NatWest, J.P.Morgan and Wells Fargo: Is it the AI or IA Era?

Artificial intelligence has made global headlines as the technology has been adapted to create and encourage businesses in their development ventures. 

Financial suites worldwide have experienced a shift in the way that operations are conceived, ranging from increased efficiency to convenience. 

Some use of AI has even encouraged the use of leaderboards at major companies such as Amazon, as reported by Business Insider. 

This is in part due to the entry of an era defined by compressed margins, shifting macroeconomic headwinds, unprecedented data volumes and back-office friction, which has become the ultimate tax on corporate growth. 

For the world's largest financial institutions, the operational mandate is no longer merely about cost reduction; it is about agility, speed and risk mitigation at scale.

So where does IA come in? Not intelligence artificial, Intelligent Automation (IA) has become the choice for busy C-suite staff who are moving beyond simple automation. It combines the efficiency of AI with global enterprise giants that are pioneering the era of IA.

First, a look at what we’ve been using so far.

It’s 2016: companies are gradually beginning to adopt robotic process automation (RPA) to enable smoother production. There is still some hesitancy, as trust hasn’t fully been adopted into the process. 

McKinsey estimated at the time that RPA was promising new development in business automation – offering a potential ROI of 30-200%. 

Posing such a huge opportunity, businesses couldn't ignore. Lower costs and an alternative way to streamline tasks, it allowed humans to focus on the explicitly human aspect of their job without the lengthy manual burden that tasks are normally accompanied by. 

Moving forward a few years, the popularity of RPA was hard to ignore: everybody was using it. And at scale. 

Moving beyond the simple task of automation allowed room for additions and improvements; namely, the introduction of AI, machine learning (ML) and natural language processing (NLP). 

IA has emerged as a powerhouse, influencing everything from executive strategy to daily financial workflows. 

This shift is part of a broader technological evolution that has redefined operational standards.

While RPA paved the way, IA now offers sophisticated solutions across various business functions. Despite the rise of more complex systems, these tools remain essential for optimising several key areas:

NatWest and Sustainability

Major UK bank NatWest is reducing its Scope 1 and Scope 2 location-based emissions by 50% as part of its ongoing commitment to achieve net zero for its operational value chain by 2050. 

As part of this mission, the bank took stock of its operations and realised that software development was contributing to Scope 1 and Scope 2 emissions. Immediately developing principles and guidelines, the commercial and retail bank created toolkits aimed at reducing energy costs associated with software testing. 

By bringing automation to the table, software testing, which includes checking quality and functionality before launch, it saw an increase in efficiency as well as a positive step towards its net-zero goal.

Test environment energy was cut by up to 85% as execution time decreased. Similarly, script development time was halved due to the automation process. 

Maintenance time decreased by 40%, also contributing to a 40% decrease in test environment energy. 

In 2023, NatWest won the Team of the Year at the UK National Sustainability Awards. 

JPMorgan Chase and Efficiency

In an era where operational efficiency dictates corporate survival, J.P. Morgan is positioning accounts payable (AP) automation as a strategic necessity rather than a mere back-office upgrade.

According to insights from the banking giant, traditional, paper-laden finance workflows are increasingly giving way to IA.

The financial dividends are clear. By digitising the end-to-end payment lifecycle – from optical character recognition data capture to three-way reconciliation – organisations drastically mitigate human error, eliminate duplicate payments and strengthen fraud defences. 

Crucially, J.P. Morgan highlights that this optimisation does not just yield cost savings and early-payment discounts; it strategically elevates the finance function. 

By liberating AP teams from manual bottlenecks, leaders can repurpose human capital toward high-value analytics, vendor negotiations and forward-looking capital management.

A prime example, the banking goliath recently invested in a robot for check processing.

Michelle Conklin, Head of Receivables and Public Sector, J.P. Morgan Payments, notes: “By investing in robotic and AI technology to improve our lockbox operations, we are automating the most labour-intensive tasks of the process, freeing our team to focus on more complex, higher-value decision making. 

“The result is a faster, more secure and smarter receivables process that gives our clients both agility and peace of mind.”

Wells Fargo and Productivity

The front line of this bank’s strategy is Fargo, a mobile virtual assistant that has surpassed one billion customer interactions. By utilising conversational technology trained on massive conversation pools, the tool handles everyday queries instantly – saving millions of users from hold times and app navigation, with future iterations slated to deliver highly personalised financial counselling.

Yet the true structural disruption is happening behind the teller line.

With tools like the Intelligent Banker Book, Wells Fargo uses smart data engines to instantly summarise client history and prep licensed bankers for meetings, turning hours of administrative homework into real-time strategy.

Similar automated, single-workflows are optimising customer service desks, slashing account-opening timelines, and accelerating how the bank’s own engineers deploy software. 

Wells Fargo is making a definitive statement: in modern finance, intelligent tech is no longer a luxury feature; it is the engine.

“If you look at our strategy, it’s pretty simple: to fundamentally transform the way the bank operates,” notes Saul Van Beurden, Wells Fargo’s Head of AI and Co-CEO of Consumer Banking & Lending.

“This means making our people – especially our bankers – more productive, improving the customer experience and removing manual work.”

Top 10 Vendors 

1. Microsoft (Power Automate): Out-of-the-box Windows 11 integration that turns standard enterprise workflows into automated cloud processes without requiring new vendor friction.

2. IBM (Watsonx Automation / IBM RPA): IBM excels at deep architectural orchestration that combines traditional bot automation with Watsonx multi-agent AI for heavy data governance.

3. Salesforce (Mulesoft + Flow): It is the gold standard for connecting legacy systems and unorganised data streams via highly customisable API connections.

4. UiPath: An unmatched end-to-end automation cycle featuring predictive process mining, automated “self-healing” bots and a massive global developer community.

5. ServiceNow: A unified platform that expertly connects disparate IT systems and employee workflows into smooth, cross-departmental operations. 

6. Pegasystems: Complex business process rules engine paired with real-time AI decisioning, designed specifically for high-volume transactions in banking and insurance.

7. Automation Anywhere: A cloud-native setup utilising an advanced AI Agent Studio that allows teams to build and scale web-based digital workers rapidly.

8.SS&C Blue Prism: A rigid, object-oriented design built for extreme operational stability and ironclad governance in strict compliance environments

9. Appian: A premier low-code environment built to help business users construct data-heavy, automated applications up to ten times faster than normal coding.

10. Workato: A smooth low-code iPaaS framework that acts as a single canvas for data integration, app connections and modern workflow automation.

Intelligent automation in financial services has entered a mature phase, shifting from isolated, rule-based software toward enterprise-wide Agentic AI. According to data from Capgemini’s World Cloud Report 2026, while 87% of financial firms leverage traditional automation, only 10% have scaled these fully autonomous AI agents – marking the industry's newest competitive frontier.

Unlike simple bots, these modern agents possess the capability to reason, interpret context and act independently across complex cloud workflows.

Another prime real-world example of this in the second quarter of 2026 is NatWest Group's comprehensive partnership with Cleareye.ai. The bank is deploying an intelligent automation platform called ClearTrade to completely overhaul its back-office trade finance.

The system extracts and categorises data from unstructured, multi-format documentation and runs automated financial crime screenings alongside Trade-Based Money Laundering (TBML) checks.

Simultaneously, major banking institutions like Lloyds Banking Group are rolling out massive enterprise-scale automation suites (such as Microsoft's E7 platform).

This scales journey-specific autonomous agents designed to automatically handle routine system interactions, drastically reducing administrative workloads. These integrated data ecosystems are transforming complex risk modelling, fraud detection, and Know Your Customer (KYC) compliance – enabling institutions to expand client approval rates while maintaining a highly secure risk profile.