BFSI’s fast track to GenAI value hinges on resolving five crucial debts

Generative AI (GenAI) applications such as ChatGPT and other large language models (LLMs) have the potential to revolutionize the BFSI (banking, financial services, and insurance) industry. With the adoption of these technologies, industry leaders face the challenge of balancing compliance with innovation, managing the cultural shifts necessary for adoption, and ensuring sustainable value creation.

To evaluate the industry’s preparedness for a GenAI-powered future, HFS, in collaboration with Publicis Sapient, co-hosted an industry roundtable in New York with executive leaders from companies including Chubb, New York Life, U.S. Bank, Wells Fargo, UBS, BNY Mellon, JPMorgan, Chase, Citi, and Deutsche Bank (see Exhibit 1). The discussions highlighted that while GenAI’s value is within reach, BFSI organizations must address five critical debts—technology, culture, skills, process, and data—to unlock its full potential and achieve sustainable value creation.

Exhibit 1: A BFSI brain trust assembled to discuss how to achieve sustained value with GenAI

Source: HFS Research, 2024

The financial services sector, while nascent in GenAI adoption, remains optimistic about the time to deliver value

Like many industries today, the financial services sector is just beginning its journey with GenAI, cautiously exploring how to incorporate this technology into its operations and making significant investments in its potential. A recent HFS study revealed that a mere 6% of BFSI organizations are pioneers in GenAI adoption and investments (see Exhibit 2). Echoing these findings, most of our roundtable attendees fell into either the “fast-follower” or “wait-and-watch” categories.

Exhibit 2: GenAI is a smoldering platform, not a burning one, within financial services

*Deniers include respondents who were excluded from the remainder of the study
N = 199 BFSI leaders across the Global 2000
Source: HFS Research, 2024

Despite being in the early stages of GenAI adoption, attendees expressed strong optimism about its potential to deliver significant value and the time required to get there. Productivity and improved customer experience topped the business benefits of GenAI. The average time to realize these benefits is projected at just 1.3 years (see Exhibit 3). The consensus among the attendees was that this time frame is achievable. However, they acknowledged that scaling these solutions might take longer, with estimates spanning two to five years.

Exhibit 3: The average time to realize the top GenAI benefits is projected at 1.3 years

N = 162 BFSI leaders across the global 2000
Source: HFS Research, 2024

Achieving GenAI value heavily depends on having the right foundations in place

The optimism for GenAI’s possibilities and its short time to value come with a critical caveat: you must have the right foundations. These foundations extend far beyond the technology itself and speak to solid data management systems and practices, a resilient technological infrastructure, governance frameworks, and a skilled workforce optimized for change.

However, the necessity of these foundations also reveals what HFS refers to as the five debts—culture, data, technology, process, and skills—hindering progress for many leaders in the BFSI space. As a delegate from a global bank stated, “You must pay these debts to make progress with innovations such as GenAI.”

Debt one: As one of the first industries to innovate, financial services has amassed huge technical debt

The financial services industry has a long history of embracing technological advancements and being early adopters. It has progressed significantly, continuously evolving from the early days of computerized banking in the 1950s to digital transformations driven by the internet and mobile technologies in the 2000s. However, by adopting many new technologies, the industry has amassed an intricate web of legacy systems and technologies, compounded by M&A, siloed lines of business, and CIO tenures, which average about four years.

Delegates at the roundtable discussion acknowledged the barriers to adopting newer technologies but pointed out GenAI’s potential to reduce technical debt. By automating code refactoring, optimizing legacy systems, and streamlining data management processes, GenAI can help financial institutions modernize their technology stack more efficiently and effectively.

Sheldon Monteiro, EVP and chief product officer of Publicis Sapient, noted, “This sector is grappling with decades-old legacy technology, which brings complexity and significant costs for updates to mitigate business risks. Embracing legacy modernization superpowered with GenAI tools enables us to upgrade rapidly, with reduced costs and enhanced quality.”

Debts two and three: Addressing culture and skills debt requires a shift from merely seeking “AI talent” to fostering an “AI mindset”

One of the roundtable’s most passionate discussions concerned the concept of culture debt, which HFS defines as the willingness to change to support innovation and the skills required to harness it. We’ve clubbed skills and culture debt together, as humans and their associated skills ultimately dictate how far the pendulum of culture change can swing. These debts emerge when organizations fail to adapt their cultural and skills development to match the pace of technological advancement, creating resistance to change and hindering progress. This challenge is particularly pronounced in financial services—an industry steeped in tradition and stringent regulations and often falls back on inflexible systems and hard-coded processes, using regulatory scrutiny as an excuse for doing things the same way it has for decades.

Participants emphasized that moving beyond the search for “AI talent” to fostering an “AI mindset” is crucial for overcoming culture debt and skills debt. As a managing director of a major global bank aptly noted, “In finance, the potential of GenAI is vast, but without a shift in mindset, we can’t fully capitalize on these opportunities.”

Offer your people the opportunity to upskill—or they will go somewhere that does

Fostering an AI mindset requires significant investments in change management and upskilling programs. As a transformation lead for a prominent American bank put it, “Upskill the people, or they will become obsolete. And if upskilling is not available, they will seek employment elsewhere.”

This stark reality underscores the urgency of equipping existing employees with the skills they need to work effectively with GenAI technologies. Financial institutions must implement ongoing training initiatives, create learning groups, and establish support systems to ensure employees are not just users but champions of AI.

Debt four: Balancing the “Navy vs. Pirate” mentality is essential for addressing process debt

Process debt, which refers to outdated workflows –literally, the prescribed ways of getting work done—was vividly captured through an interesting metaphor: the “navy vs. pirate” dynamic (see Exhibit 4), inspired by a Steve Jobs quote: “It’s more fun to be a pirate than to join the navy.” Traditional financial institutions are likened to the navy—structured and disciplined, focused on maintaining order and compliance. While essential for regulatory adherence, this structured approach often leads to bureaucratic inertia and stifles innovation.

On the other hand, the pirate approach is more agile and flexible. It is characterized by taking calculated risks, embracing innovation, and breaking away from rigid processes. Pirates thrive on speed, adaptability, and unconventional thinking, which are crucial for driving innovation and overcoming process debt.

Participants stressed the importance of balancing the navy’s structured approach with the pirates’ daring ingenuity. This balance is crucial for addressing process debt and creating an environment conducive to innovation. The head of enterprise operations and services for a major life insurance company emphasized the need for a balanced approach: “Our processes need to be agile enough to allow for rapid innovation while maintaining compliance.”

Exhibit 4: BFSI enterprises should strive for a balance between the navy and pirate approaches to GenAI adoption

Source: HFS Research, 2024

Debt five: Without data quality or governance, GenAI’s potential is severely hindered

Finally, in this world of debt, poor data quality, fragmented data sources, and inadequate data governance are significant barriers to progress. Participants stressed that addressing data debt is crucial for enabling effective GenAI implementations. Clean, well-organized, and accessible data is the backbone of any AI initiative.

A CIO of a major US bank underscored this issue’s importance: “Without high-quality data, our AI models are only as good as our worst data point.” Financial institutions must invest in data modernization efforts such as data cleansing, integration, and establishing robust data governance frameworks. Effective data management also involves breaking down data silos and creating a unified data ecosystem that enables seamless data flow across the organization. The good news is that while GenAI may be a new technology to assimilate and understand, it’s part of the broader AI canon; thus, many existing applied AI governance protocols are fit for purpose.

The Bottom Line: The time to value for GenAI is near. The BFSI industry’s GenAI-driven revolution hinges on overcoming technology, culture, skills, process, and data debts to balance compliance with innovation and achieve rapid, sustainable value.

Okay, BFSI sector, it’s time to pay your debts—tech, culture, skills, process, and data—so you can embrace and activate GenAI’s potential value. Your time to value is directly linked to establishing effective foundations to enable progress and, ultimately, scale. Finding the right balance between the navy and pirate approaches to GenAI and innovation adoption can whet the appetite for change.