How to Enhance Your Fraud Detection in Banking Transactions

Digital banking has completely revolutionized how we manage our transactions and accounts. However, with the ease and convenience of digital banking comes an increased risk of fraud attempts by scammers and cybercriminals. 

These fraudsters are taking advantage of the system, putting banks and customers at risk. 

It’s crucial that banks take immediate action to prevent such fraud attempts and safeguard their customers’ financial assets. Banks can leverage innovative technology to optimize their prevention strategies and ensure their customers’ information remains secure. 

We’ll explain what fraud detection in banking transactions consists of and how banks can take advantage of technology to protect their customers.

The basics of banking fraud detection

Putting a stop to financial fraud and keeping unauthorized transactions at bay comes down to getting a good grasp on the different types of scams that are most likely to affect a bank and its customers.

Some of the most common fraud schemes impacting financial institutions are:

  • Check and credit card fraud: Criminals steal physical payment instruments or relevant information from them to replicate and initiate new transactions. For example, check fraud is rising despite decreasing physical check usage.
  • Identity theft: Similarly, attackers can use other personal information to assume an account holder’s identity and take over their banking accounts.
  • New account fraud: Attackers can create false accounts in an account holder’s name or take over dormant ones to make fraudulent transactions.

A troubling trend in banking fraud is how cybercriminals leverage new technologies to defraud financial institutions and account holders. A landmark New York Times (NYT) report illustrates how fraud has flourished on Zelle since its inception in 2017. The ease and convenience for end users also facilitate high-volume (and high success rate) fraud schemes by organized crime and other attackers.

Strategies for enhancing fraud detection

While NYT also noted banks’ reluctance to take responsibility for these schemes, the real takeaway is the need for innovation in the face of emerging attack vectors. 

To that effect, some of the most effective strategies related to fraud detection in banking transactions include:

  • Identity and access management (IAM): Implementing access controls, such as multi-factor authentication (MFA), helps to secure user accounts.
  • Digital identity verification: Using innovative software to capture, verify, and manage identity information helps to ensure users are who they say they are.
  • Real-time fraud monitoring: Risk assessment in banking needs to include automated scanning to detect fraudulent activity as—or before—it happens.
  • Leveraging threat intelligence: Financial institutions should collaborate and share risk information to strengthen security across the banking industry.

Additionally, not all fraud comes from outside attackers. Internal fraud enacted by staff or third-party contractors is an insidious and hard-to-detect threat for banks.

Consider the account fraud uncovered at Wells Fargo in 2016 (and afterward). The initial and follow-up schemes were led by internal staff at the bank, and further legal pursuits have focused on its failure to properly address these internal fraud threats or address the aftermath for customers. This all points to the importance of staff training and cultivating a culture of vigilance alongside robust protections.

When it comes to fraud prevention, Microblink is a great addition to any existing fraud process. We can serve as a “step-up” solution by introducing additional layers of security based on early signals of potential fraud. For example, if a user attempts to access their account from a new device, our system will signal the need for additional identity verification, such as an ID scan.

We also initiate secure interactions with an ID scan, using the results to determine if further checks, such as biometric or live detection checks, are necessary. If the ID scan already indicates strong characteristics of fraud, this can help prevent unnecessary costs and time spent on additional checks.

This also illustrates why banks need to prioritize innovative technologies.

Leveraging ML and AI for anomaly detection

Machine learning (ML) and artificial intelligence (AI) empower a fraud detection system with robust, near-immediate, and accurate processing across all relevant account data. AI in fraud detection is increasingly necessary, as inaccuracy has become costly at scale.

Per JP Morgan’s report on companies abandoning fraud prevention tools, a big push behind this mistake was the skyrocketing cost of false positives. When legitimate transactions are flagged as fraudulent, the ensuing procedures account for up to 19% of fraud’s total costs—actual fraud, on the other hand, accounts for 7%.

However, companies that saw this as a reason to de-prioritize fraud detection drew the wrong conclusion. The real upside is that accuracy is absolutely essential.

AI and ML tools supercharge accuracy across transaction anomaly detection.

Machine learning in banking security also further optimizes all the strategies noted above. AI tools allow for seamless Integration of biometric verification, enhancing IAM and ID verification with options for retinal, fingerprint, and other scans.

Building a robust anti-fraud strategy

Preventing fraud in financial institutions starts with identity fraud detection in banking. But it doesn’t end there. 

Banks also need to be vigilant and address fraud indicators when they appear. Accounts and/or transactions need to be controlled and possibly frozen until the bank can be certain they’re legitimate.

The building blocks of a comprehensive anti-fraud strategy in banking include:

  • Tools for monitoring, detecting, analyzing, and acting on fraud risks
  • Robust training for customers and employees to instill awareness
  • Advanced anti-fraud technology and tactics to outpace cybercriminals
  • Mitigation strategies for addressing fraud attacks when they surface
  • Compliance with anti-money laundering (AML) and related regulations

ID verification and document management go a long way toward making sure users are who they say they are and initiate their transactions in good faith.

Microblink’s ID scanning software, BlinkID, enables automatic capture, and extraction of data that help banks detect fraud—and prevent it. 

Check out our case studies to learn how our software detects and prevents banking fraud while optimizing user experience and engagement.

Or, if you’d like to test out our BlinkID software for your bank, try our demo today.

May 13, 2024

Discover Our Solutions

Exploring our solutions is just a click away. Try our products or have a chat with one of our experts to delve deeper into what we offer.