Revolut bets on in-house artificial intelligence: fintech launches dedicated AI research unit

British financial services company Revolut has taken a significant step in its technology strategy, announcing the launch of a division specialized in artificial intelligence research. The decision marks a clear shift in direction for the fintech, which has until now relied partly on third-party AI solutions for various features across its platform.

According to Tech.eu, the new unit's main objective will be to build proprietary AI infrastructure covering as many components of the company's technology stack as possible. This approach reflects a philosophy increasingly common among major tech players: keeping algorithms and models in-house means more flexibility, better data security, and potentially competitive advantages that are difficult for rivals to replicate.

Why Revolut is moving away from external solutions

The main driver behind this strategic move is technological independence. In the financial services industry, where data protection and information security regulations are extremely strict, dependence on external AI providers can create operational and compliance risks. By developing its models internally, Revolut gains greater control over how customer data is processed and used.

Additionally, building its own AI infrastructure allows the company to tailor solutions to the specific needs of its users—from fraud detection to personalized financial assistance—without being constrained by the limitations or costs imposed by third-party providers.

A broader trend in the fintech industry

Revolut's move aligns with a trend observed among other major players in the financial technology sector, who are investing heavily in their own artificial intelligence capabilities. This trend points to a maturing market, where companies no longer view AI merely as a supporting tool but as a central pillar of their long-term business strategy.

It remains to be seen how quickly the new unit will deliver concrete results, and whether the investment in in-house research will justify the high costs associated with developing advanced AI technologies internally.