How AI fraud prevention gives credit unions a competitive edge

The $1.4 trillion small-business lending market is attracting credit unions faster than ever, but growth is exposing lenders to new fraud risks. AI-driven schemes such as synthetic identity fraud and loan stacking threaten to erode credit unions' profits and even push them out of the small-business market altogether. 

To protect themselves against the rise of emerging fraud technology, lenders can fight AI with AI. Modernizing their fraud prevention stack with AI-enabled tools is the best way for credit unions to fight back and gain a competitive edge.

In this guide, we’ll cover the risk landscape for credit unions, where most fraud tools fall short, and how credit unions can protect themselves with AI fraud prevention. 

The rising tide of credit union fraud

Fraud against credit unions is growing so fast that it threatens to outpace the portfolio growth they could gain in the small business market. According to a recent Experian report, the small business lending fraud situation is becoming dire:

• 65% of financial institutions reported increasing fraud in 2024.
• 46% of small business loan applications showed signs of first-party fraud. 
• AI-driven scams are projected to drive $40B in losses by 2027.
• 80% of fraud occurs on digital channels. 
• 64% of financial institutions plan to boost fraud investments. 

Most fraud is caught too late

The majority of lenders aren’t catching fraudsters in the act, but after the deed is done. According to a LexisNexis Risk Solutions study, only 27% of small business lending fraudsters were caught during or before origination. 

This front-end failure is largely due to one threat: synthetic and stolen identities. Fraudsters use pieces of stolen and fake identity information to make synthetic personas that they use to apply for loans digitally. 

It’s estimated that synthetic identities account for over 80% of all new account fraud. If a lender can’t identify synthetic identity fraud upfront, they’re highly likely to suffer financial losses before they know they’re being scammed.  

Why credit unions are vulnerable

Most credit unions are not properly equipped to protect themselves against the rising threats of modern fraud. There are three vulnerabilities in particular that make credit unions an easy target:

• Manual reviews: Many credit unions rely on time-consuming manual reviews for new loan applications. These reviews are expensive, prone to human error, and reviewers are unable to catch the fake and stolen information in synthetic identities at scale.  

• Siloed data: Limited data access and fragmented systems miss early red flags and patterns that might indicate fraud. 

• Inadequate tools: Many credit unions rely on consumer fraud tools that aren’t built for the complexities of SMB lending, such as Know Your Business (KYB) processes, multi-entity business structures, and mixed data sources. 

To grow their SMB portfolios without putting themselves at risk, credit unions can shift beyond these vulnerable practices and adopt modern, AI-driven loan fraud detection systems. If credit unions don’t automate and scale fraud prevention, their growth will be stymied by the fraudsters who outpace them. 

AI shifts fraud prevention from reactive to real-time

Credit unions that adopt AI fraud detection are able to catch more fraudsters upfront, before fraud is committed. Instead of reacting to compromised accounts and accepting write-offs on unpaid loans, they’re catching more fraudsters in the application phase. 

Here’s how AI fraud detection is helping credit unions catch more fraudsters in the act: 

• Speed and precision: AI models provide real-time risk scores to new applicants by analyzing documents and IDs, and cross-referencing them against vast data sets in seconds. Manual reviews cannot handle the same level of precise risk management at scale. 

• Continuous improvement: Machine learning fraud models learn from each new data point. They are constantly evolving themselves as fraudsters test new methods against them, and can catch more subtle patterns from emerging fraud schemes before they turn into losses. 

• AI-driven orchestration: AI models can quickly decide which loans should move forward and which should be flagged for further review. This automated orchestration enables good borrowers to get loans funded faster while stopping fraudsters from moving further through the process. The end result is a growing portfolio of healthy loans and fewer fraud losses due to late detection. 

Inside Lynx: the fraud prevention platform for SMB lending

The best solutions to fraud threats come from those who’ve faced them. With over 20 years of proprietary data and real-world lending experience, Rapid Finance has firsthand knowledge of the fraud tactics that face small business lending. 

Lynx is a fraud prevention platform built for lenders, by lenders. It provides real-time risk assessments that enable credit unions to process applications and underwrite loans with greater speed, confidence, and accuracy. 

Here’s how Lynx protects credit unions in four quick steps for each loan application:

1. Instant intake: For incoming applications, AI tools instantly scan supporting documents, standardize the data, and prepare it for analysis.
2. Cross-validation: Lynx validates application data against the lender's data, network data, and 3rd party KYB/KYC integrations.
3. AI fraud detection: AI algorithms immediately spot any anomalies or fraud patterns across the integrated data in real time.
4. Results in seconds: Lastly, the AI fraud algorithms assign a score: Pass, Fail, or Review, along with insights that explain why. 

Running new loan applications through the Lynx fraud prevention system helps you scale your SMB loan portfolio without scaling fraud losses with it. 

AI fraud prevention is the competitive advantage credit unions need

Credit unions that don’t use AI fraud prevention tools like Lynx will not be able to grow their portfolios without exposing themselves to massive risks. In fact, it’s possible that fraud losses will outpace any profits they might make from expanding their portfolio to begin with. 

On the other hand, credit unions that are early adopters of AI fraud prevention will see a distinct competitive advantage that enables them to scale without increased risk. Below is a before-and-after picture of what that change looks like. 

Protect your portfolio. Grow with Confidence.

Implementing Lynx is a streamlined process that gets you from concept to protection in a few easy steps:

1. Connect via API: Easily integrate Lynx with your existing systems through a single, modern API connection.
2. Upload historical data: Upload your historical lending data for calibration, allowing the AI to learn your specific applicant profile and risk indicators immediately.
3. Customize rules and indicators: Work with Rapid Finance experts to fine-tune Lynx with your unique rules and workflows.

Book a Lynx Demo today to see how AI fraud prevention can help scale your portfolio with confidence.