Italian Banks Eagerly Investing in an AI Transformation

Category Machine Learning

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In 2023, Italian banks have invested significantly in AI-driven transformation. This transformation includes aspects of corporate strategy, such as budget, benefits, and strategy, as well as governance aspects such as organizational structure and processes, risk management, skills management, and ethical implications. Benefits of investing in AI include improved business performance, decision-making, customer relationships, products, and services. AI governance requires transparent, explainable, and traceable frameworks to monitor business and technical efficacy as well as risk and ethical compliance.

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AI-driven transformation continues to accelerate. In this phase, banks are faced with new challenges and opportunities, which force them to pay attention to a plurality of aspects, all transversally crossed by a major cultural transformation.The main aspects affected by this transformation are, on the one hand, corporate strategy, which concerns the degree of pervasiveness of AI within banking activities, the dedicated budget, the benefits encountered and the challenges that remain open, as well as of course their progress over time. On the other hand, however, there are the governance aspects, which embrace organizational issues, processes, management of skills and issues relating to risk management and ethical implications.

Many Italian banks have invested in AI well beyond the €500,000 mark

With reference to the strategic aspects, it should be noted that AI today represents an increasingly important investment item for Italian banks. 76% of respondents to the ABILab survey (2023) state that they have a dedicated budget and in 65% of cases this budget is more than €500,000 and 59% of those interviewed expect that budgets will further expand in 2023.

There is a strong tendency to interpret AI as a strategic driver of business transformation. In fact, 88% of respondents stated that they have defined/are defining an ad hoc strategy, which will then have to be put in synergy with the company's Data Strategy. This theme also implies the strengthening of partnerships and ecosystems useful for promoting innovation.

About 88% of the responding banks have defined or are currently defining an AI-driven transformation strategy

In fact, Italian banks are already using mixed sourcing models for the development of AI solutions, using make and buy levers accordingly and interfacing with a variety of players (ICT partners, startups, etc.) .

In defining an AI-driven transformation path, it is also important to frame the benefits that banks intend to seek and obtain. In this regard, it is interesting to note that answers to the survey do not exclusively refer to higher economic returns from a reduction in costs (53% of the sample), but also to improvements in decision-making processes (53%) as well as strengthening the relationship with the end client (41%) and, last but not least, improving existing products/services.

53% of Italian banks reported a decrease in operational costs, 53% improved decision-making processes, and 41% reported an improvement in their relationship with the end client

In fact, the majority of use cases already present on the market concern support to (assisted and self-service) channels and support to control functions.

On the other hand, as regards governance issues, most of the responding banks (58% of them) say they are working on implementing a framework for the governance of AI and these initiatives are often placed in continuity with the efforts that have been devoted in recent years to the definition of a company model for Data Governance, now widely operational in banks.

58% of responding banks are implementing a framework for AI governance in conjunction with their existing Data Governance framework

The main pillars on which the banks intend to build this governance system are those of transparency, explainability and traceability. They also believe it is useful to have a monitoring system that makes it possible to evaluate the results of AI from the point of view of business effectiveness, technical efficiency, governance and ethics. This kind of monitoring that is already in place in about 40% of the sample.

Transparency, explainability, and traceability are all seen as pillars for the framework on which banks intend to build their governance system

A further important factor concerns skills, which are necesary to leverage AI for its full potential and make it effective. The majority of the addressing banks (60%) are confident in the ability of their internal resources to manage the AI process, particularly from the skills point of view and in terms of managing AI projects.

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