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The impact of the introduction of Artificial Intelligence on the banking world and on Corporate & Investment Banking

Transforming processes and customer experience
reading time: 6 min

The application of artificial intelligence is becoming increasingly widespread and influencing almost all markets and industrial sectors. The size of the global AI spending market is estimated at around EUR 550bn in 2023, to grow exponentially with a CAGR of around 19% by 20261.

Artificial intelligence systems are based on algorithms that utilize large amounts of data provided as input to advanced models that process various outputs, such as, for example, predictions of future events, decision-making recommendations or suggestions based on a series of explicit or implicit predefined objectives.

Since 2023, there has been exponential growth in the development of generative artificial intelligence that introduces the large-scale use of neural networks, programmed on large amounts of data, in order to perform a wide variety of tasks, including generating texts, images, videos, music or other media in response to requests formulated in natural language (the so-called "prompts") expressed by the user.

In the banking sector, artificial intelligence, both in the most traditional forms and in the recently deployed generative forms, can be applied to support certain processes and objectives, including:


  • Improving operational efficiency and effectiveness, by automating of internal processes, contributing to greater automation and uniformity in the processing of information (such as, for example: documentation, contracts, correspondence, information flows, etc.) and reducing time and costs (some areas include commercial, credit granting, processes, back office teams, etc.)
  • Improving customer experience and making financial knowledge more accessible, thanks to the language skills of generative artificial intelligence, clients can promptly access the information needed to complete the so-called customer journey within the banking channels dedicated to certain products that can be identified and clustered in advance and that are best suited to the digitisation of sales. Artificial intelligence offers the option to quickly process technical, transactional and financial information on those same channels, facilitating digital communication between the clients and the Bank
  • Improving fraud detection, through the processing of information related to onboarding processes and controls, to intercept and address any fraud attempts to the detriment of clients in a timely and informed manner.

The introduction of artificial intelligence in the Corporate and Investment Banking world is gradually leading to reflections on possible innovation themes compared to more traditional business models, offering interesting opportunities that support and enhance the activity of Relationship Managers and some specialist desks.

In addition to the applications already mentioned, AI could represent an innovative enabling factor in some areas, such as:



  • Predictive analysis on industrial sectors: in the Corporate and Investment Banking world, timing is essential to guarantee the right support to clients and partners in directing commercial action and investments in line with market needs. Advanced analytics and machine learning techniques are used to simulate future scenarios and contexts in order to develop synergies between the bank and clients and to exploit information and opportunities in an ever-changing environment
  • Markets and trading: through the application of reinforcement learning for the development of algorithms capable of autonomously implementing sequential decision-making strategies to support the operations of specialists in the financial markets. In addition, artificial intelligence can help reduce costs and operational risks associated with the management of trading flows, by automating manual and repetitive tasks such as data verification, transaction reconciliation and exceptions handling
  • Automation of market data collection and ESG scoring: Natural Language Processing techniques are used to collect, sort and process market data from various sources, such as financial statements and other publicly available information, facilitating due diligence and company evaluation processes, including in the ESG sector.

Although in Corporate and Investment Banking the central role of the Relationship Manager continues to be a distinctive element, artificial intelligence can offer advantages in process management with the aim of raising customer service levels, thereby increasing competitiveness on the market.

It is also crucial that supervisory authorities and financial institutions cooperate to ensure responsible and informed use of artificial intelligence systems, through the assessment and monitoring of potential risks.

In this regard, the European Union recently agreed on the AI Act regulation. The new regulatory framework aims to protect citizens from the health, safety and fundamental rights risks that may arise from the use of artificial intelligence systems, in line with the values of the Union. The aim is to promote ethical, sustainable and inclusive development for a technology that will be the focus of innovations in the coming years, including those in the banking sector.



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