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Written by: Laura Fitzgerald

Head of Brand and Digital Experience

According to BAI Banking Outlook: 2024 Trends, banks’ top priorities in 2024 include growing deposits, acquiring new customers, and enhancing customers’ digital experience. BAI is a nonprofit organization in the United States that provides research, training, and thought leadership events for the financial services industry. 

However, one of the biggest challenges to improving the customer digital experience is the risk of fraud. Isio Nelson, BAI’s managing director of research, writes, “Fraudsters are directing various scams against banks and their customers.”

The report further explains that 6 in 10 Gen Zers said they would switch financial services organizations in favor of a bank that offered a better app and other digital capabilities. But it’s a delicate balance. With digital capabilities comes an increased risk for fraud. 

Here’s how we expect the landscape to change in the coming years. Keep reading to be well-informed and prepared for the potential risks and challenges.

The current state of banking fraud

The top kinds of fraud in financial institutions are account takeovers, new account fraud, and familiar fraud (i.e., repeat offenders), all of which require good technology to combat. In 2024, Deloitte predicts that the impact of generative AI, industry convergence, embedded finance, open data, money digitization, decarbonization, digital identity, and fraud will grow. 

Common types of bank fraud

According to the survey by BAI, phishing and check fraud remain the most common types of third-party fraud reported by customers of the institutions surveyed (73% and 72%, respectively). That’s followed by debit card fraud (69%), electronic banking fraud (52%), account takeover (47%), impersonation of official scams such as Social Security and other government programs (37%), malware (25%), provider scams (19%), charity scams (13%), and economic relief scams (13%).

[Chart taken from BAI Banking Strategies Executive Report 2024 Banking Outlook, Page 10]

Synthetic fraud is also on the rise. Fraudsters make up a name based on fictitious information to create enough of a backstory to develop accounts. There is also a rise in cryptocurrency scams.

Six anticipated security trends in banking fraud for 2024

Banks must instill the proper protocol and checks and balances to mitigate and prevent fraud. Here are six changes banks can anticipate as we move to an increasingly digital banking landscape.

1. Real-time payment rails 

Real-time payment rails refer to the infrastructure and systems that enable instantaneous fund transfers between bank accounts or financial institutions. These systems facilitate transactions that are processed and settled in real-time, providing near-instantaneous access to transferred funds. Due to their efficiency, speed, and convenience, real-time payment rails have become increasingly prevalent in the global financial landscape.

2. Tech to prevent deepfake-driven scams 

Deepfake-driven scams refer to fraudulent schemes in which deepfake technology creates convincing audio or video content to deceive individuals or organizations for malicious purposes. Deepfake technology utilizes artificial intelligence (AI) and machine learning algorithms to manipulate audio, images, or videos to make them appear authentic, often by superimposing one person’s likeness onto another’s. Good technology can help avoid such scams from infiltrating banking and allowing fraudsters to gain access to accounts.

3. Tech to spot AI-driven fraud-as-a-service

AI-driven Fraud-as-a-Service (FaaS) refers to the provision of fraud-related tools, resources, and expertise through cloud-based platforms or services powered by artificial intelligence (AI) and machine learning (ML) algorithms. In FaaS models, cybercriminals can access sophisticated fraud techniques, tools, and datasets on a subscription or pay-per-use basis. This enables them to orchestrate various fraudulent activities with minimal technical expertise. Technology, however, contains a fraud consortium to spot trends and prevent repeat offenders.

4. Technology that limits scam fatigue and distrust 

Scam fatigue refers to the weariness and diminished trust experienced by individuals or customers due to being repeatedly targeted or exposed to various scams or fraudulent activities. When individuals are bombarded with fraudulent emails, phone calls, or messages regularly, they may become desensitized to warning signs and less vigilant in identifying potential scams. This can lead to a loss of trust in institutions, businesses, or online platforms and a reluctance to engage in online transactions or share personal information.

5. Large language models 

Large language models (LLMs) can be exploited in various types of scams due to their ability to generate human-like text and responses. While these models are developed with safeguards and ethical guidelines, there are still concerns about their misuse in fraudulent activities.

6. Check fraud persistence 

Despite advancements in digital payment and detection technology, check fraud remains a significant concern in the banking and financial industry. Check fraud involves the unauthorized use, alteration, or creation of checks to steal funds or deceive individuals or businesses.

How technology is reshaping fraud prevention

Technology is crucial in reshaping banking fraud detection and empowering organizations to detect, mitigate, and prevent fraud more effectively. Here’s how technology is driving advancements in fraud prevention.

AI-driven fraud detection systems

Bank leaders want AI to be the answer. Seven in 10 banking executives say AI will be the most critical technology over the next decade. Technology is moving quickly, and it takes good AI to combat and detect future false and fraudulent AI usage.

Biometric verification

An Experian report found that 85% of consumers report physical biometrics as the most trusted and secure authentication method. However, less than a third (32%) of businesses use biometrics to detect and protect against fraud. This is a big disconnect that may impact where customers choose to secure their funds in the future. 

Behavioral analytics

Behavioral analytics involves analyzing patterns, trends, and anomalies in human behavior to gain insights into individual or collective actions, preferences, and decision-making processes. Technology with liveness detection includes a layer of behavioral analysis and is a crucial component in biometric systems. Its goal is to determine if a sample being captured is from a live person rather than a spoof or fake.  

Data analytics and machine learning for anomaly detection

Data analytics and machine learning techniques are widely used for anomaly detection across various domains, including cybersecurity, finance, healthcare, and manufacturing. Anomaly detection involves identifying patterns or instances that deviate significantly from normal behavior or expected outcomes.

Best practices for mitigating banking fraud

As fraud behaviors shift, banking fraud detection platforms must keep up at the same pace. Updated software that can detect synthetic identities is also needed as the number of platforms that create realistic replicas of voice and speech increases.

Eight of the top 10 US banks and credit unions trust Pindrop® to provide voice authentication and fraud detection. The overarching goals remain to increase data security and fraud protection, consider the customer experience, reduce authentication, and improve self-service costs. By implementing these practices, financial institutions can enhance their security posture and effectively combat emerging threats in the evolving landscape of banking fraud.

Secure banking operations with Pindrop® security solutions

The contact center is often the weakest point for fraudsters to enter many companies. Pindrop® technology offers a solution-driven approach to secure banking operations and provides a comprehensive and advanced security framework for the evolving banking landscape. Pindrop’s voice fraud detection signals in the voice channel and the IVR to gain a clearer view of fraud impact. The goal is cutting-edge voice biometrics, machine learning for fraud detection, and enhanced brand and customer reputation. 

To learn more, see how Pindrop® safeguarded $56M in assets while maintaining customer-centricity for a top commercial bank.