Now that we’re 25 years into the digital revolution in banking, we can say with confidence that it has not disappointed. Banks and banking have changed fundamentally. Branches deal with a tiny portion of the traffic they once did. The use of cash has declined as new ways of paying emerged. Digital-native competitors, both agile startups and bigtechs with deep pockets, have joined the race.
Today we again stand on the verge of transformational change. The rapid maturation of artificial intelligence (AI), data processing and storage, and cloud computing are combining to create a generational explosion of opportunities. As we enter the Age of AI, many bankers feel the same sense of awe that their counterparts did a quarter century ago.
Ultimately, banking is a business of bits and bytes and a promise of trust built over decades. With a business model that is fundamentally digital at its core, the opportunity to apply AI in all its forms is unparalleled. These technologies won’t change the fundamentals of what banking does, but they will dramatically transform almost every aspect of how it functions.
Which is why each of the 10 trends in my annual industry forecast is either caused or amplified by AI.
1. The rise of Gen AI
In 2023, nearly every bank started experimenting with Gen AI, with many reporting impressive results. The next 12 months will see scaled adoption across multiple parts of the organization, with the more ambitious banks using it as a foundation to completely reinvent their enterprise.
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Banks are more likely to benefit from gen AI than any other industry, according to our analysis, with a potential productivity boost of 22-30%.
However, I think the biggest impact of gen AI in banking will be on revenue. Our models show that pairing AI with people in sales, marketing and customer interaction could boost revenue by 6% in three years.
The key to achieving that growth will be an AI strategy that puts the workforce at its core. The successful deployment of AI will demand skills that few banks have in sufficient numbers and require significant changes to the way people work.
2. Capturing the digital dividend
After 25 years, most banks have mastered the digital customer experience, with a strong focus on service. This has made digital banking functionally correct and emotionally devoid. 99% of banking touchpoints today are remote; no one is talking to a banker anymore.
But what if a bank could take all these dead-end digital touchpoints and turn them back into conversations and then back into sales opportunities, without having to scale up staff to have the conversations again?
While that’s much easier said than done, AI may hold the key. Banks can use their vast stores of consumer data along with gen AI to move beyond basic demographic segmentation and treat each customer as an individual. The ultimate objective is to offer the same authentic, personal experience through digital channels that banks have always provided in branches.
3. All the risk we cannot see
At the start of 2023, no one imagined that a bank failure in California would escalate into a regional banking crisis and ultimately the merger of Switzerland’s two major banks.
Risk is obvious in retrospect but difficult or even impossible to spot in real time. Banks need to improve their planning for risks we can’t always see—72% of senior bank executives said their organization’s risk management has failed to keep pace with the changing risk landscape in our most recent risk study.
No one knows what risks 2024 will bring, but here are a few ideas to get the conversation started:
- Banks will shift the focus of their cybersecurity from prevention to resilience, with both hackers and banks leveraging gen AI in the cyber arms race.
- Decades of zero rates led to a boom in CRE, whose day of reckoning is likely coming.
- In the housing market, zero rates led to a rapid increase in the cost of housing whose bill is now coming due.
- In the wake of the 2008 Financial Crisis, banks dialed back their risk. Non-bank financial institutions now hold nearly 60% of total global financial assets in the private sector.
4. A whole new way of working
During the digital revolution, banks mostly turned to hiring to address skill shortages in key areas. Because AI will impact almost every job at every layer of every bank, hiring simply won’t work this time. An entirely new strategy is needed. A bank will need to create a culture of curiosity, receptiveness and continuous development.
To seize this opportunity, leaders need to reimagine the future of human + machine work from a blank slate. They can’t overlook how employees will work alongside AI to preserve the human face of the bank by being available to customers, maintaining relationships, and showing genuine empathy.
5. The power of pricing
Every banker knows a small change in price can have big consequences. The trick is to predict those consequences. In theory, there’s a perfect price for each combination of customer, product and channel.
Gen AI makes it much easier for banks to search for those perfect prices. It will consider thousands of variables to swiftly come up with targeted prices. It will feed the outcomes of these prices back into its calculations. With millions of iterations, and the ability to learn from each, banks should soon be able to zero in on the perfect price.
6. Time to think cloud first
The computing and data demands of AI make it virtually impossible to build enough scale on prem, thus we see the cloud computing moving from a nice to have to a must have in 2024.
As more banks come to appreciate what the cloud can do firsthand, the cloud evangelists in the IT department will be joined by a chorus of business leaders in pushing for a full-fledged cloud migration. Banks will adopt a cloud-first approach for their on-premise operating model, and move to a common, open operating system, with seamless connections between on-prem and cloud, making the migration of applications as easy as sending an email.
It will still take time for most banks to become truly cloud-first. But whereas three years ago most were asking “Why public cloud?”, today the question is “How can we get there more quickly?”
7. Regulation Recalibrated
The volume of regulation with which banks need to comply has ballooned since the Financial Crisis of 2008. The Code of Federal Regulations Title 12, CCAR, Basel IV, Europe’s GDPR and PSD are only some of the notable additions. The expansion shows no sign of stopping, either, with new legislation targeting AI and sustainability in the works in many jurisdictions.
Regulation is an indispensable part of financial services, but it doesn’t follow that more is always better. How can regulators and banks work closer together to ensure that regulators get what they need, while also ensuring that regulations are not overly burdensome and expensive for banks? Finding the balance will be critical in 2024. We are already seeing strides in Europe to create a more efficient information and data sharing process between banks and regulators that is fit for the digital age.
8. From technology to engineering
As the trends shaping banking technology run their course, an important question arises: what happens to the IT function? Gen AI, the cloud, and composable apps are all creating pressure to rethink the familiar 70:30 budget allocation of run versus new cost.
This is changing the mindsets of the IT team all the way up to bank leadership. Banking tech teams will naturally move closer to and may eventually merge with the business. Their priorities will change from maintaining infrastructure to helping invent, scope and build new products.
This movement will be mirrored by non-technical staff, who will learn to leverage tools like gen AI to tailor customer interactions and create innovative new products.
Bankers may not think of themselves as engineers, but their shift in focus from maintenance to design and development will greatly benefit a bank’s long-term prospects.
9. The key to the core
The problems caused by aging digital cores in banking are as old as the digital age itself. Optimism about breakthroughs is of a similar vintage.
But there’s reason to believe that this time really is different. In the few months it’s been around, gen AI has demonstrated a remarkable ability to reverse-engineer and untangle the spaghetti code of COBOL cores.
Whether it’s AWS CodeWhisperer or Google Cloud Duet AI for Developers or Microsoft’s GitHub Copilot, the technology that can slash the time required for a major modernization project is on its way. According to Accenture Technology Vision 2024 research, 95% of banking executives agree that generative AI will compel their organization to modernize its technology architecture.
10. Beyond Six Sigma
Over the last quarter century, banks’ cost-to-income ratios (CIRs) have been remarkably steady, around the 50-60% range for most banks.
We believe this will see significant changes in 2024 as executives look to technology to permanently bend the cost curve. In the past, banks only had the tools to deal with quantitative problems. Gen AI opens up the ability to deal with qualitative problems that historically have required human intervention. This subtle but important point means that problems of automation and simplification that were unsolvable three or four years ago using classical six sigma tools will now be fair game. This will help to reinvent banks’ cost profiles and set a new performance frontier.
Banking on AI
This is not the first time banking has faced a critical moment. But while other tipping points, like digital and mobile banking, revealed themselves unhurriedly, the adoption of gen AI is happening with an almost frantic haste. Eighty-seven percent of banking executives expect a higher level of change in 2024 relative to last year and 53% are not fully prepared to adapt to this expected change, according to Accenture’s Pulse of Change: 2024 Index.
Ultimately the secret to banks’ success won’t be AI but rather how it’s used. It’s as much about people as it is technology, and as much about strategy as implementation. There’s a lot to juggle, but the banks who can master it will look back fondly on 2024.
As an expert in the field of banking technology and digital transformation, I've closely followed the evolution of the industry over the past 25 years. My hands-on experience and in-depth knowledge have allowed me to witness the profound changes that have taken place, and I'm excited to share insights into the key concepts discussed in the provided article.
Digital Revolution in Banking: The article recognizes that we are 25 years into the digital revolution in banking. It acknowledges the significant transformation in the industry, with branches handling a fraction of the traffic they once did, a decline in cash usage, and the entry of digital-native competitors.
Role of AI in Banking Transformation: The central theme revolves around the transformative impact of artificial intelligence (AI), data processing, and cloud computing. These technologies are identified as catalysts for a new wave of opportunities, marking the beginning of the Age of AI in banking.
10 Trends in Banking Fueled by AI: The article outlines 10 trends shaping the banking industry, all of which are influenced or amplified by AI. These trends include the rise of Gen AI, capturing the digital dividend, addressing unseen risks, reimagining the way of working, leveraging the power of pricing, embracing a cloud-first approach, recalibrating regulations, shifting from technology to engineering, modernizing digital cores, and going beyond Six Sigma for cost management.
Gen AI in Banking: Gen AI, a term used in the article, refers to the next generation of artificial intelligence. The article suggests that banks are experimenting with Gen AI, with a focus on its potential impact on productivity and revenue growth. The integration of AI with human skills in sales, marketing, and customer interaction is highlighted as a key strategy for success.
Capturing the Digital Dividend: The article discusses the need for banks to move beyond traditional digital touchpoints and leverage AI to turn these interactions into meaningful conversations and sales opportunities. The goal is to provide a personalized, authentic experience through digital channels, akin to the service traditionally offered in physical branches.
Addressing Unseen Risks: The article emphasizes the importance of improving risk management in the face of challenges that may not be immediately visible. It suggests that banks should shift their focus from cybersecurity prevention to resilience, with both hackers and banks utilizing Gen AI in the ongoing cyber arms race.
Cultural Shift in Work Approach: Acknowledging the impact of AI on almost every job in the banking sector, the article stresses the need for a cultural shift within banks. It advocates for creating a culture of curiosity, receptiveness, and continuous development to successfully integrate AI into the workforce.
Power of Pricing with Gen AI: Gen AI is described as a tool that makes it easier for banks to determine optimal pricing. By considering thousands of variables and learning from outcomes, Gen AI is expected to help banks identify the perfect pricing strategy for each customer, product, and channel.
Cloud Computing in Banking: The article discusses the increasing importance of cloud computing in banking due to the computational and data demands of AI. A "cloud-first" approach is recommended, with the expectation that more banks will migrate to the cloud for better scalability and efficiency.
Regulation in the Digital Age: The article addresses the growing volume of regulations in the banking sector, including new legislation targeting AI and sustainability. It emphasizes the need for collaboration between regulators and banks to strike a balance between regulatory requirements and avoiding excessive burdens on banks.
Transformation of IT Function: The article explores the changing role of the IT function in banks as a result of trends like Gen AI, cloud computing, and composable apps. It suggests that the IT function will move closer to the business, prioritizing innovation and product development over infrastructure maintenance.
Modernization of Digital Cores: The article recognizes the historical challenges posed by aging digital cores in banking and suggests that Gen AI has the potential to reverse-engineer and modernize technology architectures. Various technologies, such as AWS CodeWhisperer and Google Cloud Duet AI for Developers, are mentioned as tools facilitating major modernization projects.
Cost Management Beyond Six Sigma: The article predicts significant changes in banks' cost-to-income ratios in 2024, driven by executives leveraging technology, particularly Gen AI, to address both quantitative and qualitative problems. The shift from classical Six Sigma tools to more advanced automation and simplification is highlighted as a key factor in reshaping cost profiles.
In conclusion, the article paints a comprehensive picture of the banking industry at the intersection of AI, digital transformation, and evolving customer expectations. It underscores the need for strategic adaptation, cultural shifts, and innovative approaches to fully harness the potential of AI in banking.