Intelligent Banks Do More with Less

While global banks face growing pressures in 2024, Generative AI offers new opportunities to do more with less.

The report: World Report Series 2024 Retail Banking: Intelligent Banks Do More with Less [March 2024]

Source: Capgemini

Why we picked it: French IT and consulting company Capgemini produces excellent reports on the banking industry. The annual World Retail Banking Report looks at global banking trends and technology.

Executive Summary

Capgemini’s World Banking Report is now in its 20th year. The consulting company partnered with Microsoft, Salesforce and Temenos to survey over 250 banking executives, 1,500 employees and 4,500 customers. In 2024, banks face a volatile and uncertain banking landscape market characterized by inflationary pressures, competitive new-age banks, declining interest income and geopolitical uncertainties.

This year’s report views how embracing AI-driven strategies can optimize operational efficiencies while improving the customer experience. Capgemini notes that the seamless adoption of AI-powered copilots can augment human expertise and revitalize retail banking by taking a bottom-up strategy to help scale intelligent transformation.

Key Takeaways

• 70% of bank CXOs plan to increase digital transformation investments by up to 10% in 2024

• 80% of bank executives believe generative AI represents a significant leap in advancing AI technology

• Bank staff typically allocate 70% of their time to operational activities and only 30% to customer interactions.

• Capgemini’s analysis found AI copilots can offer a significant productivity boost and help banks optimize up to 66% of the time spent on operational documentation.

What we liked: Capgemini surveyed many bank executives and customers for a full view of the industry and how AI applications may help.

What we didn’t: The sheer volume of stats, data, findings and excess content is overwhelming and can lead readers into the weeds. This could have almost been broken up into a few separate reports.

Turbulent Headwinds Ahead

Most of 2023 saw healthy global bank performance, with revenue growth and improved net profit margins due to high interest rates and low credit defaults. However, 2024 brings greater volatility, with inflationary pressures, declining net interest income and geopolitical uncertainties. As a result, many banks are striving to get back to the basics by focusing on productivity, expanding the customer base by retaining profitable segments and diversifying into non-interest income.

Financial stress: Nearly three-quarters of respondents across 14 markets said inflation had a moderate to high impact on their economic well-being, while 16% said it drove them to live paycheck-to-paycheck. Capgemini notes this is an early sign of falling demand for credit and an outflow of bank deposits as consumers deplete the savings they acquired during the pandemic. The trend was most notable in the United States.

Declining deposits: Despite the attractiveness of high interest rates to consumers, banks have been slow to pass on all the benefits to their customers. In the U.S., by June 30, 2023, bank deposits declined 4.8% YoY for the first time since 1994. Additionally, concerns over the stability of small regional banks spurred a shift in deposits to larger financial institutions. Over half of the customers surveyed said they had plans to diversify their deposits across multiple banks to limit potential losses to a bank failure.
Managing Customer Profitability: Given the economic volatility, banks need to identify profitable customer segments, each characterized by different profitability and loyalty levels. Capgemini notes four segments, each requiring a different strategy to boost profitability.

Building a new, future-focused customer pipeline: A large aging consumer segment means there could be sparse credit demand in the coming years. CXOs said Gen Z individuals account for only 21% of their bank’s total customer base and only 9% of bank executives prioritize acquiring those customers. Banks targeting this demographic should seek collaborative, white-label partnerships with Gen Z brands rather than direct investments in the segment.

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The shift to digital: The disparity between in-branch banking and digital channels continues to widen. Only 23% of respondents preferred visiting branches, yet they are gradually shifting to digital channels. However, these digital channels have relatively lackluster experience and nearly 60% of customers rated their bank’s mobile app as only average.

Cost base: Customer and competitive pressures are moving banks to reassess their cost base and prepare for potential challenges in 2024. Rising funding costs, reduced lending volumes, declining customer confidence and the threat of non-performing assets may fan the flames of business. As a result, bank CXOs are proactively tightening their operational belts by focusing on efficiency and productivity.

Read more:

Improving Banking CX and Efficiency with Gen AI

The World Retail Banking Report 2024 found that 80% of bank executives believe generative AI represents a significant leap in advancing AI technology. AI applications have become pivotal in banking, transforming operations from the back-office to the front end. AI can support customer acquisition, retention and risk management.

A copilot to elevate workforce productivity: Capgemini found more than 60% of bank employees are frustrated by lengthy, repetitive documentation processes and allocate nearly 70% of their time to operational activities, leaving only 30% for customer interactions. Capgemini notes that generative AI can augment human expertise by complementing decision-making, offering insights and recommendations and aiding task completion.

“Generative AI can have a lighthouse effect when used responsibly and wisely across operations. There is also a need for increased efforts on making Gen AI explainable and appropriately transparent. The time to act is now to establish practices that build much-needed trust and customer intimacy. Success will come down to developing a roadmap that balances hype with a pragmatic, traceable and measurable approach.”

Supporting the workforce: A generative AI copilot architecture blends advanced generative models and data sources with banking applications to create and share authentic data. Capgemini noted the transformative impact of workforce copilots in banking, which could yield a productivity surge between 20% and 70%, particularly in IT and development activities.

Documentation: Processing documents remains costly and labor-intensive in the banking industry. Bank employees spend 55% of their time on documentation and operational tasks throughout the onboarding, KYC and account opening process and only spend 9% of their time on customer interaction. Capgemini’s analysis found AI copilots can help banks optimize up to 66% of the time spent on operational documentation.

Bank contact centers: Many contact centers continue to operate in communication silos, disconnected from mobile platforms, websites and branches. 61% of customers said they contacted agents because they were unhappy with chatbot resolutions. Coincidentally, 81% of bank employees rated contact center digitization as low. Gen AI-enabled solutions can transform contact centers into value amplifiers by optimizing nearly 77% of the time spent on various operational and customer interaction activities.

An Enterprise-wide Approach to Scale AI Capabilities and Value

Banks will find several impediments in the race to enterprise-wide AI transformation.

Challenges: First, legacy systems make it difficult to integrate new AI technologies. Many banks have fragmented data across disparate departments, which must be aligned to support AI applications. They also have skill shortages, an inherent risk aversion and a concern about the costs and uncertain returns.

Inadequate back-end capabilities: Capgemini’s survey found CXOs were allocating 56% of their technology budgets to the front end, compared to only 44% on back-end improvements. While CX is important, back-end investments are fundamental for ensuring data security, operational efficiency, scalability and system integration of various systems in the bank’s ecosystem.

Intelligent transformation readiness: Despite the benefits, only 6% of CXOs surveyed said they are ready for a roadmap for enterprise-wide AI-driven transformation “at scale.” Approximately a quarter said they are actively exploring a suitable roadmap or are in the early stages of devising a plan. Additionally, 34% have developed AI adoption strategies for specific lines of business but have not integrated them within the enterprise.

Unlocking value in data with a product mindset: Banks can embrace a “data mesh architecture,” which proposes a decentralized approach to data architecture with domain-oriented data ownership. Data is not treated as an asset or by-product of operations but as a standalone offering with a value proposition. Domain teams can then create and manage data products tailored to their needs.

Shape the model layer: Banks must decide whether to buy, partner, or build. Buying enables them to quickly adopt AI with off-the-shelf generative AI solutions, typically at a lower cost. While 56% of CXOs preferred this approach, these solutions have limited customization options. Partnering allows for greater customization but demands substantial investments and modifications to the bank’s data architecture to seamlessly integrate the generative AI solution.

Define KPIs: Banks will need to create their own KPIs to measure the impact of intelligent AI across various facets of organizational strategy and performance. They should consider bias, hallucinations, privacy risks and the risks of malware use.

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