Striking a balance: Addressing the dual nature of AI in banking

While AI holds great promise for the future of banking, it is not without its flaws. File photo.

While AI holds great promise for the future of banking, it is not without its flaws. File photo.

Published Jun 24, 2024


Artificial intelligence (AI) has brought transformative changes to various industries, including banking and financial services. “While the use of AI in banking is not new, its adoption has expanded in recent years, particularly in areas like fraud protection, prevention, and improving the customer experience,” explains Doros Hadjizenonos, regional director at cybersecurity specialists Fortinet. “However, it is important to recognise that AI can have both positive and negative impacts on the sector.”

Enhancing security measures through AI

Every day, banking services are accessed by millions of consumers for things like bill payments, depositing funds, and transferring money. It’s the ordinary nature of these tasks that make them vulnerable to fraud, which is a major concern in the industry. One of the primary motivations for implementing AI in banking is to revolutionise security measures to help prevent these types of attacks through various applications, such as fraud detection and biometrics.

“AI has the power to help banks detect abnormal patterns, identify system loopholes, and then recognise potentially fraudulent activity in real-time,” says Hadjizenonos. “That is why AI systems are superior to manual security measures and detection. AI can be used to rapidly analyse large sets of data that no human brain could possibly process and can come up with AI-assisted decisions and conclusions on an issue when needed.”

Ensuring consumer trust in AI-powered banking

While AI offers benefits like increased efficiency, enhanced customer support, and superior risk management, banks also need to consider the vulnerabilities of these systems, such as data privacy breaches. “Regarding data privacy exposure in the banking sector, sensitive customer information can be jeopardised if not handled properly or if adequate security systems are not in place,” Hadjizenonos notes.

Let’s not forget that AI systems themselves can still be vulnerable to cybersecurity threats. “AI has become a double-edged sword for cybersecurity. On the one hand, it has lowered the barrier to entry into cybercrime, enabling would-be criminals to generate malware even when they lack programming skills and providing more sophisticated criminals with capabilities few could have imagined a relatively short time ago,” says Hadjizenonos. “On the other hand, cyber defenders can take advantage of AI for intelligent automation and defence strategies. AI has the potential to level the playing field – even against AI-equipped adversaries and the dynamic threats they pose.”

Furthermore, banks must ensure the best possible customer experiences to maintain trust in the system. “To achieve this, banks should be transparent with consumers about their use of AI applications to protect their data and mitigate security risks,” says Hadjizenonos. “Clear consent from consumers should also be required to ensure that their data is only used for its intended purpose.”

AI integration and ethical banking

Maintaining a balance between leveraging AI for security and upholding transparency and ethical practices is crucial for banks to protect consumer interests.

One of the concerns is that AI algorithms can be inadvertently unfair and biased in data relating to gender, race, ethnicity, educational background, and location. These biases can lead to limited access to fair credit scoring, investment strategies, and customer service for certain individuals. For this reason, banks looking to take advantage of AI should be smart about it. They should investigate the market and work with providers whose commitment to security and accuracy matches their needs. Teams using the model should also be trained to reflect best practices.

AI-powered systems play an important role in making banking safer, whether it is analysing unusual spending behaviours and spikes in transaction amounts or adapting and learning instantaneously to stay ahead of cyber threats. Nevertheless, it’s important not to overlook the challenges that AI in the banking sector can bring about.