The Good and the Ugly with AI in a Bank

Welcome back to my Tech Blog! This time, I will delve into how Artificial Intelligence (AI) is reshaping the banking industry in ways we once only imagined in science fiction.

From enhancing security posture and performing automated security tests to analysing Red Team outcomes, AI promises a new era of banking efficiency and innovation. However, as with any powerful tool, AI also brings its own set of challenges and risks.
This article explores the GOOD aspects of AI, such as improving security measures and employee competence, and the UGLY aspects, including potential misuse by insiders and the increasing sophistication of cyber threats. I will examine these transformative benefits and potential pitfalls, particularly from a technology and non-financial risk perspective.

The Good – Revolutionizing Banking with AI

AI is a powerful tool for banks, particularly in enhancing security and operational efficiency. Here are some of the most impactful applications of AI for technology and security professionals in banking.

1. Improving Security Posture

AI can be used to continuously monitors and analyzes security events to identify potential vulnerabilities and threats. By leveraging machine learning algorithms, AI can detect patterns and anomalies that might indicate a security breach, allowing banks to respond proactively and strengthen their overall security posture.

2. Automated Security Tests

AI can perform automated security tests, such as penetration tests, to identify weaknesses in SEB applications or systems. These tests can be conducted regularly without human intervention, ensuring that security measures are always up-to-date and effective against the latest threats.

3. Cyber Threat Actor Simulation and Emulation

AI will be important to use to simulate and emulate cyber threat actors, providing a realistic testing environment for security defences. This allows banks to evaluate their preparedness against sophisticated attacks and develop strategies to mitigate potential risks.

4. analysing Red Team Outcomes

AI can analyze the outcomes of Red Team exercises, identifying the most significant vulnerabilities and proposing targeted remediation measures. By automating the analysis process, AI ensures that all critical issues are addressed promptly and effectively. AI will never decide, we use AI conclusions for decisions. 

5. Education and Competence Lift

AI can personalize training and development programs for employees, enhancing their cybersecurity skills and knowledge. This continuous education helps maintain a high level of competence across the organization, ensuring that staff are equipped to handle evolving threats.

6. Real-Time Threat Detection and Response

AI can detect and respond to threats in real-time, significantly reducing the time between detection and mitigation. This immediate response capability is crucial in preventing data breaches and minimizing damage.

7. Enhancing Compliance and Regulatory Adherence

SEB already use AI to adhere to regulatory requirements by automating compliance checks and ensuring that all processes align with the latest standards. This reduces the risk of non-compliance and the associated penalties.

The Ugly – Risks and Challenges of AI in Banking

Despite its myriad benefits, AI also presents significant risks that banks must manage carefully, particularly in terms of technology management and non-financial risks:

1. Internal Misuse of AI Systems

AI systems can be exploited by malicious insiders. For instance, an employee might manipulate AI algorithms to approve fraudulent transactions or access sensitive data. In another scenario, a consultant might use AI tools to siphon off confidential data for personal gain. These incidents highlight the need for robust internal controls and continuous monitoring to detect and prevent such activities.

2. AI-Driven Cyber Threats

The dark side of AI is that it can also empower cybercriminals. Threat actors are leveraging AI to automate and enhance their attacks. AI can create sophisticated phishing emails, generate malicious code, and propagate malware through fake repositories or software updates. This makes cyberattacks more sophisticated and harder to detect, requiring banks to continuously evolve their cybersecurity strategies.

3. Ethical and Compliance Challenges

AI algorithms can inadvertently introduce biases, leading to unfair treatment of customers. Ensuring transparency and accountability in AI decision-making processes is crucial. Additionally, banks must navigate complex regulatory requirements to ensure their AI practices comply with data protection and privacy laws.

4. Increased Costs from Data Breaches

Recent reports indicate that the global average cost of a data breach has increased by 10% over the previous year, reaching USD 4.88 million, the largest jump since the pandemic. The costs associated with business disruption and post-breach customer support are significant. Many organizations pass these costs on to customers, which can be problematic in a competitive market already facing pricing pressures from inflation.

5. Impact of AI and Automation on Breach Costs

On the defender side, applying security AI and automation is proving beneficial. Researchers have found that these tools can lower breach costs by an average of USD 2.2 million. AI and automation reduce the time needed to identify and contain a breach, thus minimizing the resulting damage. Conversely, defenders without AI and automation tools take longer to detect and contain breaches, leading to higher costs and increased damage.

Balancing the Good and the Ugly

To effectively leverage AI while mitigating its risks, SEB need a dynamic and adaptive approach:

1. Robust Security Measures: Implement advanced security protocols and conduct regular audits to protect AI systems from internal and external threats.
2. Ethical AI Practices: Develop and enforce ethical guidelines for AI use, ensuring transparency, accountability, and compliance with regulatory standards.
3. Continuous Learning and Adaptation: Invest in AI-driven cybersecurity tools and update security measures continuously to stay ahead of evolving threats.
4. Dynamic Risk Management: Act dynamically based on real-time threat and risk assessments. Use AI to continuously improve security defences, adapting to the ever-changing threat landscape.
5. Employee Training and Awareness: Educate employees about the ethical use of AI and the importance of cybersecurity. Encourage a culture of vigilance and accountability.

Final Thoughts

AI holds immense potential to revolutionize the banking industry, offering significant benefits in customer service, data analytics, fraud detection, operational efficiency, and employee empowerment. However, the risks associated with AI misuse and cyber threats cannot be ignored. 

At SEB, we have been at the forefront of AI adoption, leveraging its capabilities to enhance our business models while carefully studying and countering its potential pitfalls. By adopting a balanced approach that emphasizes robust security, ethical practices, continuous learning, and dynamic risk management, we can effectively harness the power of AI to drive innovation and growth in the banking sector, ensuring we remain a trusted partner for our customers now and in the future.

At SEB, Security is Innovation and Trust in Action!

Author: Ulf Larsson, Security CTO