Prioritizing responsible AI6 Executives must address self-governance, cybersecurity, privacy and ethical concerns as they build out AI initiatives. Any organization seeking to benefit from AI will need to address a host of critical issues up-front; self-governance, fraud and cybersecurity, data privacy, workforce management and the spread of disinformation are only the most immediate. This is especially relevant in a highly regulated area such as financial services, where firms serve collectively as a cornerstone of the global economy and a bulwark that protects individual customers and businesses against those who threaten their financial well-being. Responsible AI is a broad term that covers these and other issues. It refers to the practice of designing, building and deploying AI in a manner that empowers employees and businesses and impacts customers and society fairly. There are four main pillars: –Organizational: Democratizing the new way of working and facilitating human- machine collaboration. –Operational: Setting up governance and systems that will enable AI to flourish. –Technical: Helping ensure systems and platforms are trustworthy and explainable by design. –Reputational: Articulating the firm’s AI mission and ensuring this is anchored to its values, ethical guardrails and accountability structure.As companies implement AI more extensively, with ever-increasing sophistication and decision- making responsibility, it will be easy to lose sight of this imperative. Imperfections such as a minor demographic bias can quickly have an outsized effect when the technology is scaled across the firm’s operating model. To achieve responsible AI, leaders should leave no doubt that this is a corporate priority, and should disseminate a set of practical guidelines that help to embed it in people’s daily actions and the corporate mindset. As they begin to define their AI ecosystems, they will also need to evaluate their vendors, and the grouping of multiple AI systems based on their vision of the role of AI in their future. Businesses across financial services continue to prioritize responsible AI, especially in areas like self-governance, with 84% of financial organizations implementing or planning a framework to govern how AI will be built, trained, used and audited, to adhere to business principles and relevant regulations.21 Alongside this, there is growing support for external groups and coalitions, like the Fintech Open-Source Foundation (FINOS) and the Taiwan Financial Supervisory Commission. These bodies work together to support AI policy development, collaboration and innovation while also promoting the safe and effective use of AI across financial services. Artificial Intelligence in Financial Services 17of financial organizations are implementing or planning a framework to govern how AI will be built, trained, used and audited.84% 17 Artificial Intelligence in Financial Services

Artificial Intelligence in Financial Services 2025