AI spending races ahead among European banks

European banking leaders are poised to increase spending on AI faster than on cybersecurity. This occurs amid challenges in recruiting top talent in both these areas and pressure to streamline costs and enhance efficiency. The second volume of the Infosys Bank Tech Index brings these key findings and more.  

Talent a hurdle to AI’s growth

AI is at an interesting stage. It helps banks grow and reduce costs. The technology can shore up banks defences yet brings with it concerns around ethical, data and cybersecurity risks.

Global banking spending on AI is growing faster than any other tech. AI, combined with the power of cloud, is delivering transformational growth and efficiency outcomes for banks. European banks’ AI spending is expected to rise by 5.9% — slightly slower than 6.3% for global peers. AI accounts for 14% of budget allocation in Europe, compared to 22% on average among banks globally.

Figure 1. Intended technology spending growth in current quarter

Source: Infosys Bank Tech Index – Volume 2, Infosys Knowledge Institute 

Notes:
1) *AI includes machine learning (ML), deep learning or neural networks, and large language models (LLMs).
2) N = 324, where N is total number of banks that participated in the survey (Europe = 61, Rest of the World = 263).

AI advancements, including generative AI, empower institutions to integrate the technology throughout their value chain. For example, Deutsche Bank uses generative AI for software development and adverse media management, while European neobank Bunq employs it for fraud detection. Going AI-first is now imperative for institutions seeking enhanced growth and efficiency. It also has a direct bearing on all connected stakeholders — enabling customers to make quicker, better decisions, amplifying employee potential, and delivering greater shareholder value through lower risk exposure.

Yet European financial institutions seem to lag on AI — one reason could be the challenge to find talent. AI topped the technology difficulty rankings, with a difficulty score of 28 (a higher score means the skills are harder to acquire) among European banks. This was higher than the global average of 26 and outranked cybersecurity and cloud in difficulty, confirming a trend identified in Infosys Generative AI Radar. In terms of skills, AI talent accounted for 26% of European tech staff recruitment against the global average of 30%. For example, Danske Bank accelerated AI adoption based on talent and capabilities. With talent competition intensifying, banks must compete with global peers and big tech companies to capture the best AI talent.

Figure 2. Technology areas by difficulty to recruit

Source: Infosys Bank Tech Index – Volume 2, Infosys Knowledge Institute 

Notes:
1) *AI includes ML, deep learning or neural networks, and LLMs.
2) N = 324, where N is total number of banks participated in the survey (Europe = 61, Rest of the World = 263).
3) Tech skill difficulty score: This shows the difficulty banks face in acquiring human resources for a technology compared to other technologies. This is based on the average weight given to a technology when respondents were asked which technology areas were the most difficult to recruit for.

Historically, regulations have trailed technological advancement, especially in AI. Now there is an increasing impetus from governments worldwide to introduce regulations so that institutions can build ethical, responsible AI. The EU AI Act, set to take effect in June 2024, aims to keep strict transparency on high-risk AI models, tools, and systems. While many of the act’s obligations fall on providers, developers, and deployers of AI systems, it also applies to institutions developing AI inside the EU member countries and sometimes those outside the EU if their AI system’s output is consumed within the EU. With specific provisions likely to take effect over the next three years, financial institutions are evaluating the act’s impact on parts of their AI-powered businesses. These include credit scoring models and risk assessment for health and life insurance, and noncompliance could lead to hefty penalties.

Europe continues to focus on cybersecurity

European banks are set to increase cybersecurity spending by 5.1%, surpassing the 4.1% global average rise. This heightened focus aligns them more closely with their international counterparts. Our survey reveals that cybersecurity now represents 26% of budgets in Europe, compared to 24% in other regions. With heightened digitisation and geopolitical tensions, cybercrime has been on the rise. As cybercriminals continue to target the European financial services and insurance sectors, the average cost of a data breach in 2023 was US$4.7 million in Germany and US$4.2 million in the UK. Such incidents erode customer trust, trigger bank runs, and damage reputations, sometimes leading to executive resignations. A data breach at Equifax, an American consumer credit reporting company, led to the resignations of its CEO and other senior executives and multimillion-dollar fines by regulators.

As European institutions gear up for new regulations, such as Digital Operational Resilience Act (DORA) effective from 2025, focussing on enhancing resilience, including cyber resiliency, cybersecurity investment is expected to grow. Financial institutions must embed security into their framework design, build scalable enterprise-wide resilience and security, and adopt technologies that drive resilience in the future.

Cost optimisation in a difficult economy

Since the release of the first index, European banking executives have intensified their focus on cost reduction. While banks historically struggled to optimise costs during economic downturns, often pursuing this strategy in isolation, they typically prioritise growth. But shifting strategies without strong senior management commitment can prove detrimental, with research indicating that only 26% of technology leaders achieve expected returns.

Figure 3. Technology strategic priorities

Source: Infosys Bank Tech Index – Volume 2, Infosys Knowledge Institute 

Note:
1. N = 324, where N is total number of banks that participated in the survey (Europe = 61, Rest of the World = 263).

Effective cost transformation requires a committed journey towards sustainable, positive outcomes. Leading banks incorporate cost optimisation into their overall operational strategy, planning transformations in phases to yield cumulative benefits. Quick wins are achievable through initiatives like automation and strategic talent sourcing. Each phase of cost savings fuels the next, gradually reducing the need for additional investments. This self-funded, continuous approach ensures efficiency and fosters innovation within banks.

Interestingly, investments in AI can optimise costs. Although it demands an initial investment, a strategic commitment helps banks rapidly increase efficiency and productivity. For example, Dutch bank ABN Amro uses generative AI at its contact centres to create call summaries so that representatives can focus more on clients. The bank also uses the tech to generate improved call training data, that leads to better responses during calls. BBVA, the Spanish financial institution, is actively developing approximately 100 generative AI use cases to enhance productivity, streamline processes, and foster innovation.

Institutions with well-crafted strategies and strategic alliances resolutely shape decisions that foster innovation and transform operational efficiency, workforce dynamics, product offerings and the overall customer experience. These endeavours yield enduring benefits for stakeholders and offer a formidable competitive edge to banks.