Banks and fintechs are now digital-first by design, making them prime targets for fraud. Today’s fraudsters are more than just persistent. They’re armed with advanced GenAI tools, pushing past traditional tactics.
But how exactly do today’s technologies impact fraud prevention and detection strategies in banking and fintech? And what changes are coming in these sectors?
Explore key findings from Regula’s recent study, including insights from companies in the USA, UAE, Germany, and Singapore.
What IDV threats do banking and fintech companies face most?
In finance-related industries, identity verification (IDV) typically involves document and biometric checks, along with additional KYC questionnaires.
Take Paysera, for instance. To open an account, new users must confirm their phone number and email, complete KYC and PEP checks (like proof of income or political association), and submit both a government-issued ID and a selfie.
According to respondents’ feedback in Regula’s study, the biometric verification stage is seen as the most vulnerable step in the entire IDV process. It’s where fraudsters attack most often, targeting both banks and fintechs. The tactics include impersonation using photos, videos, or other media; using fake or stolen biometric data; and manipulating voice or video.
| Type of attack | Banking | Fintech |
|---|---|---|
| Identity spoofing | 34% | 40% |
| Biometric fraud | 35% | 31% |
| Deepfake fraud | 33% | 39% |
Another widespread tactic is the use of synthetic identities, blending fake and real personal data to bypass verification. This type of fraud was reported by 30% of banks and 28% of fintech companies.
Document fraud is also common. Over a quarter of banks (26%) and nearly a third of fintechs (32%) faced cases where users presented counterfeit or altered documents.
Finally, social engineering attacks—like phishing and pretexting—target legitimate, verified clients. These types of attacks were reported by 27% of banks and 30% of fintechs.
Key takeaway:
Most biometric-related attacks today are powered by AI-generated media. That’s not surprising, since these tools are increasingly accessible and capable of producing convincing fake images or videos.
Additionally, these attacks often happen at the onboarding stage, when users are first identified. That makes onboarding a central focus among current fraud prevention trends.
The tricky part is that customers expect onboarding to be fast and seamless. Striking the right balance between user experience and security still remains one of the top priorities for both banks and fintechs.
How banking and fintech businesses fight fraud
The constant wave of fraud attempts has pushed companies in the industry to take proactive steps. Many already use a wide mix of tools to detect and prevent attacks.
Real vs. ideal IDV setups
Currently, identity verification in banking is most commonly based on:
Multi-factor authentication (MFA), including two-factor authentication, OTPs (one-time passwords), security keys, and authenticator apps (28%).
Biometric verification and liveness checks (both used by 24%).
Dark web monitoring (23%), to track stolen credentials or biometrics and prevent incidents like account takeovers.
Dive deeper: Biometrics in banking is one of the traditional approaches to identity verification. Check out this free guide based on Regula’s webinar, featuring insights from UBS’s experience.
Still, about 21% of banks say they want to adopt biometrics and MFA—highlighting a gap between current capabilities and ideal setups. Notably, nearly 24% of respondents want to add manual fraud checks by trained specialists for critical situations or where required by regulation.
Among fintechs, the top methods in use are:
Database and watch list checks (AML, PEP, etc.)—24%.
Liveness detection—both also 24%.
MFA—23%.
Similar to banking, many fintechs still see gaps: 31% say MFA is part of their ideal setup, and 26% would like to implement biometric verification. Also, 24% aim to adopt dynamic threat prevention, including real-time fraud alerts and flexible security policies.
Key takeaway:
The diversity and fragmentation of identity verification in banking and fintech likely reflect the variety of KYC and AML regulations worldwide.
For instance, in the UAE, banks may use UAE Pass, a national digital ID, for customer identification. In Türkiye, in-person video calls are also an accepted method. In Egypt, as of 2025, the Central Bank is preparing rules for remote verification for certain transactions, such as opening new accounts, so most of these operations are still done offline.
Another reason for this diversity is risk appetite. Some institutions take a conservative approach, relying on manual checks or in-person verification to minimize compliance risks. Others are more open to innovation, testing automated IDV and AI-powered fraud detection to streamline onboarding and improve customer experience. The level of digital maturity, local regulatory flexibility, and even customer trust in technology often determine how far a bank or fintech is willing to go to adopt remote verification methods.
Automation vs. human oversight
An interesting contrast emerges between banks and fintechs when it comes to automating IDV. According to Regula’s survey, 23% of banks tend to use human oversight for complex or high-risk cases, such as document authentication, while fintechs are more open to automated ID checks: 24% use them and 15% rely on expert reviews by humans.
| IDV method | Automated document verification | Human expert review |
|---|---|---|
| Banking | 18% | 23% |
| Fintech | 24% | 15% |
Looking at the overall level of automation, 46% of respondents report that up to 75% of banking identity verification processes are currently automated. Interestingly, 47% consider this level ideal, showing a preference for maintaining a balance between automation and manual checks.
On the other hand, fintechs demonstrate a stronger push toward automation. While 43% of respondents already automate up to half of their IDV tasks, 41% want to reach 75% automation.
Additionally, 39% of banks and 43% of fintechs agree that automated orchestration of IDV tools and workflows—such as the approach implemented in Regula IDV Platform—is the most effective way to handle complex scenarios and multiple verification methods.
See also: 12 ID verification trends for companies in 2026
How the role of IDV will change for banking and fintech
Many companies in this niche are already digitalized and open to adopting advanced technologies in line with current fraud prevention trends.
A smooth and consistent user experience is among the most important indicators for IDV effectiveness, cited by 40% of banks and 43% of fintechs.
Major fraud prevention KPIs
Companies in the banking sector track metrics like employee training effectiveness, regulatory compliance, cost of fraud, chargeback rate, and false negative rate. In the fintech identity verification approach, customer impact—the number of customers affected by fraud—ranks as a top concern (24%).
| Metric type | Fraud prevention KPIs | ||||
|---|---|---|---|---|---|
| Employee training effectiveness | Regulatory compliance | Cost of fraud | Chargeback rate | False negative rate | |
| Banking | 18% | 18% | 17% | 16% | 16% |
| Fintech | 24% | 14% | 20% | 24% | 19% |
Metrics like fraud trend detection speed, response time to alerts, and false positive rate are seen as lower priorities across the industry. Only 10-15% of respondents listed them among the key indicators.
Key takeaway:
Historically, finance-focused businesses have prioritized regulatory compliance when choosing IDV solutions. But the study also reveals a growing focus on team expertise and ongoing training, which now rank just as high or even higher.
Another rising priority is customer satisfaction, with the false negative rate (legitimate users being mistakenly blocked) serving as a crucial metric.
In an increasingly competitive market, banks and fintechs are starting to treat smooth and accurate IDV processes as a strategic advantage, not just a security requirement.
Fraud prevention in banking and fintech: Key challenges
To make real progress in fraud detection and prevention, finance-related companies must overcome several key challenges.
For banks, the top issues include lack of stakeholder support or low prioritization of fraud prevention (26%), talent shortage among IDV specialists (23%), and manual processes that slow down detection and response (22%).
Meanwhile, fintechs primarily struggle with budget constraints limiting investment in better tools (27%), inconsistent processes across departments (26%), and outdated IDV technologies (24%).
A shared concern across both sectors is staffing. A significant majority—76% of banks and 78% of fintechs—report needing more personnel to manage fraud risk effectively. Many existing teams are overwhelmed with the volume and complexity of tasks.
Key takeaway:
The biggest barriers to stronger IDV strategies are operational: staffing shortages, lack of alignment, and insufficient resources.
The talent gap in IDV adds another layer of complexity, especially as fraudsters advance their methods with GenAI-powered tactics.
Fortunately, there are signs of progress. Most companies surveyed already offer training on detecting deepfakes and synthetic identity fraud. Also, investment is picking up, with 38% of banks and 28% of fintechs expecting their IDV budgets to grow—ideally, by 21-50%—in the coming years. For comparison, over the past two years, IDV spending increased by 10-21%, as reported by 38% of banks and 26% of fintechs. These shifts also suggest a growing awareness that fraud prevention isn’t just a technical task but a strategic priority.
How the future looks through the eyes of IDV specialists
A strong majority—71% of banking respondents and 75% from fintech companies—say that fraud prevention is a priority for their organization. This underscores the growing importance of IDV as a core part of security strategies.
As the focus shifts inward toward operational challenges, professionals working in fraud detection and prevention are also rethinking what the future of IDV should look like in the next three to five years.
In banking:
30% of respondents perceive IDV as a fully automated, real-time process powered by adaptive machine learning (ML) and decentralized identity solutions.
26% expect a shift toward global, near-instant verification, with multi-platform support and seamless scalability.
23% foresee IDV systems combining ML, biometrics, liveness checks, and risk-based verification, adaptable to evolving threats and regulations to ensure compliance and protection.
In fintech:
30% of specialists expect IDV to become deeply integrated across business functions, including marketing, customer service, and personalization.
28% anticipate fully automated, real-time verification.
26% share the vision of multi-platform scalability and predictive risk analytics, aligning closely with perspectives from the banking sector.
Summary: Common trends across banking & fintech
| Trend | Impact level | Shared direction | |
|---|---|---|---|
| Banking | Fintech | ||
| AI-driven fraud (deepfakes, spoofing) | High | High | Both face growing biometric attack risks |
| Onboarding under attack | High | High | Onboarding is the core fraud battleground |
| Hybrid (human + automation) | Balanced | Automation-leaning | Hybrid orchestration is emerging |
| Fragmented tools → Orchestration | Yes | Yes | Unified IDV platforms are gaining traction |
| IDV as a strategic function | Rising | Rising | Focus is shifting from compliance to customer experience |
| Talent shortage | Severe | Severe | Shared challenge of human capital shortages |
| Budget increase (%) | 38% | 28% | IDV investment is a growing priority |
Key takeaway:
With staff shortages and rising workloads, IDV professionals are looking to reduce manual effort and automate routine tasks to boost both efficiency and accuracy.
Stakeholders are likely to support this move, as automated IDV systems offer operational savings and stronger fraud prevention.
To keep up, finance-related businesses should consider a long-term, balanced IDV strategy that combines automation, cross-functional integration, and scalability while maintaining compliance and customer trust.
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