Global Banking Annual Review 2026: Why precision, not heft, defines the future of banking

It would be easy to think that the last several years were a mediocre year in the banking sector considering the headlines of layoffs and concerns of the slow down of the economy. As a matter of fact, banks have made record after record without much prior notice or hue and cry.

This report is a joint endeavor, by Darius Imregun, Ido Segev, Jon Steitz, Klaus Dallerup, Marti Riba, Miklos Dietz, Pradip Patiath, and Saptarshi Ganguly and is the opinion of the Financial Services Practice. Money that is mediated by the global banking system, whether by traditional banks or nonbank providers, increased by 122 trillion, or roughly 40 per cent, driven by the world household and institution wealth. Revenues of banks that survived risk cost were a record 5.5 trillion in 2024 which contributed to the high net income in the sector, the highest value ever of any industry. Nonetheless, capital markets are yet to be persuaded of the potential value creation by banks: The performance of the banking sector is mostly 70 percent lower than the average of all other sectors.

Why the disconnect?

The recent performance of the banks has been supported by good conditions, namely, peak in international wealth cycle, exceptionally high revenue margins due to increased interest rates, and low risk costs, yet these tail winds are known to be fading. ROE is barely paying off the cost of capital. The price to book ratio in the industry is 1 which is 67 percent lower than that of other industries.

After the banking sector surged over the past few years, there is a possibility of a return to the mean, reduced growth and an increasing pressure on profitability. In order to intercept the new growth curve, banks need to change their pattern of taking advantage of traditional time worn methods to value-creating, more challenging strategies.

Not only will the probable reversion to the mean be supported by macroeconomic factors, including the changes in interest rate and demographics but also by the disruption induced by AI development, the increase in competition by the nonbank entities, including fintechs, and the change in customer expectations. The banks need to move beyond traditional methods they have used over time to focus on precision strategies creating value in more demanding environments in order to capture the next growth curve.

The current strategies have failed

Over 600 billion dollars per year are used by banks on technology yet the productivity is low. General segmentation of customers has not paid off. In capital efficiency, there is no sufficiency of sweeping reallocations and broad balance sheet adjustments. Running after scale by M&A deals and nothing more has not paid off. Banks require new solutions in order to prosper. The strategies that were macro-oriented and scale-driven once guaranteed resilience but no more. The key distinguishing factor is precision, which distinguishes between the front runners and the back movers in the banking industry and brings a change in the curve of industry performance.

The precision toolbox

The precision toolbox, which applies to both large and small banks, transforms strategy in four key areas:

• Technology: becoming surgical in investments in technologies with the most impact--even in agentic and gen AI--scaling back investments that do not enhance workflows, customer experience, or business models
• The new consumer: no longer broad segmentation, but individualization (a consumer segment of one), offering hyperpersonalized, data-driven access to products and services that endears itself to customers in an age of diminished loyalty
• Capital efficiency: no longer doing massive reassignments, but doing millions of small, data-driven optimizations

In 2024, the banking sector continued to take off. The pace of increase of funds circulating in the banking system has always been at a higher rate than the general economic growth. Funds intermediated by the global banking system, conventional banks but also nonbank providers, increased at a pace much higher than the global GDP (7.0 percent a year, on average, compared to 4.8 percent). This tendency was caused by high interest rates, savings during the COVID-19 pandemic caused by government stimulus and altering consumption habits and the strong investment activity, which channeled even more money via banks and asset managers, adding to the volume of funds that they intermediate. During the same time, retail fund managed by financial institutions was growing 6.0 percent per annum and institutional fund was growing 7.7 percent per annum. Banks in the banking system grew fastest due to the capitalisation of the banking system in the form of funds, which grew by 17.2 percent per annum, an indication of the increasing strength of the role of the private capital in the global markets. The global wealth of households and institutions is a subgroup of intermediated funds that have been on an increasing trend which has contributed to the growth of revenue in the banking industry. During the last five years, world wealth has been more than 350 percent of the nominal GDP. Besides, the distributable capital or free cash flow to equity, created by the banks in 2021-24, is enormous compared to the sum of other industries. Shareholders obtained a huge share, yet the banks have accumulated historically large reserves as possible investments and acquisitions.

Have banks prepared for the future?

The last three years have been extremely robust of banks, yet have they taken the best of the times to remodel the windfall into ensuring that their business models are geared up to the future? Capital market opinion indicates that perhaps not all banks have so done. Though the recent years have been the best in the history of the banks, the valuation difference between the banking and other industries still exist. Banks are not convinced that their highs are sustainable to markets. Researching the situation are macroeconomic dynamics, such as falling interest rates, changing technology and consumer behavior, and the continuous bleeding of juicy profit pools by fintechs, private credit, and wealth managers. All these may lead to a situation where the ROE of banks would be less than the cost of equity in most markets.

Banks, which are already struggling with declining revenues, are desperately in need of productivity enhancements, and AI may offer it. Nonetheless, AI is two-sided, and it is not only likely to introduce cost savings but also disruption. The AI agentic in specific can transform the banking industry radically, and not always to the advantage of the industry overall. It may generate efficiencies and new customer value never seen before, yet unless the banks act decisively to adapt to it, it is going to cannibalize the traditional pools of profits.

Since these are still infantile stages of agentic and gen AI, it is only now that surgical precision is necessary to find out where these technologies can actually make money, and not to invest heavily in them due to the FOMO.

AI impact scenarios

Two important factors will determine the size of the impact of AI on banking, namely, how much banks can become fully agentic and how much they can radically reduce the cost of operations, and how much customers use AI to deal with their financial functions. There are nine scenarios that are described with the aid of our analysis. In the middle case, as we calculate, a 30 percent probability that the scenario will occur, AI radically alters the banking business, as well as consumer behavior. Other situations seem to be less probable. As an illustration, scenario C3, where consumers delegate the entire financial decision-making process to AI agents and the banks reduce their staff numbers to drastic levels, is conditioned by two unrealistic aspects that cannot happen in the medium run: the acceptance of agents acting autonomously on behalf of customers and the capacity of AI to make decisions at a senior level. Nevertheless, although it might be necessary that consumers should also provide a final approval to transactions that are made by AI agents, i.e., they are not completely autonomous, this model may lead to significant disruption of the industry, as in our central case. The time of disruption is not certain. However, we believe that we will have a break out agentic business model within the next three to five years that will bring a tipping point.

Cost savings and profit erosion

With AI being deployed in the banking sector, it might lead to the gross degradation of up to 70 percent in some cost areas. However, since this savings will partially be neutralized by the increasing cost of technology, we forecast that the overall impact on the aggregate cost base of banks will be a 15 to 20 percent reduction. These savings will have an effect, but it will not be long lived. Similar to the previous advancements, the competition will tend to dilute the profits of banks and most of the benefits will be passed to customers with time. In the long run, AI will cause the decline in bank profitability when consumers will begin actively utilizing AI agents to rationalize their finances (such as by automatically transferring deposits to better paying accounts), this would make customers less inert and transform the industry economics.

Deposit disruption

The deposits and credit card lending would be among the areas where agentic AI can cause disruption through cutting inertia. It is now possible to find 23 trillion of the world total of 70 trillion of consumer deposits in the checking accounts with virtually zero rates, and what is left is in the accounts which usually pay relatively low savings rates. Assuming that only 5-10 percent of checking balances shifted to the highest rates of the market, a step AI agents may trigger, this would cut the overall deposit profit of the banking industry by 20 percent or more.

It is sufficient to make average returns lower than the cost of capital. The impacts will not be equally experienced. Using their advantage, AI pioneers may realize a four percentage-point rise in return on tangible equity (ROTE), by reinventing models and seizing value. On the other hand, slow movers will be likely to experience reduced profits in the long run.

AI is disrupting the relationship between customers and banks, building demands on smooth, hyperpersonalized experiences particularly in younger generations. Customers are more digital, less loyal and more conscious in their selection of financial services providers.

The consumer decision journey

Once a consumer is aroused to seek a financial product, the consumer decision journey (CDJ) will usually start with the initial consideration set (ICS), or the first set of banks the consumer considers. The consumer then proceeds to active evaluation where the banks may either be added or eliminated. This trip may also include a loop of loyalty where customers purchase new products with the bank without looking at other alternatives but that is much less probable nowadays. There is a transformation of the CDJ of banking purchases. In the US, a mere 4 percent of new credit card holders select their current credit card provider without previously comparing it to others, compared to 10 percent in 2018. US checking accounts are even more impressive, with loyalty loop openings accounting 4 percent down to 25 percent in 2018. Rather, customers attach more weight to the initial few banks they look into during their buying process, which implies that any bank able to develop awareness appropriately will be able to get into the ICS and be put in the right position to succeed.

Keys to entering the initial consideration set

Banks most likely to fall into the ICS tend to be excellent in four major aspects:

• becoming highly aware, e.g. by spending media resources where it will have the most effect
• inciting action, e.g. by using precision to multiply word of mouth recommendations, e.g. data-driven referral programs
• matching message to what customers value
• eliciting preference through primacy The fact that a bank is the primary bank of a consumer (that is, the bank has deposited the majority of their money or has been involved in the majority of their payment activities) makes it three to four times more probable that the bank will be included in the ICS to offer more products, as well as, cross-sell products, than the competitor. The consumer decision journey is also being further disrupted by other forms of businesses including aggregators, gen AI platforms, intermediaries, and embedded-finance providers, which also doesn't help the reduction in loyalty.

Gen AI adoption by consumers

Over a half of customers are now using gen AI tools, and they want their banks to provide them too. Almost everyone claims that they would ultimately change their bank supplier in case their current bank was not able to match this technological change. AI and mobile have stimulated the consumer transformation. Gen AI has already been used by the majority of consumers and they want their banks to offer them also. The number of consumers who are using gen AI tools has increased to more than half, and a large portion of consumers depend on a model like ChatGPT to assist them in managing their financial needs. Nevertheless, they are also keen on banks to provide such services: The vast majority of users would like their existing bank to provide AI solutions, and almost all of them would eventually move over to another provider in case their existing bank was not able to keep up with this technological change.

Mobile banking dominance

Banking has turned mobile into the most popular banking channel and its importance will increase with the integration of gen AI in the financial services. The value provided by banks through mobile already by customers that use the mobile is much higher, which proves the strategic nature of this channel. Nevertheless, branches are still important in most geographies especially with operations like opening of checking accounts. The next level of customer engagement will be banks that combine AI-driven insights and mobile-first, personal experience, with digital ease and human connection. Banks that want to succeed must captivate mind share with consumers, adopt mobile as the pathway to consumer engagement and integrate AI into customer experiences before challengers take the lead. Precision may enable banks to better cater to the less committed, more digital modern customer, who desires hyperpersonalized experiences and mobile-first integrated experiences and journeys, like being able to begin a task on mobile and finish at a branch without repeating the reason to them. Banks which can respond to these changes and present exactly what their customers desire will be in a good position to succeed. In case of the non-reaction of incumbents, there will be a sudden increase in the number of new waves of AI fintechs to seal the gap.

The next growth curve of the banking industry will not be determined by the scale but by precision. Leaders who incorporate accuracy in their plans encompassing technologies, customer interaction, capital deployment, and mergers and acquisitions will gain outsize rewards whereas slow movers who remain attached to the previous playbook will fall. Precision is not only a strategy in this new era, but also the path to profitable growth. Provided that banks are able to put the precision toolbox to good use the huge valuation gap in the sector may start to bridge, leaving the banks that do it right, with a real value creation.

Darius Imregun is a partner in the Boston office, where Saptarshi Ganguly, Ido Segev, and Saptarshi Ganguly are senior partners. Jon Steitz is a senior partner based in the Bay Area office, Klaus Dallerup is a senior partner based in the Copenhagen office, Marti Riba is a partner based in the Barcelona office and Miklos Dietz is a senior partner based in the Vancouver office. Pradip Patiath is the senior partner of the Miami office with Suhas Gudhe working as an associate partner in the same office, Michael Kirchner as an associate partner in the New York office and Valeria Laszlo as a senior capabilities and insights expert in the Budapest office.

Additional contributors

The authors would also like to recognize the contribution of the following colleagues to this report: Partners and senior partners: Amit Garg, Dan Williams, David Remley, Federico Berruti, Felicia Tan, Felipe Costa, Felipe Villarreal, Fernando Ferrari-Haines, Fuad Faridi, Ishaan Seth, James Kaplan, Javier Martinez Arroyo, Jonathan Godsall, Joydeep Sengupta, Marukel Nunez Maxwell, Max Flototto, Paul Maia, Renny Thomas, Roberto Marchi, Roger Rudisuli Analytics and solutions co-workers: Anubhav Das, Belian Kiss-Borlase, Blanka Koji, Csanad Kortvelyessy, Debopriyo Bhattacharyya, Enrique Briega, Garima Ailawadhi, Istvan Rab, Jay Datesh, Luca Pato, Mayar Abdelaziz, Nurzhan Onashabay, Rauhan Nazir, Sanjana Agarwal, Sergey Khon, Shikha Gupta, Tanuj Sachdeva and Urvashi Jain As crew members: Annie Tan, Anouk Frieden, Eszter Teszarik, Gretal Tang, Julia Shamayskaya, Lisa Kondo, Mark Staples, Matt Cooke, Matteo Camera, Polina Skladneva, Pomponia Orehoczki, Roberto Truque, and Teresa Diviu The authors would also like to extend their thanks to the following banking equity analysts and experts; Brian Foran and John McDonald of Truist Securities; Guy Moszkowski, the cofounder of Autonomous Research US and now senior advisor; Mathias Nielsen of Nordea; and Mike Mayo of Wells Fargo Securities. Jana Zabkova, a senior editor at the New York office, did the editing.