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How to stop fraud in its tracks with AI-driven document automation

17 May 2024
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Fraud is a universal challenge for lenders, as counterfeit documents in loan applications can lead to defaults and significant financial losses.

Traditional manual verification methods, while aimed at preventing these issues, are time-consuming, labor-intensive, and prone to unavoidable errors. These outdated techniques fall well short of identifying advanced fraud schemes.

As fraud tactics and technologies evolve rapidly, manual processes struggle to keep up. This gap makes it increasingly difficult for financial institutions to protect themselves from potential risk.

The challenges of manual document verification in fraud detection

Manual verification and fraud detection methods require extensive staffing and training, leading to unnecessary payroll expenses. Labor-intensive strategies strain resources while driving up operational costs, making them an inefficient solution for fraud detection.

Customers expect a swift review process from lenders, and the slow pace of manual processing can delay key loan decisions. No matter the hold-up, a lack of speed impacts the borrower experience and reduces a lender’s edge over the competition.

The time-intensive nature of manual review also makes it difficult for lenders to scale operations efficiently during peak demand periods without compromising on fraud detection or incurring additional costs. As application volumes surge, maintaining the same attention to detail becomes increasingly challenging, leading to even more potential mistakes.

Beyond the time and effort required, manual fraud detection also carries a heightened risk of human error or oversight. As fraudsters’ technologies advance, digital manipulations, subtle inconsistencies, or even forged documents can appear legitimate to the human eye. To keep up, lenders need to harness technology to catch subtle fraud signals and effectively manage risk.

how to address the 6 most common types of fraud in loan applications

Advantages of AI-driven document automation in detecting fraud

AI-driven fraud detection gives lenders the tools to identify and prevent this type of advanced fraud in the financial sector. With tools like Ocrolus Detect, lenders can identify patterns and anomalies typically imperceptible to human reviewers. By diving into a document’s digital ‘guts,’ advanced software can alert lenders to alterations or inconsistencies within documents, increasing the accuracy and reliability of fraud detection.

AI can also detect document tampering more quickly than humans, leveraging both advanced algorithms to flag signs of fraud to lending teams for more confident decision-making. This flexibility enables financial services providers to scale and adjust their offerings in real-time, catering to client needs without costly, timely manual intervention. With this added efficiency, lenders can manage risk while enabling their teams to focus on more strategic work and customer service.

Beacon Funding mitigates fraud risk and enhances decision-making

In one example, Beacon Funding Corporation, a premier resource for businesses seeking financing solutions for their equipment needs, expanded into new markets and encountered a growing need for more efficient bank statement verification processes. The diversity of companies applying for financing required a streamlined approach to handle the volume and complexity of the applications.

Before collaborating with Ocrolus, Beacon Funding’s team members dedicated over five weekly hours to manually verifying bank statements, they faced significant challenges in determining the authenticity of statements.

In search of a solution, Beacon Funding turned to Ocrolus for an AI-driven document automation solution, seamlessly integrating its API into its Credit Platform. This optimized Beacon Funding’s operations, verifying the authenticity of bank statements within 4 minutes and enabling sales and credit teams to handle deals more efficiently.

Within the first 4 months of using Ocrolus, Beacon Funding identified a half-dozen fraudulent applications that would have been overlooked in manual review, saving time and reducing risk in their operations.

Fora Financial streamlines processing while deterring bad actors

In another case, Fora Financial, which serves companies across all major industries and mainly focuses on difficult-to-fund applicants, relied on manual underwriting review. This often led to subpar data accuracy, delayed decision times, and application backlogs from a fixed workforce.

To address these challenges, Fora introduced Ocrolus’ Detect for automated fraud detection and mitigation at the start of the underwriting process. With the Detect Authenticity Score, Fora’s team has the benefit of a singular score, indicating the likelihood that a document is genuine, along with context on what was tampered with and the overall confidence in the fraud signal. 

With this simplified scoring process, Fora is able to target bank statement verification more effectively, reducing the cost and resources required for verification services, increasing conversions by eliminating unnecessary verification requirements, and lowering early credit losses. 

According to Jesse Goldman, Vice President, Credit Operations at Fora Financial, “By targeting our approach more effectively, we reduce bank statement verifications by over 50%, streamlining the process for legitimate users while deterring bad actors.”

While traditional manual processes are costly and inefficient and often struggle to keep pace with today’s increasingly sophisticated fraud tactics, AI-driven document automation reduces operational costs and manual labor associated with improving the speed and accuracy of fraud detection.

These tools enable financial services providers to leverage real-time data analysis, stay ahead of fraudulent activities, and manage higher application volumes without sacrificing quality or security.

Book a demo and see how Detect can transform your fraud detection and prevention approach.

Key takeaways:
  • AI-driven solutions significantly increase fraud detection’s efficiency, accuracy, and reliability by identifying patterns and anomalies that human reviewers miss.
  • Advanced document automation and fraud detection reduce the time and resources spent on manual verification, allowing lenders to handle various document formats simultaneously and streamline subsequent processing stages.
  • AI-driven systems enable financial services providers to scale and adjust their offerings in real time, mitigating fraud risk and enabling more confident lending decisions.