AI readiness checklist for banks

Every bank is under pressure to have an AI strategy. Vendors are pitching, boards are asking questions, and regulators are watching closely.

The real question isn’t if you’ll use AI, it’s whether your data, core systems, teams, and governance are actually ready to support it without adding risk.

Our AI readiness checklist for banks helps you answer that, clearly and honestly. It’s designed for product, tech, data, risk, and compliance teams to complete together.

Move from AI talk to AI you can trust in production

Download the AI readiness checklist here.

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AI fraud detection guide for digital-first banks in 2026

Fraud in emerging markets just changed. Rule-based fraud detection systems are obsolete. Here's why: more than 50% of fraud now involves AI, but most detection systems can't adapt faster than fraudsters iterate.

The good news is that institutions using AI fraud detection can achieve 90-99% accuracy. But only if they solve data infrastructure first.

This playbook covers everything from deepfake-enabled account opening to fraud-as-a-service marketplaces. But the centrepiece is this: the same institutions that detect fraud in real-time are the ones whose cores process transactions as events, expose customer data through APIs, and let teams investigate without a vendor ticket.

Your fraud tools are only as good as your data layer. This guide shows you how to build it.

Think bigger. Go further.

Come and see the future with us. Talk to one of our core banking experts.