Why your bank’s AI pilot failed and how to fix it
Most banks’ AI pilots fail not because of poor models, but because their legacy core systems and data layers can’t support real AI in production.
Case Study: Esquire Financing
Frustrated by the mounting limitations of their legacy systems, Esquire began exploring options for a full-scale transformation. Oradian’s cloud-native core proved to be the right fit. With real-time capabilities and easy integrations, Oradian gave Esquire the tools to scale fast and serve more SME clients without sacrificing control or speed. Follow the story so far.
Find out how Oradian helped power business growth for Esquire Financing.
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AI use case prioritisation matrix for banks
Every bank is under pressure to do something with AI, but not every use case should be first.
This matrix helps product, tech, data, risk, and compliance teams decide where to start and what to park.
Use the template to score AI ideas across impact, feasibility, data readiness, regulatory sensitivity, and time-to-value – so you can move beyond hype and focus on use cases that are both realistic and meaningful.
90-Day AI pilot planning template
This 90-Day AI Pilot Planning Template helps banks turn AI from a slide in a board deck into a live, measurable pilot.
In four simple sections, it guides your product, tech, data, risk, and compliance teams to align on one realistic use case, the data it needs, and a safe 90-day timeline.
It also covers governance, success metrics, and rollback plans so you can move fast without adding uncontrolled risk. Download the template to leave your next AI discussion with a concrete plan.
Think bigger. Go further.
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