Banks and other financial institutions (FIs) use online banking to enrich their portfolio of services and operate more efficiently. However, while digital banking has propelled revenue and profitability, it has also raised cybersecurity concerns. Research shows that the finance industry is the second-most targeted industry for cyberattacks. This alarming trend indicates that the finance industry needs to invest in more sophisticated threat detection solutions to prevent costly breaches because they can cost $3.7 million to resolve.
To advance banking cybersecurity, FIs are turning to technology that has already added immense value to their operations—AI. Institutions have yet to tap into the full potential of AI, and it can be a valuable asset when improving online banking cybersecurity.
Despite taking steps to secure their data, the finance industry still faces plenty of challenges when it comes to data security.
One factor undermining security is the growth of non-cash payment transactions. In 2017, the number of non-cash transactions was over 539 billion. This is expected to grow to 1046 billion transactions by 2022. The sheer volume of transactions makes it hard to distinguish authentic ones from attempted phishing attempts, leaving room for possible cyber attacks.
The growth of mobile apps, internet banking, and instant payment technology has opened up multiple endpoints for firms, making it difficult to secure digital infrastructure. This is because certain cybersecurity processes, such as manual threat hunting, have become impossible to do in the current environment. Cybersecurity specialists cannot analyse billions of transactions to prevent a breach, regardless of their proficiency.
Furthermore, while banking networks are expanding, cyber attacks are evolving.
Hackers are never static; they are always looking for new ways to bypass existing security mechanisms to access the data. This creates a situation where existing firewalls and threat detection systems become obsolete because they cannot evolve with cyberattack methods.
When cyber defence mechanisms are compromised, it raises concerns about data security. Moreover, FIs could find themselves out of compliance with regulatory standards set by the GDPR and other regulatory bodies.
To tackle these challenges, banks need to invest in advanced cybersecurity mechanisms that evolve.
FIs can use AI to augment cybersecurity defences; it would be relatively easy to implement because AI is already an integral part of business operations; therefore, extending it to improve cybersecurity would be a simple transition to execute.
Automate threat hunting
AI can automate the threat hunting process to improve detection rates by over 95%; this will not only improve detection rates but also guard your cybersecurity infrastructure against evolving threats. AI solutions can also integrate additional tools, like behavioural analytics, to strengthen threat hunting and these models can be used to develop profiles on banking applications to identify vulnerabilities faster.
Tackle new threats
New threats are always around the corner, but with AI, FIs have a much better chance of meeting these new challenges by integrating automated banking cybersecurity applications into the process. AI applications can learn from previous patterns and leverage the information to look for early signs of an attempted attack. Furthermore, cyber threats, such as bots, work too fast for manual methods and could undermine cybersecurity if AI applications are not used.
Predict risk breaches
AI can improve banking cybersecurity by predicting cyber breaches before they happen. AI cybersecurity platforms can determine IT asset inventory by analysing records of all devices, users, and applications. Based on the information, AI applications could predict where an attack could take place and flag particularly vulnerable applications for IT technicians to tackle.
Improve endpoint detection
With apps and remote devices used to share financial data, mobile banking cyber threats are a growing concern. To tackle this problem, there is a need to improve endpoint detection. AI applications play a crucial role in securing these endpoints by establishing a baseline for behaviour through a repeated training process—if something unusual occurs, AI applications can flag it and send a notification to the IT team to resolve it.
Online banking is growing and will continue to be an integral part of financial operations. To protect banking networks, it is important to invest in more advanced cybersecurity applications powered by AI.
AI-powered cybersecurity would allow your cybersecurity team to guard their network more effectively to reduce data breaches and meet compliance requirements. AI applications are key for making this happen as they can improve cybersecurity, making it agile, responsive, and effective.