AI in financial services, the latest insights from Evident

Introducing the latest from Evident

The latest round of insights from Evident dropped into subscriber inboxes earlier this month. Evident’s benchmark, which has now been running for three years, is “the” place to look for an indication of AI maturity and readiness among the biggest players financial services across the globe.  Evident’s stated aim is to “separate “hype” from “reality” in areas of strategic investment undergoing profound, disruptive, and lasting change”. 

To produce its benchmark, Evident cuts through masses of publicly available data relating to banks across the US, Europe and Asia, and distils its findings into easy-reading reports that focus on increasing transparency, and dissipating best practice, for the benefit of others in the market and for broader societal gain. In a space where transparency has been slow to arrive on the scene, it seems that the leaders of the pack are now becoming more open to sharing their hard-earned learning. Evident notes that financial services may now just be on the “cusp of moving from scattered anecdotes of AI: ROI to demonstrable, sustained value delivery and broader reporting at enterprise level”.

Who are the “leaders”?

It is fair to say that this is not a level playing field. The “Top 50” tracked by Evident are the largest global banks by reference to total assets. This is noted as key, as is the significant advantage that disruptors, who fall outside of tracking scope on numbers, may have over their larger rivals. Smaller banks, and the challengers, may well be more digitally advanced, operate with leaner structures, be less bogged down with red tape, and be more agile than their larger competitors. These advantages have the potential to allow them to outmanoeuvre the mega-banks, benefit from second mover advantages, learn from the mistakes made by others, and close the gap that has for now been created, more quickly than might be anticipated.

The leadership gap

There is quite some hype around the significance of the gap between the leaders and the peloton. Will the leaders be the only ones who can unlock the real potential of AI? Will the “laggers” fall so far behind that they can never catch up? Evident observe that the same handful of US banks have consistently been in the lead for the last three years and that their gains are now enabling them to pull further ahead. These leaders have invested relentlessly, hired talent at pace, and are now moving at speed, into the next phase of the deployment cycle, which is predicted to be where they will experience value creation, fundamental re-wiring of their organisations with AI fully embedded, and tangible scale up. There is some risk for those that do not keep pace, that the leaders will accelerate faster and faster leaving them constantly playing "catch-up to a moving target”. 

The key levers 

Evident focusses on four “primary enablers” or “key levers” into which the leaders have poured investment in order to drive an unlocking of value in AI. These key levers are:

• Talent: Talent is the foundational lever and is noted as being “critical to successful AI deployment”. This enabler is about investment in the technical expertise that is required to build robust and compliant applications and fully integrate them into a business. Evident is tracking the employment levels of “AI and Data talent” (that is, those people working in AI Development, Data Engineering, AI Model Risk, AI Software and Implementation, AI Product Management etc.), in addition to visible initiatives to hire, retain and develop AI talent and level-up AI literacy throughout the rest of the organisation (including partnering with leading academic institutions and offering qualifications such as doctorates and master’s degrees). Evident observe that “47 out of 50 banks increased their density of AI talent…..the expansion of AI talent is proceeding at 5x the rate of growth of the overall employee base, 47 of the 50 banks tracked in the Index are improving the ratio or “density” of their AI talent relative to total headcount…..But this critical mass of AI workers is not evenly distributed. In fact, ten banks account for nearly half (49%) of the total talent employed by 50 banks in the Index. Moreover, the five banks with the largest teams are not geographically diverse – they’re all based in the United States”. Evident note that the banks with the talent enter a virtuous circle, compounding returns on AI talent and creating what they refer to as an accelerating “flywheel effect” which spurs the continual recruitment of the top talent available in the market and accelerates digitisation.  
• Innovation: Innovation is the fuel for the engine, enabling AI development and adoption, and has a direct impact on an entity’s route and time to market. Long-term investment in AI (including, for example, leading research, and collaborating with leading academic institutions), development of AI specific intellectual property and intellectual capital, strategic investment in and acquisition of AI specific companies, and visibly high levels of engagement (for example, in leading conferences, and partnering with academic institutions), has enabled the leaders to be strategic about where to invest and where to partner, whether to “build, borrow or buy”, and to leverage their lead becoming ever more agile and making their AI deployment ever more effective.
• Leadership: Leadership provides the steer on the narrative, the strategy, the communication, and the thought leadership. Leadership helps to build confidence among stakeholders by making strategic use of coverage across a range of media channels including the press, social media, investor and customer relations, and industry events. Leadership can develop a clear and credible narrative. By positioning the c-suite leaders at the front of industry discussions, building talent, strengthening relationships, providing in-depth updates on use cases (including information on the impact of them, details of how roll-out was achieved, what the financial outcomes are, the productivity that has been gained, the benefits that can be evidenced for clients and employees, etc.) these leaders can set expectations, indicate the path ahead, and build confident relationships with all stakeholders, including the regulators.
• Transparency and responsible AI activities: Transparency and responsibility are drivers of root and branch embedding of fundamental ethical principles throughout organisations. They are levers to the reduction of regulatory and reputational risk, the building of investor and consumer confidence, the deployment of responsible, explainable, auditable and trusted AI, and the development of competency in AI specific governance, risk and compliance.  

The UK’s position in “the race”

During their roundtable, where they delivered their latest key findings to a live audience, Evident were (in their own words) quite “grumpy” about the UK which, although it has a strong talent pool, a substantial level of university-level focus on emerging technology, together with a vibrant start-up scene, is perhaps not currently doing enough of the right thing to ensure that there is an environment where the start-ups remain and retain their talent with them. That said, four out of five ranked UK banks appear in the top half of Evident’s index and rank highly for transparency, currently placing the UK in a leading position relative to the safe and responsible deployment of AI.  This result is happily consistent with the UK's regulatory stance on AI.

Some key take-aways

Despite the evidence of some hype, notably around the risks of lagging behind for those not ranked in this particular version of elite, there are some grounding signs for those that are looking for some key indicators of what is going around the world in financial services with which to inform their own AI journeys:

• It is still early days: Even the leading banks, who have been longtime investing in AI capability, pouring countless hours of preparation into projects, frequently revising and re-planning their AI initiatives, and who have very significant resources are still in the “foothills” of this journey and, even among these leaders, many are not yet ready or able to make significant disclosures. It is going to take time and sustained effort for the industry to build out, capture, and report credible information on what the proof points are and underpin and evidence AI development that is genuinely mature and referenceable.
• It is not all about deep pockets: Without a doubt, the leading banks have significant and likely increasing AI investment resources. However, there are still going to be competitive advantages in other key factors, including creating the right culture, having the right people, taking the time to establish foundational capability, being more digital by nature, and being nimble.  
• Talent: Talent holds the keys to AI adoption, and without it, it will be difficult to advance in AI. Evident point to a clear correlation between talent and outcomes and “an accelerating flywheel effect between AI talent and progress on practical business level applications”.
• Time: The leading banks started their AI journeys a long time ago. They have continually invested, they have been building research laboratories, sourcing talent, partnering with business developing AI, creating a narrative around their roll-outs of AI to their employees, disclosing use cases, disclosing their outcomes, and their return on investment. Behind these disclosures are years of thinking.

Conclusion

Evident’s index helps, at a time when few are ready to engage in open discussions, to bring valuable context and information to many others in the financial services ecosystem who are on an AI adoption journey. Along the journey, it is going to be vital for financial services entities to collaborate, to align, to engage, to set the agenda, to get involved in shaping emerging standards and frameworks. All of these initiatives, when combined, and given time, will start to produce tangibles, deliverables and validation in the form of case studies, use cases, and research papers, and what currently may seem abstract will begin to turn into clearer evidence of what form safe and responsible AI will take as it operationalises in the real world. 

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If you would like to discuss how current or future regulations impact what you do with AI, please contact me, Tom Whittaker, or Martin Cook. You can meet our financial services experts here and our technology experts here.

UK banks now hold four of the top-10 spots in the Transparency rank, underscoring the UK’s ambition to lead in the Responsible AI (RAI) space

https://evidentinsights.com/reports/key-findings-report-banking-2025?id=ee70baf26d