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From Principles to Practice:

Use Cases for Implementing Responsible Artificial Intelligence in Financial Services

There is great interest in financial services – as in other industries – in the promise of AI to unlock new opportunities for innovation, increased efficiency, and improved services for customers. This promise is fast becoming reality, with growing adoption of AI by financial institutions across Asia.

A recent survey conducted by IDC and Microsoft with 168 business leaders and 94 workers from the financial services industry across 15 Asia Pacific markets found that

More than half (52%) of financial institutions surveyed said they are already on their AI journey, with positive impacts across business functions, including better customer engagement, improved competitiveness, accelerated innovation, and improved business intelligence.
Responsible AI principles in financial services

In Singapore, the Monetary Authority of Singapore ("MAS") and Personal Data Protection Commission ("PDPC") have both issued guidance documents that set out various considerations for how organisations can use AI in a responsible manner:


In mid-2019 a cross industry group came together – Deutsche Bank, Linklaters, Microsoft, Standard Chartered Bank, and Visa – to explore the application of responsible AI principles in financial services.

In response to invitations by the MAS and PDPC to pilot their guidance, the group applied the two sets of Singapore responsible AI guidance to three specific use cases drawn from the practical experience of the group in developing and deploying AI systems.

1. Using AI to predict which cards will be used for travel

B2B service applying AI to predict consumer travel behaviour as a basis for travel-related marketing


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2. Using AI to automate verification of wet ink signatures

Applying AI to verify a signature against the client’s specimen signature



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3. Using AI for regulatory compliance relating to Know Your Customer (KYC) checks

Using AI to generate insights and support decision-making for KYC Compliance-related processes

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The six key learnings from the application of responsible AI guidance to the three use cases that financial institutions need to know

The importance of context and assessing materiality for specific use cases

Guidelines on responsible use of AI must acknowledge the importance of context in translating high-level AI principles into practice. Specific principles will have different implications in different contexts - and some principles will be more, or less relevant. Therefore, assessing materiality is especially important given that AI is increasingly embedded in all forms of software

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