4 minute read 4 Mar 2024
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If the regulatory and technological landscape moves fast, how do you make AI investments last?

Authors
Konrad Meier

Senior Manager, AI Law Leader in Financial Services | EY Switzerland

Solution-oriented financial services lawyer with an entrepreneurial mindset.

Harald Hügel

Senior Manager, Technology Consulting in Financial Services | EY ifb Switzerland

Experienced implementation-centric management consultant and trusted advisor.

4 minute read 4 Mar 2024
Related topics Banking and capital markets Financial Services Law AI
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AI offers exciting possibilities for financial services organizations – but demands careful planning amid emerging regulatory requirements.

Download EY AI Use Cases Banking and Insurance brochure

In brief

  • Financial institutions are discovering new use cases for AI across a variety of areas.
  • New regulatory requirements around AI are emerging and compliance with data protection remains vital.
  • Before investing in AI solutions, financial institutions need to carefully consider the business case, technology, process and regulatory aspects.

In recent years, artificial intelligence (AI) has emerged as a game-changer in the financial service industry, presenting a multitude of interesting business opportunities. AI’s ability to analyze large amounts of data, make intelligent proposals and automate various processes has the potential to reshape traditional banking and insurance practices

To address concerns around trust and bring the law in step with technological developments, the EU has also been working on a draft Artificial Intelligence Act (AIA) – the first law on AI by a major regulator anywhere in the world. The regulation takes a risk-based approach and seeks to position Europe as a global hub for trustworthy AI through harmonized rules governing the development, marketing, and use of AI in the EU. By fully understanding the regulation at an early stage, including its opportunities and limitations, financial institutions can realize a competitive advantage.

For further insights, refer to our article here: The EU AI Act: What it means for your business

Banks and insurance companies have access to an extremely large pool of data. In the past, this was not used optimally, not least due to human limitations on the way we process and analyze data. AI changes that. Before looking into opportunities, the implications of managing AI need to be understood. Understanding the technologies is the first step. For instance, robotics process automation is not a system that is capable of learning and improving. In a second step, the focus should be on re-designing the process and defining which steps can be done by the machine and which ones should be left to humans. Additionally, managers should promote augmentation and make sure that machines act as partners of human beings. Last but not least, they need to consider that data-driven decisions are better decisions.

Currently, many financial institutions have not yet moved from selected AI use cases to scaled AI across the entire organization. They often lack a clearly defined AI strategy, with many also maintaining a legacy core system, fragmented and siloed data management and outmoded operating models that prevent proper collaboration. Across the entire value chain, there are a magnitude of opportunities to tackle. 

How EY can help

EU AI Act readiness

The EU AI Act will be adopted shortly with far-reaching extraterritorial impact. As it is often more costly and complex to ensure compliance when AI systems are operating than during development, we recommend that firms start preparing now with a professional AI Act readiness assessment and early adaptation.

Read more

The opportunities of AI in the value chain of financial institutions are manifold. We see huge potential in digital client relationship management, customer service, claims processing, credit scoring and loan underwriting, anti-money laundering and fraud detection as well as risk assessment.

So far, many financial service providers have only realized pilot cases either in the front office – such as digital CRM to identify and predict customer behavior patterns and (chat)bots to answer basic client questions – or in the back office, especially in risk and compliance to detect fraudulent transactions. However, we also observe an increasing number of institutions seeking to take a strategic approach to deploying advanced AI and embedding it from the front to the back office.

While this enthusiasm for embracing AI is encouraging, it’s important to take a systematic approach to ensure a planned use case is both effective and compliant.

  • Assess the opportunity

    Take a business case, technology and process view to assess the concrete use case in detail and proceed to the next step if it is attractive on all three counts.Analyze the impact on data protection.

    In a second step, the impact on data protection policies including the revised Swiss Data Protection Act and European General Data Protection Regulations (GDPR) should be analyzed. If the use case raises no data protection concerns, proceed to the next step.

  • Verify compliance with the EU AIA

    The third step involves reviewing whether the use case can be further executed within the boundaries of the concrete EU Artificial Intelligence Act. On top of that, AI governance and ethical topics are addressed, and critical risks are mitigated. Especially, human supervision of key AI output is always required to ensure regulators’ expectations are fully met.

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AI Use Cases in Banking and Insurance

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Summary

Assessing the feasibility of an AI use case demands a combination of legal, technological and business know-how. This intensive approach is an effective way to ensure your AI investments pay off – in terms of results but also effort. As the technological landscape evolves, so too do regulatory requirements. Considering all aspects at the use case assessment stage ensures that financial and other resources are only invested in the most promising and feasible solutions.

About this article

Authors
Konrad Meier

Senior Manager, AI Law Leader in Financial Services | EY Switzerland

Solution-oriented financial services lawyer with an entrepreneurial mindset.

Harald Hügel

Senior Manager, Technology Consulting in Financial Services | EY ifb Switzerland

Experienced implementation-centric management consultant and trusted advisor.

Related topics Banking and capital markets Financial Services Law AI
Upvote