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Summary

Are you curious about how artificial intelligence (AI) is transforming the banking industry? According to a recent survey, banking executives believe new technologies like AI, automation, and blockchain will continue to drive the global banking sphere for the next five years. But what about regulatory concerns around these technologies? While risk management has never been about risk avoidance, banks must re-evaluate their risk culture to win in the digital age. In this article, we explore how AI is crucial in accomplishing risk and innovation goals and delve into some exciting AI use cases in the client onboarding and AML/KYC space. But how can disruptive AI be successful in banks? Read on to find out.

The pace of digital innovation in financial services has been stupendous in the last few years. From products and services like digital banking, digital wallets, robo-advisory, and crypto trading, to the adoption of infrastructure driving open banking, cloud banking, and real-time payments, as well as serving high-risk growth businesses like the cannabis industry, online gaming, etc. – the landscape is rapidly changing.

Findings of an Economist Intelligence Unit survey1 report say that 66% of banking executives believe that new technologies like AI, Automation and Blockchain will continue to drive the global banking sphere for the next five years while regulatory concerns around these technologies remain top of mind for 42% of banking executives. While robust risk management has never been about risk-avoidance but rather to manage risk effectively, in this age of tech-driven innovation, banks must relook at their risk culture and reassess the desired risk-reward balance to win in the digital age.

The Risk & Compliance functions continue to become more of a strategic business partner, enabler, and driver – and intelligent automation/ AI can play a significant role in bridging the actual or perceived gap between risk and business innovation.

A Top-Down View Is The Need Of The Hour

Risk management and business innovation might intuitively appear at loggerheads with each other. Taking a strategic view, however, there is a common set of objectives to be driven from both a risk and an innovation perspective. A few examples are listed in the table below.

AI can play a key role in accomplishing the risk and innovation goals in each of these broad themes. So, if Financial Services firms take a top-down view, they can drive AI programs strategically to achieve enterprise-wide objectives rather than implementing use cases in silos.

A Deeper Dive Into Some AI Use Cases

Let us take the example of client onboarding and KYC reviews to demonstrate the applicability of AI across the value chain, both for reimagining and innovating the process, and for improving risk management as part of digitalization.

Some use cases for applying next-gen technology in this space include:

  • Knowledge Graphs: Entity resolution and network analysis can help evaluate risk in the context of associations and connected data. The insights generated from the connected data across client relationships can help spearhead innovations, from minimizing client burden during onboarding (staying one step ahead in data gathering) to providing a one-bank model for customers.
  • Process mining: Control gaps, operational violations or inefficiencies can easily be detected, and automated risk & controls can be implemented to address these. The process intelligence provided can drive multiple innovations to streamline and simplify the onboarding journeys and omnichannel onboarding experience.
  • Advanced Analytics: In the AML/KYC space, insights, predictions, and outlier detection can help risk managers better manage emerging risks. Similarly, these insights can help with new customer acquisition at exponential volumes and provide hyper-personalization of offerings cutting across business/ product silos.
  • Natural Language Processing / Generation: Drive risk insights from unstructured data while improving the productivity of Risk & Compliance managers. At the same time, it can be game-changing in simplifying the complex account opening requirements for clients and streamlining requirements across business/ product lines and jurisdictions.
  • Generative AI: Of course, one cannot fail to mention the latest technologies, which can quickly transition from hype to actual use cases like conversational advice to clients and risk summarization for compliance managers.

We have helped implement several of these use cases at both mid-sized and large FS firms, not just at the Proof-of-Concept level but also at production scale. In our experience, a critical success factor at these firms has been an active buy-in and involvement from Risk and Compliance executives; in fact, many of these initiatives have been led by and piloted for the second line of defence even before being used by the first line of defence.

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How Can Disruptive AI Be Successful In Banks?

Disruptive technologies can be a significant enabler of innovation and digital risk management, but we must acknowledge that they can also bring newer manifestations of operational, financial, and reputational risk.

  • Top management and Boards need to gain a deeper understanding of disruptive technologies and their associated risks.
  • As banks focus on technology-led innovation, they must include Compliance and Risk as partners, enablers, and advisors from the start of their transformation journey.
  • A culture of Digital Risk by Design needs to be established while also digitizing core risk processes themselves.
  • Compliance, Risk and Legal teams need to restructure and reskill to have a seat at the digital innovation table.

It is but a myth that Risk and Innovation – the twain shall never meet. Thoughtfully applied next-gen technologies can play an instrumental role in bridging the gap for financial institutions.

Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies