Across financial services software, vendors and their customers are chasing the same goal: how fast they can add AI to everything that moves. Speed alone is not what will separate the winners from the losers. The firms that come through will be those that apply AI in ways that strengthen durable value, trust and duty of care, rather than compromise them.
In this contributed article, Chris Livesey, chief executive of the financial controls software firm AutoRek, argues that the real test of AI in financial services is not how quickly it is adopted, but whether it protects the controls the sector depends on.
A strategic divergence between providers and their customers
Financial services technology buyers have long struggled to integrate applications and data across fast-moving businesses. The complicated and often fragile integrations that sit on the edges of these applications are costly to build and troublesome to maintain, and they carry clear operational risks around data security and resilience. This runs across a wide range of applications on different stacks, with varying interoperability, and often a heavy reliance on legacy systems of record.
The appeal of AI is obvious: a way to navigate these estates of applications and data with little change to the underlying systems, creating new insight and unlocking new value. It is tempting to imagine AI as a universal solvent that dissolves complexity without touching the architecture beneath.
Some buyers are going further, and asking whether they could remove certain applications altogether, replacing them with self-built agentic services that meet the same need across their domain, freeing them from licence costs and letting them work at the speed of their business rather than the speed of a supplier. Some software vendors, in turn, see disaggregating their own applications into agentic services as a way to keep offering the value of their expertise, and to protect their businesses from customer self-build.
Where enterprise architecture is heading
Large enterprise software stacks will almost certainly be broken up into capability platforms that a hybrid workforce of people and AI agents can operate. Those capabilities will sit alongside a wider ecosystem, orchestrated centrally where possible and underpinned by an operating-model control plane that spans data quality, governance and interoperability. The competitive ground will shift from the edges of applications to the ownership of agentic orchestration and decision-making.
That control plane is where agents and humans meet, and how it works in practice is still unclear. It is also where buyers and suppliers will need to converge. If they do not, disconnected strategies risk fragmenting approaches, standards and methods, and increasing fragility in the underlying business services: the opposite of the enduring value financial services firms are trying to give their own customers. In financial control, this matters even more, because the operating model itself is the product.
The destination is trust
In financial controls and regulatory compliance, the work starts with the control and moves outward. The need for provable results has not changed; what has changed is the range of technologies available to deliver them. There is real, durable value in using AI to shorten implementation, improve configurability and embed intelligence into financial control. The point is to move fast where AI genuinely strengthens those outcomes.
Much of the current AI narrative implies the opposite, treating controls as secondary to the technology and suggesting that regulation will have to adapt to AI rather than the other way around. How regulators and the audit profession respond to an AI world remains to be seen, but if their goals stay centered on protecting people and society, that adaptation is unlikely to make easy room for new risk.
AI is an accelerator, not a substitute. The question is not whether it will reshape the operating model, because it will, but whether it does so in a way that enhances the duty of care financial institutions owe their customers. Applied well, AI strengthens trust, accuracy and confidence. That is the destination.
About the author
Chris Livesey is chief executive officer of AutoRek, a financial controls and reconciliation software
provider serving banking, payments and insurance firms.
The post AI May Well be a Big Accelerator, but Let’s not Forget the Destination appeared first on The Fintech Times.
