16-04-2025
How Better Data Can Reduce Fraud For Financial Service Providers
Gus Tomlinson, Managing Director – Identity Fraud at GBG, an industry leader in global identity and fraud intelligence.
Access to financial services has never been more widely available.
Whether people are connected to a traditional financial institution or leverage emerging financial technology (fintech) services, they now have unprecedented opportunities to manage, invest and grow their money through digital platforms and innovative financial solutions.
This is excellent news for people as access to quality financial services is associated with increased economic mobility, improved financial literacy, and building long-term wealth and financial security.
It also presents a unique problem: fraud.
The anonymity of the internet, the complexity of digital financial systems, and the rapid pace of technological innovation make fraud a pervasive, billion-dollar problem for financial institutions and their customers. The UK's Financial Ombudsman Services predicted earlier this year that fraud and scams would account for 35% of their banking and loan cases in the next financial year.
Unsurprisingly, business leaders are clamoring for better identity verification solutions that help them connect safely with genuine identities, and consumers want solutions that enable them to live safe and rewarding digital lives.
However, this can create friction as brands look to balance customer experience with security. Our company's latest Global Fraud Report notes that while businesses believe quick and easy onboarding is important to customers, almost all (97%) are worried about the added friction of robust fraud checks impacting onboarding for good customers.
Meanwhile, many financial institutions still rely on traditional identity verification methods, which rely exclusively on public data and often fall short, especially when addressing thin-file customers, new-to-country populations or synthetic identities.
In many ways, identity verification is a data equation. The better data you have, the more effectively you can catch fraudsters before they do real damage. It can be compared to a jigsaw puzzle, with each piece of data building out the picture until it becomes clear.
Public identity data can accomplish a lot, but it only gets you so far. However, it struggles with thin-file customers, such as those new to credit systems or individuals who recently relocated.
It also limits financial institutions' ability to detect and defend against synthetic identity fraud (SIF).
SIF, which occurs when fraudsters create fake identities by combining real and fabricated personal information, has become especially problematic as frontier generative artificial intelligence (GenAI) models make it easier for bad actors to create sophisticated, believable false identities with realistic documentation and backstories.
To address these challenges, financial services providers can turn to credit header data, which provides more granular information (like precise dates of birth) and the most current address information, as well as regional-specific data such as matches of social security numbers (SSN) in the U.S.
Public data provides broad coverage and is critical for high-level matches, while credit header data provides depth with granular information. Layered together, this helps to create a more robust identity verification framework that enables financial institutions to detect fraud most effectively, improve pass rates and elevate the customer experience.
To go one step further, businesses can leverage cross-sector and industry identity intelligence to combat fraud by identifying serial fraudsters targeting multiple businesses.
This type of collaboration is becoming increasingly critical. After all, criminals don't limit their attacks to one business, industry or country, and the availability of AI has increased both the ease and scale of fraud attacks.
The data shows when it comes to tackling fraud, the solution doesn't just sit with banks and financial services—social media and technology platforms need to be involved as well. Analysis from the UK's Payment System Regulator found that over half of authorised push payment (APP) scams involve Meta platforms.
Better identity verification offers financial institutions several tangible advantages:
• Increase Revenue Potential: Higher match and pass rates mean fewer missed opportunities to onboard genuine and good customers. It's a win-win: Better matches ensure financial institutions can capitalise on legitimate customers who might otherwise be rejected by public data alone, and good people get access to the products and services they care about.
• Reduced Costs And Operational Efficiency: Fraud is expensive, and an ounce of prevention is worth a pound of cure. Better fraud detection lowers overall costs and keeps financial service providers focused on their customers, not bad actors.
• Enhanced Customer Experience: Reducing friction in the onboarding process improves customer satisfaction. Matching submitted data seamlessly against additional sources delivers higher approval rates without compromising user experience. Simply put, better data enhances fraud detection capabilities and streamlines the verification process, improving customer experiences and increasing revenue opportunities.
• Verified Fraud Deterrence: Data sources are critical to driving successful identity verification, reducing fraud and increasing revenue.
By tapping into diverse data sources, financial institutions can build robust identity verification frameworks that unlock business potential worldwide, no matter what bad actors are up to. The benefits accrue to companies and their customers, making it a win-win investment for financial service providers in 2025.
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