforms.
Although the CFPB’s lawsuit was dropped, the large bank sector continues to incubate its own solutions to better tap into the demand for fast-payment services. Another incentive for innovation and synergy in this area is the evolving nature of contemporary fraud itself.
The same scams, but upgraded
Modern financial fraud perpetrators rely on social engineering — a set of timeless con-artistry techniques geared to gain trust — but in the digital age, they also launch fraud attempts at speeds and volumes rarely seen before. At that pace, only a few attempts are needed to be successful for the scheme to pay off quickly and with fewer traces.
The traditional goal of gathering victims’ information through trust is ultimately to commit identity fraud on banks, but even this has changed. Normally, a fraudster assembles enough information about another person or business to impersonate them long enough to open an account and move money through it. In the past, fraudsters obtained this information by stealing it (for example, by rifling through someone’s discarded documents) or by tricking their victims into revealing it.
Now, however, more than 80% of new account fraud comes from the use of synthetic identities — patchwork entities made up of information from various individuals. Consumer-facing AI tools also make these financial fraud attempts, like phishing, spoofing, and document fabrication, more convincing and realistic. And illicit actors who engage in financial fraud at this scale often obtain information from large data breaches or on the dark web. Even the most vigilant consumer has little control over the latter.
How can financial institutions fight back?
Financial institutions must take comprehensive responsibility for the problem, whether transactions are fast or slow. A good balance between risk reduction and due diligence, on the one hand, and frictionless on-boarding with unobtrusive, ongoing account monitoring, on the other, may be the best strategy. However, such processes increasingly require a reliable system of transaction triage and sorting.
Banks increasingly use comprehensive analytic tools to verify identities and comply with know-your-customer (KYC) and anti-money laundering (AML) requirements, moving away from manual customer reviews. These tools sort transactions into high- and low-risk categories, allowing staff to reserve manual review for a much smaller number of cases. Even then, banks can streamline the process with a single-dashboard search across public and private records, consumer data and adverse media.
Smaller retail banks and credit unions face different challenges from larger banks in addressing digital fraud. Although they must meet the same KYC and AML compliance requirements, their legacy practices, customer community, and threat profiles differ significantly from their large competitors. Smaller banks have less capacity to absorb fraud losses than bigger banks, and credit unions balance a community mission with financial concerns.
For example, in recent years, California’s Ventura County Credit Union (VCCU) has faced a significant increase in financial crime through synthetic identity fraud and money mule activities, in which new or existing consumer or small business accounts are used in coordination to launder money in smaller rather than more suspicious larger amounts. VCCU was already doing risk evaluation and compliance work, with a conventional focus on examining individual accounts; yet by adopting newer analytic tools, it was able to look at activity across accounts and better detect patterns.
Going forward on verification
Many banks use machine learning as a force multiplier to enhance and extend the work of their analysts and compliance officers. The financial technology sector shows that today’s solutions may not address tomorrow’s problems, as digital-age financial fraud evolves rapidly. Banks need fast-payment systems and adaptable tools to keep up.
Institutions that leverage flexible tools to respond quickly to changing customer needs—and strengthen their defenses against fraud—will be best positioned for success. Stay ahead of these challenges by exploring opportunities through our recent e-book The future of KYC and AML in a Fintech world.
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