Tushar Vartak, Executive Vice President & Head of Information, Cyber Security and Fraud Prevention at Rakbank, discusses the impact of AI, identity security, cloud adoption and thirdparty risk on the modern banking security landscape.

The banking sector continues to face increasingly sophisticated cyber threats, from ransomware to AIdriven attacks. How has Rakbank’ s cybersecurity strategy evolved to address today’ s threat landscape while maintaining customer trust?

The threat landscape has changed in character, not just in volume. Attacks are faster, better resourced and increasingly automated, and they target people and processes as often as technology. Our strategy has evolved from a perimeter-and-compliance mindset to a risk-led model built on the assumption that no single control is infallible. That means layered defences, continuous monitoring, and the ability to detect and contain quickly rather than relying solely on prevention. It also means treating cyber risk as a business risk, discussed in the same language and the same forums as credit, liquidity and operational risk, with visibility at Board and executive level. Customer trust sits at the centre of this. Trust is earned through consistency: services that stay available, data that stays protected, and clear, honest communication when customers need guidance. We invest continuously, we test ourselves

rigorously, and we hold ourselves to the standards our regulators and our customers rightly expect. Ultimately, resilience and trust are two views of the same commitment.

AI is transforming both cyber defence and cybercrime. How are you leveraging AI to strengthen your security operations, and what safeguards have you put in place to manage the risks associated with AI adoption?

AI cuts both ways. Adversaries use it to scale social engineering, craft more convincing lures and shorten the time between discovery and exploitation. Defenders gain the same leverage. We use AI and machine learning primarily to reduce noise and compress response times, helping our analysts see the signal earlier, correlate events across a large estate, and focus human judgement where it matters most. The intent is augmentation, not replacement; consequential decisions stay with experienced people. On the risk side, we treat AI as a governed capability rather than a free-for-all. Use cases are assessed before deployment, data

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