How modern tech is changing the way banks detect fraud

Customer protection is one of the top priorities for financial institutions. While digital technology has created new types of bank fraud—such as phishing and cyberattacks—it also created new protections. Biometrics and recent developments in machine learning will continue to improve themselves and may even predict fraud before it happens. 

Types of banking fraud

Bank fraud refers to illegally stealing money or assets from a financial institution or its customers. Fraudsters have always accomplished this by using stolen customer information to make fraudulent purchases or transfers. 

According to the 2024 Global Financial Crime Report (by Nasdaq and Oliver Wyman, a financial consulting firm), fraud cost individuals and companies nearly $500 billion globally in 2023. Here are the main types of fraud affecting customers today:

• Identity theft: The thief uses personal information to impersonate a target, allowing them to open bank accounts or credit cards in the target’s name.
• Card skimming: The thief uses a scanner attached to a checkout terminal or ATM to steal credit card numbers.
• Check fraud: The thief uses counterfeit checks or real checks connected to an empty account to make payments that will knowingly bounce.
• Phishing: The target clicks through a fake email or message that looks legitimate but fools the target into entering personal information.
• Cyberattacks: The thief compromises a banking institution’s website or digital records, stealing account and personal information from their customers.

How did banks detect fraud before computers?

Before digital methods were available, banks relied on manual verification to detect fraud, meaning anomalies in account activity were pursued and verified by hand. This meant banks had to flag and preserve physical files for accounts they thought might engage in suspicious activity, or receive a fraud tip. Often, fraud was only apparent after it had already occurred. 

How digital technology changed fraud detection

While the information era introduced new types of fraud, it greatly improved the banking security required to defend against it:

• Online banking allows customers to manage their accounts remotely. 
• Most online transactions and communications between customers and banks are now encrypted, meaning no one without a decryption key can see what’s being exchanged.
• Firewalls protect personal and banking networks from unauthorized access.
• As the number of customer devices have increased, two-factor authentication allows for a more secure sign-in process.
• Predictive fraud detection systems allow banks to prevent fraud before it occurs, making it easier to adapt to the shifting tactics of cybercriminals.
• After a few high-profile data breaches in the 1990s, the United States government implemented stricter banking compliance requirements around customer financial data.

Current trends in fraud detection tech

AI and machine learning

Artificial intelligence (AI) can progressively analyze data patterns (from either all customers or a specific customer) to find and predict anomalies before they happen. Because these technologies excel at recognizing patterns in huge datasets, they reduce overhead costs associated with manual review and free bank employees to focus on other tasks.

The use of machine learning (ML) algorithms means banking fraud AI systems can improve themselves over time, increasing accuracy and making automated fraud detection even more efficient, especially as new fraud tactics emerge.

Biometrics

Biometric authentication uses the body’s unique signatures to verify customer identity—you may have used a fingerprint, facial recognition, or voice identification as a part of multi-factor authentication, or even in place of sign-in credentials. Because your biometric signatures are unique to you and highly complex, biometrics are much more difficult to fabricate than sign-in credentials or identification numbers.

Biometrics such as a fingerprint prompt provide convenient, continuous identity verification, which is useful for preventing fraud because your bank can periodically verify your identity during a session.

The future of financial fraud

Any new technology can be expensive and difficult to integrate with existing systems. In the financial sector, customer privacy and compliance with new regulations are also important to consider when upgrading. Fortunately, advancements in AI and ML will continue to offer more accurate and efficient fraud detection and prediction as they continue to improve.

Because of this, the future of banking fraud will probably rely less on exploiting technology and more on exploiting human vulnerability. To protect your accounts, familiarize yourself with common social engineering scams, such as the pig butchering scam.