Banks Adopt AI for Modern Transformation
Dave Murphy, Head of Financial Services – EMEA & APAC at Publicis Sapient, highlights how banks and businesses are leveraging AI for modern transformation. With nearly 30 years at Sapient, he draws parallels between today’s AI shift and the transformative impact of the World Wide Web in the early ‘90s, noting a similar fundamental rethink in financial services.
Founded in the early 1990s, Publicis Sapient initially positioned itself as a technology consultant to businesses. Today, it operates in 72 countries, employing over 20,000 people, and helps clients handle technological advancements.
Murphy joined the company in 1997, during a key era for technology development. The introduction of the World Wide Web in the early ‘90s not only transformed businesses but also forced them to rethink operations and customer engagement. This shift, according to Murphy, mirrors the current impact of agentic and generative AI in financial services.
“It wasn’t just the introduction of the World Wide Web itself but the moment companies and corporations started to adopt it that fundamentally changed the way they engaged their customers and thought about their operations,” Murphy explains. This shift eliminated barriers, allowing customers direct interaction with back-office systems.
The Big Banking Shift
As digital services expanded, their availability to paper-native businesses grew, driven by tech giants like Google. This democratization of technology accelerated digital adoption across industries, including banking. Murphy notes that this shift is particularly striking for institutions with histories spanning 350 years, which have had to adapt rapidly.
“Now, if you look at any high street bank or financial institution, they are fundamentally digital businesses,” Murphy observes. Between 2014 and 2015, digital adoption among high street bank customers was only 35% to 40%. Today, it’s closer to 80% to 90%, driven by collaborative efforts and socio-economic events like the pandemic, which forced businesses online.
“Previously you were protected, because even if there were huge technological shifts happening in the industry, you could still serve your customers through human touch, the branch or the telephone,” Murphy warns. “But now that you’re a digital business, as those technologies change, you have to change with them.”
AI: A Double-Sided Digital Coin
Banks are turning to AI for everything from conversational customer service to end-to-end transactions. Murphy divides AI into two dimensions: historical, akin to machine learning, and agentic. While machine learning drives personalization through data, agentic AI, like chatbots, is more recent and less predictable.
“There’s a lot of thinking still needed in the agentic space, because it isn’t always 100% accurate – there’s a non-deterministic element to it,” Murphy says. Banks are starting from the back office, ensuring systems work before deploying them customer-facing.
For instance, Publicis Sapient began implementing machine learning platforms for high street banks around 2016 to 2017, enabling data scientists to refine these systems. AI adoption remains gradual, with banks prioritizing guardrails and platforms to ensure safe integration.
Fintechs, meanwhile, face choices in adopting AI. While they have a more hands-on approach than banks, guidance remains key. Using gen AI as an autocomplete tool can improve workflows by up to 15%, but rethinking processes entirely with agentic AI offers greater potential. “To do that, you need to think hard about the workflow, because what matters most in harnessing the power of agentic AI, beyond the large language models themselves, is the context you provide,” Murphy emphasizes. “That will typically only give you around a 15% improvement. Fintechs that get that context right for whatever problem they’re solving… will be able to offer real added value.”
This foundational work has paved the way for more advanced AI applications today.
Fintechs’ AI Adoption Strategies
Fintechs face choices in adopting AI, with a more hands-on approach than banks. Guidance is key to ensure successful implementation. While gen AI can offer incremental improvements, agentic AI promises transformative changes by rethinking workflows entirely.
