Author

Dan Brightmore

Published

10 October 2025

Estimated Read time

8Mins

Evident’s annual AI Index reveals the banks making the biggest moves in AI… JPMorganChase, Capital One and Royal Bank of Canada are the three leading banks in AI adoption…

JPMorganChase has maintained its position as the world’s most AI-advanced bank in the Evident AI Index. The global standard benchmark for AI adoption in the financial services sector.

According to Evident, the leading banks for AI maturity have pulled away from their peers in 2025, consolidating earlier gains and – increasingly – realising ROI for their AI investments. 

Evident AI Index

The annual Evident AI Index evaluates the ongoing AI performance of 50 major banks in North America, Europe, and APAC against 70+ indicators drawn from millions of public data points.

It reveals that although nearly every bank is advancing in the Evident AI Index, the top 10 banks are increasing their scores 2.3x faster year-on-year than the rest of the Index.

This year’s top three AI performers – JPMorganChase, Capital One and Royal Bank of Canada – have retained their rankings for a third successive year. JPMorganChase takes the top spot in three of Evident’s four pillars of AI capability – Innovation, Leadership and Transparency. Capital One leads on Talent, and has continued to gain ground on its rival. While the two undisputed leaders have further extended their lead, there is now little to separate the two in terms of overall AI maturity.

The top 10 is increasingly dominated by US-headquartered institutions, but RBC, UBS and HSBC continue to secure places among the global leaders as the top performers in Canada, Europe and the UK respectively. 

Based on the Evident AI Index, the ten banks leading the race for AI maturity are:

BANK2025 INDEX2024 INDEX2024-25Change
JPMorganChase11–
Capital One22–
Royal Bank of Canada33–
CommBank45+1
Morgan Stanley510+5
Wells Fargo64-2
UBS76-1
HSBC87-1
Goldman Sachs911+2
Bank of America1015+5

“Banking is one of the most advanced and competitive industries on the planet when it comes to developing and rolling out AI at scale. While some have described recent history as ‘The Summer AI Turned Ugly’, in the banking industry a different story is playing out. We’re beginning to see clear signs that AI investment is starting to translate into tangible financial gains, both in terms of efficiency and, increasingly, via new revenue opportunities. Banks and their shareholders expect ROI to accelerate over the next few years, and those in our top 10 are in pole position to see their efforts come to fruition.“

Alexandra Mousavizadeh, Co-founder & CEO, Evident

By far, the most competitive segment of the Index was found among those banks ranked just outside the top 10. All five of the banks in this range – BNP Paribas (#11), Citigroup (#12), TD Bank (#13), BBVA (#14), and Lloyds Banking Group (#15) saw a >20% increase in scores year-on-year (compared to ~10% for the wider Index), highlighting the intensity of the battle to keep pace with the leading banks.

Across the regions covered in the Index, all six regional leaders are unchanged from 2024, with the gap between domestic leaders’ and laggards’ AI capabilities also growing year-on-year.

Mousavizadeh adds:

“Bifurcation in AI maturity creates a credibility gap. Banks that fail to keep pace risk losing the confidence of boards, regulators, and investors. At the same time, lagging institutions will struggle to attract and retain top-tier AI talent. This combination of stakeholder doubt and the risk of talent flight slows deployment, undermines momentum, and compounds the difficulty of turning AI investments into measurable business outcomes.”

HSBC Heads Top AI Performing UK Banks

When it comes to AI adoption, the UK is one of the most consistent regions in terms of bank performance. Four of the five UK banks rank in the top half of the Index. Three of the five UK banks advanced their position in the ranking year-over-year. And all five UK banks are tightly clustered – featuring the narrowest spread between the top-performing bank (HSBC) and bottom-performing bank (Standard Chartered) across every region.

Responsible AI continues to be an area of strength, with four of the five UK banks ranking among the top 10 in the Transparency pillar. Conversely, no UK bank places in the top 10 in the Talent pillar.

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HSBC improved its standing by +1 position across both the Talent and Innovation pillars, while ceding ground in Leadership (-10 rank) and Transparency (-3 rank). Consequently, HSBC lost one position in the overall ranking, but maintained a spot among the top 10 banks.

In contrast, Lloyds Banking Group demonstrated the most forward momentum, rising from 27th to 15th in the ranking. This performance was buoyed by significant jumps in Talent (+12 rank), Leadership (+20 rank), and Transparency (+14 rank), with Lloyds one of only four Index banks to improve across all four pillars of the methodology.

Mousavizadeh comments:

“Lloyds Banking Group’s strong performance reflects a significant mindset shift at the bank, with the establishment of a centralised AI team and an increased focus on AI hires to accelerate the execution of its AI strategy. The upshot is that Lloyds is now sharing more details of its active use cases and long-term plans, translating into a much improved ranking in the Index.” 

In a short space of time, Lloyds has matched HSBC in the number of recent AI use cases specifying outcomes. In March, the bank filed a patent for its Global Correlation Engine (CGE) – documenting an AI-driven approach to cybersecurity threats that results in 92% fewer false positives. And in July, the bank rolled out Athena, its first large-scale GenAI product.

Measuring Returns on AI Investment

According to Evident, twice as many banks reported a total number of active artificial intelligence use cases (jumping from 12 to 25 banks since last year), and 32 out of 50 have disclosed at least one use case with an associated financial or non-financial impact – up from 26 in 2024. 

While more banks are reporting returns at the use-case level, only a small group have quantified the performance of their AI portfolios at Group level. Today, eight banks are disclosing portfolio-level ROI estimates – either realized or projected – with just three reporting both.

These frontrunners include BNP Paribas, DBS, and JPMorganChase (all of which have already revised projections upwards). JPMorganChase is at the top of the table, raising its estimates from $1 billion to “heading more towards $2 billion” in AI-driven benefits, according to President and COO Daniel Pinto.

Annabel Ayles, Co-founder & Co-CEO of Evident, comments:

“All banks – regardless of size – are increasing their AI budgets, and our data shows virtually every key metric of AI adoption increasing.We’re already seeing these investments translate into tangible examples of use cases deployment. And our discussions with banking leaders suggest they’re expecting to see material, reportable AI returns in the next 12-18 months. Our data strongly suggests that this achievement is imminent. The question is: how big will the returns be? If they exceed expectations, current AI investment levels could pale in comparison to what comes next.”

Talent, Innovation, Leadership and Transparency in AI

According to Evident, the top 10 banks in the Index all demonstrate industry-leading AI performance across at least one of the four pillars, as follows:

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Talent: 

  • Ten banks now employ almost half of all AI talent in the Index (circa 90,000 workers), with US banks dominating the leaderboard.
  • The AI talent pool across the top 50 banks grew 25% year-over-year, the fastest on record, nearly 5x faster than overall headcount growth.
  • On average, the top 10 banks by talent volume disclosed nearly 2x more use cases than the rest of the banks in the Index.
  • 38 of the 50 banks now disclose some form of AI training to its employees (up from 32 banks last year). And 33 banks now offer distinct training for senior leadership.

Innovation: 

  • JPMorgan retained #1 spot for Innovation through the unparalleled strength of its AI research team and continued venture investments into AI-focused companies. 
  • Capital One overtook Royal Bank of Canada for the #2 spot, partly driven by the Discover merger, doubling its AI research team and showing steady growth in patents.
  • HSBC moved up to #8, the leading light amongst the European banks, who otherwise don’t feature.
  • Despite banks rushing to fund hyperscalers and the infrastructure that will power the AI era, general investment by banks into AI-focused and Data/Tech-focused companies is down double digits (17% from 2024) for the second year in a row.

Leadership:

  • Over the past year, even those organizations that have traditionally chosen to keep their progress behind closed doors, are making their AI activities more visible.
  • Five banks maintained their top 10 ranks in Leadership: JPMorganChase took the top spot, strengthening its external AI communications efforts considerably, and Royal Bank of Canada jumped +5 ranks to take #3 position, publishing projected financial returns from AI for the first time during its Investor Day in March.
  • New entrants to the top-10 included: Natwest, UBS, and Morgan Stanley – and while they did not go as far disclosing financial targets for AI value, they each provided richer updates on use cases and impact than ever before.

Transparency: 

  • JPMorganChase retained the top position for Transparency and seven of the top 10 banks carry over from 2024.
  • Responsible AI activity continues unabated across the industry – over the past year, the volume of RAI-specific talent found across the 50 banks more than doubled, and nearly 300 RAI-specific research papers were published, a +60% increase year-on-year. 
  • 35 of the 50 banks engage in partnerships with academic institutions, government bodies, or private companies (up from 31 banks last year), with nearly 80% of these partnerships yielding published case studies or use cases (up from 45% last year), demonstrating the increasingly tangible outcomes of their RAI efforts.

Evident AI Index Methodology

Since launching in January 2023, the Evident AI Index has quickly become established as the leading independent source of data and insight on artificial intelligence adoption across the banking industry.

The Index combines extensive research, automated data capture from public sources, consultation across Evident’s network of AI experts, and ongoing dialogue with featured banks.

Drawing from millions of public data points spanning 70+ individual indicators, it ranks each bank across four key capability areas which collective signal AI maturity:

  • Talent: measures the depth, density and development of AI talent within each organisation.
  • Innovation: captures long-term investment in AI-related innovation, including research, patents, partnerships and engagement with the open-source ecosystem.
  • Leadership: assesses the role of leadership in setting and communicating the organisation’s AI agenda.
  • Transparency: evaluates public engagement with Responsible AI (RAI), from internal talent and frameworks to external partnerships and disclosures.
  • Artificial Intelligence in FinTech
  • Neobanking

Author

Dan Brightmore

Published

17 September 2025

Estimated Read time

3Mins

New data from Evident shows banks are increasingly turning AI research into real-world tools

AI benchmarking and intelligence platform Evident has published its latest report… The State of AI Research in Banking, analyses over 2,700 AI-specific papers from 50 of the world’s largest banks. 

The State of AI Research in Banking

The report shows that the big banks have increased their annual artificial intelligence research output by 7x over the past five years. The most AI-advanced institutions are focusing on research areas that directly serve their AI production pipelines.

Since 2019, the number of banks publishing AI research has nearly doubled from 25 to 46 from 50 banks tracked by Evident. Last year, two-thirds of this research (65%) was driven by just five banks. They are JPMorganChase (37%), Capital One (14%), Wells Fargo (5%), RBC (5%), TD Bank (4%).

According to Evident, it’s possible to map the banks’ historic research pipelines directly to their artificial intelligence use cases and products. From RBC’s ATOM model powering responsible lending to Capital One’s multi-agent systems for customer service. Examples of banks where research papers have served as blueprints for production include:

  • Capital Markets & Trading: Scotiabank, RBC Borealis, BlackRock, JPMorganChase
  • Transactions, Risk, AML, and Fraud: RBC Borealis, NatWest, CommBank
  • Agentic AI and Workflow Automation: Capital One, JPMorganChase, UniCredit
  • Causal AI and Personalisation: BBVA, TD Bank
  • Customer Experience and Summarization: NatWest, JPMorganChase

“Through their research programmes, banks like JPMorganChase, Capital One, RBC, Wells Fargo, and TD Bank are setting the tone for how AI will be deployed in high-stakes, regulated environments. In contrast to the more commercially-guarded R&D practices of Big Tech, these banks are signalling the future of applied AI in financial services. And, most impressively, moving from research pipelines into production at scale within two to three years. Which is lightning fast by academic standards.”

Alexandra Mousavizadeh, Co-founder & CEO, Evident

The Rise of Agentic AI

The State of AI Research in Banking report also points to the rise of Agentic AI as a priority within the world’s largest banks. 

Evident’s data shows that AI Agents and Agent-based Systems research is now the fifth most popular research paper theme. Agentic themed research accounts for nearly 6% of year-to-date 2025 publications – or twice the current share of public agentic use cases Evident found across banking. 

As more resources pour into agentic research, there has been an accompanying year-over-year decline in papers focused on Computer Vision (-0.7%), Scientific Discovery (-1.8%), and Healthcare / Biomedicine (-2.2%). This data further underscores where and how banks are shifting efforts away from open inquiry, in favour of applied research that clearly relates to immediate business applications.

“While academic research within big business is often dismissed as a vanity exercise to keep PhDs happy, our analysis shows the opposite. The leading banks are pushing the frontier on emerging technologies like agentic AI – building the architectures and workflows that will soon underpin real-world applications. This isn’t research for research’s sake: it’s laying the foundation for faster deployments, smarter trading agents, and the next frontier of AI-driven financial services,” added Mousavizadeh.

About Evident

Evident is the intelligence platform for AI adoption in financial services. The company supports leaders stay ahead of change with in-depth insights, benchmarking, and real-time data through its flagship Indexes, Insights across Talent, Innovation, Leadership, Transparency and Responsible AI pillars, a real-time Use Case Tracker, community and events. Evident also provides private outcomes benchmarking, enabling firms to understand how their adoption of artificial intelligence compares to peers. Learn more at www.evidentinsights.com

  • Artificial Intelligence in FinTech

Author

Alexandra Mousavizadeh

Published

26 June 2025

Estimated Read time

4Mins

Alexandra Mousavizadeh, Co-Founder & CEO at Evident, on the rise of Agentic AI in financial services

Agentic AI is no longer the preserve of the distant future. Agents are already here, embedded in the day-to-day operations of businesses. As well as answering questions and crunching numbers, they’re making decisions, taking action, and learning on the fly. They can handle customer queries, tap into APIs, and even rewrite their own instructions.

It’s a big shift from traditional AI, which stayed firmly in the realm of prediction and recommendation. Agentic systems are very dynamic in comparison, and involve more acting and doing, which fundamentally changes the risk landscape.

For banks looking to capitalise on agentic, the implications are especially consequential. This is a highly sensitive sector where trust, compliance and control are existential issues. That is why Responsible AI (RAI) has quickly moved from being a nice-to-have to a critical foundation. It can balance the need for controls with the promise of innovation.

In our latest Responsible AI in Banking report at Evident, we found a clear upweighting of RAI priorities. More banks are appointing RAI leads. More are publishing principles. And more are thinking hard about how to scale those capabilities across the business.

But Agentic AI is a different challenge. It pushes past the limits of old governance models and forces a rethink of how we manage risk, maintain oversight, and build trust. 

Here’s why a rethink is needed…

Static Governance Doesn’t Work for Dynamic Systems

Most current AI oversight models are built for systems that behave predictably. They assume models will be trained, validated, deployed, and then monitored using relatively fixed parameters. This is no longer the case.

Agentic AI systems learn and act independently. They are decision-making agents as well as tools. That makes governance more complicated.

Banks need oversight models that can keep pace in real time. That includes enterprise-wide assurance platforms that can help to spot unexpected behaviour, adjust on the fly, and give leaders a clear view of what’s happening across the organisation.

Building the right tooling in this way is essential. What’s harder is laying out an agentic AI strategy and ensuring it’s being applied across teams, with clear direction on where agents will be used and the governance guiding decisions.

Having these failsafes in place is an approach that allows for continued innovation without running an unacceptable level of risk.

We’re Seeing a Regulatory Shift – from Theory to Evidence

AI regulation is morphing over time, moving gradually from high-level principles to concrete requirements that need to be backed up by evidence. The EU AI Act, NIST frameworks and ISO standards all suggest that financial institutions will need to demonstrate not just model performance, but responsible use.

This creates new compliance needs. Banks will need to show how decisions are made, how risks are mitigated, and how safeguards perform under pressure. As one senior executive told us during our research, “AI risk is no longer model risk. It’s also architectural.”

All of this means that keeping reliable documentation and maintaining end-to-end system visibility is becoming a baseline expectation. Banks will need explainability mechanisms that can keep up with increasingly complex AI systems. Pressure for more transparency on agentic AI use and human in the loop is likely to follow too.

Responsible AI is a Strategic Capability

Responsible AI has often been framed as a brake on progress – important for safety and reputation, but ultimately slowing things down. In practice, we’ve seen the opposite. The banks leading the charge on effective AI adoption know that RAI is a strategic enabler. That means that in addition to developing more use cases, scaling faster across business lines and hiring more talent, they are also ahead of the curve when it comes to RAI.

They also earn more trust, whether from customers, regulators or from their own leadership. That trust will grow more important as agentic systems begin to underpin services ranging from credit assessment to wealth management.

In this environment, responsibility is not a constraint. It is a foundation that allows banks to push further with AI, including finding new applications for agentic tools, while keeping risk in check.

____________________________________________________________________________________________________________________________________________________

The banking industry has made huge strides on the road towards AI adoption, and the arrival of Agentic AI – while creating new compliance and safety challenges – is nevertheless an opportunity that the leading AI-first banks will be keen to embrace.

Banks have already made significant investments in AI governance. What Agentic AI does is raise the bar, requiring them to ensure they’re able to demonstrate a deeper institutional understanding of autonomy, intent, and accountability – in essence, what the AI agent is doing and why.

The decisions being made today about AI governance will shape the next generation of financial services. Forward-thinking institutions are already preparing for that future. JPMorgan, Citigroup, Wells Fargo, UBS and Capital One have quietly assembled specialist teams focused on agentic AI. Others are hoping their existing frameworks will stretch far enough.

Opting for the latter approach is a big risk to take. Agentic AI is arriving faster than many expect. The challenges are real and so is the opportunity, but only for those who have already laid the groundwork via an RAI structure that lets them reap the benefits while maintaining trust, transparency and control.

  • Artificial Intelligence in FinTech

Author

Dan Brightmore

Published

30 October 2024

Estimated Read time

4Mins

Alexandra Mousavizadeh, CEO and Co-Founder of Evident, on how global banks are stepping up their AI comms in the face of growing investor scrutiny

In the big banks’ Q2 earning calls this year, a critical milestone was reached. For the first time, half of the 50 major banks we track in the Evident AI Index fielded questions from equity analysts concerning risks and opportunities specific to artificial intelligence (AI).

External scrutiny of the banks’ AI progress is steadily increasing. This is in line with the huge sums institutions have pumped into originating, developing, rolling out and scaling AI use cases. Banking leaders we’ve spoken to aren’t expecting to register meaningful bottom line business impacts from AI investments for at least another 24-36 months. Meanwhile, investors need satisfying that progress is being made, and that ROI will be forthcoming,

Against this backdrop, the way in which banks communicate around AI is becoming increasingly important.

Just 12 months ago, many banks were making only sporadic, broad-brush or conceptual references to AI. However, our recent AI Leadership Report revealed every bank in the Evident AI Index now has a communications and marketing strategy. Furthermore, the majority are referencing AI across multiple communications channels. These include annual reports, press releases, company LinkedIn posts, and media interviews.

Banks need to ‘talk the walk’

It’s not just the volume of comms, but the substance that is increasing. More banks are now willing to reveal specifics around internal use cases already in production. Moreover, they are sharing the results of these efforts and tangible information about what they are doing to scale artificial intelligence.

Last year, only 6 of 50 Index banks identified AI as a strategic priority in investor relations materials, and clearly described specific use cases in production alongside their ROI. This year, this number increased 2.5x to 15 banks.

These substantive communications help to reassure and placate investors. Furthermore, if a bank is perceived to be at the leading edge of AI adoption, the easier it becomes to attract, retain and inspire the talent needed to make organisation-wide transformation a reality

The C-Suite needs to engage in the AI debate

To achieve cut through in the debate, banks are mobilising their C-level leaders to publicise their ongoing efforts. They are setting out their vision for becoming AI-first organisations.

Of the 50 banks, 45 now have at least one C-Suite executive that has engaged on the topic of AI in external media in the last year. Furthermore, 15 of the 50 banks have two spokespeople on AI, while six banks (CaixaBank, DBS, Goldman Sachs, Intesa Sanpaolo, JPMorgan Chase, and NatWest) are engaging with four or more spokespeople across the Executive team.

As the primary owner of the bank’s strategic vision, the CEO should arguably lead from the front when it comes to market communications around AI. Meanwhile, JPMorgan Chase leads the pack across a host of AI maturity metrics. The efforts of Jamie Dimon to set the agenda and relentlessly beat the drum should not be understated.

Over the past 12 months, Dimon has been quoted in the media on AI topics around 10x more than any other banking chief. He continuously reaffirming his institution’s dominant position in the eyes of investors. This is an intentional, coordinated AI communications strategy that other banks would be well advised to follow.

Communicating tangible AI gains is vital as operational realities bite

Every potentially game-changing new technology follows a well-established hype cycle. In the case of AI, we’re now seeing the inflated expectations of Generative AI – arguably the most significant technology innovation of the past decade – being tempered by the realities (and difficulties) of operationalisation.

A recent memo from leading venture capital firm Sequoia Capital highlighted the elephant in the room. Namely, that the gap between what’s being spent to build out AI (mostly by tech companies) and the actual revenue realised by that investment has risen to $600 billion this year, up from $200 billion in September 2023. Investors are starting to probe for detail on when and where the ROI is coming from and, like Big Tech, the world’s leading banks will find it impossible to duck the difficult questions.

A delicate balance must be struck. Overpromising on AI today and underdelivering further down the line could prove disastrous. And yet, banking leaders know that in the highly contested race for artificial intelligence supremacy, failing to communicate their plans and progress also carries reputational risk.

Of the 50 banks we track, 38 announced at least one AI use case in the last year. Meanwhile, only 21 reported any outcomes associated with those use cases. And of those, only two – JPMorgan Chase and DBS – went so far as to specify their total actual realised $ return on AI spend last year.

With investor scrutiny only likely to intensify in the year ahead, individuals at the top of every bank must set forth a clear vision. They must establish frameworks for measuring the effectiveness of their AI efforts and the ROI being realised. And, crucially, provide consistent and clear communication every step of the way.

  • Artificial Intelligence in FinTech