3 Real Examples of how #AI is transforming Risk and Compliance

The world of Risk & Compliance is no exception to the transformational change being brought about by #AI. The community, conservative by definition and function, is straining to keep up with the blinding pace of the AI revolution.

It is increasingly apparent that one of the most profound effects of #AI is the move from a rules based world to learning-oriented, adaptable ecosystem of platforms. This shift is fundamental and every Risk professional needs to not just understand its implications but also take the lead in figuring out how to take advantage of it.

One of the big opportunities, and challenges, is to marry the technology with use cases that will have a measurable impact on the business: given the hype in the ecosystem, it is all to easy to start multiple PoCs and rapidly lose sight of the end goals, which in turn results in a wastage of precious R&D dollars.

At RZOLUT (rey-zo-lute) , we are going through a similar journey as we figure out how to ingest #AI into our own offerings. We started by asking ourselves some simple, timeless questions:

1. Is the technology enabling a new dimension of risk management that helps our customers build safer businesses?
2. Is it going to impact productivity positively: Will it result in faster and lower cost deliveries?
3. How do we leverage it to reduce manual interventions? (thereby not just cutting time and cost but most importantly, eliminating human error)
4. The investments are heavy: do the economics make sense?
5. Do we have the capability to implement, both from a funding as well as a technological skills perspective?

After much debate, we identified multiple areas where AI would make a discernable difference to our products and value propositions. Here are 3 ways in which #AI is transforming our Risk and Compliance Offerings:

1. Name Matching Engine: Leveraging a mix of third party and homegrown technology, we developed a next-gen name matching engine. So, when a search is initiated on our Screening platform now, the system is able to parse through 16 variations of name entry (misspelt names, phonetic similarities, etc.) before throwing up a result. This has resulted in a measurable reduction in false positive output, thereby partially overcoming one of the evergreen challenges that bedevils the industry.
2. Processing Media Articles: Our platform processes between 2 to 4 million media articles per day, sourced from across the world and in more than 100 languages. Feeding off the compute power of one of the hyperscalers and with our own #AI tech embedded, we are able to categorize and metatag articles automatically. Our engine extracts entities from within the articles and attributes "sentiment" at an entity level. Even more significantly, we are able to build a relevancy score on each article contextual to the topic of the search. This makes for super-efficient search and discovery exercises by users, saving precious time and cost and driving customer delight.
3. Summarization: One of the areas of strength of modern-day LLMs and AI engines is the process of summarization. We leverage AI to build summaries for news articles. We also use to to build Executive Summaries for Due Diligence reports. One important caveat here: we have observed hallucinations more than once. Therefore, it is imperative to have a structured review process to check the veracity of the summarization, else one can end up with dangerously incorrect conclusions. AI-driven, automated summarizations save an enormous amount of time for our analysts, researchers and DD experts.

I trust that you have been able to visualize the increasingly influential role of AI in the world of Risk and Compliance. With Agentic AI promising to intelligently complete entire workflows autonomously, we are excited about what comes next!

The AI revolution has barely started. The coming decade is going to challenge the Risk and Compliance community to reimagine how to enable the business to grow safely and profitably.