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Will generative AI crack the code for bank tech teams?

Banks could roll out tools to help translate old—or write new—code within months.

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One of the major difficulties introducing generative artificial intelligence (AI) into the heavily regulated financial sector is ensuring those who use it have suitable expertise to understand its risks.

That requirement means one particular use case could be easier to adopt: assisting coding teams who already have a good grasp of algorithms and their limitations. Risk.net, a sibling publication of WatersTechnology, has spoken to more than 20 sources and determined that at least four global

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M&As, MCPs and why clean data is essential

The Waters Wrap: Financial firms are racing to adopt AI—but the payoff depends on having the right foundations, particularly clean, normalized data, writes Wei‑Shen.

How governance-first architecture stabilizes complex systems

Chetan Patil argues that many transformation projects fail not because of the technology but because of weak data governance. Adopting a governance-first discipline early (and building speed, resiliency, and credibility over time) is best.

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