Excellence in RiskTech: Dharrini Bala Gadiyaram, Bloomberg

Dharrini Bala Gadiyaram, Bloomberg

I’ve been very fortunate to be a part of an incredible team – since the inception of our Multi Asset Risk Solutions, MARS for short, we’ve always functioned like a startup within Bloomberg. This means every member of the team shows up prepared to learn from our clients and the fast-changing market we operate in and putting in the hard work to get things done, while coming up with exciting ideas for how we can incorporate technological advancements into our solutions. Having a great idea is just ten percent of the way to success – bringing that vision to life, and actually delivering the value is crucial for any business, especially one that moves as fast as ours. That’s why my mantra has always been “execution eats strategy for breakfast”.

How do you think RiskTech will evolve over the next five years, and what impact will it have on the financial industry?

The explosive advancements in generative AI and data science across the market have created some very exciting opportunities for RiskTech. The role of a risk officer involves looking at a host of different immediate threats, growing perils and long-tail risks, and so a lot of the evolution in the next few years is going to be around helping them understand, quantify, prioritize and manage all the risks that their firm is exposed to. This includes some newer risks – climate risk is a bit farther along in the journey but the market is still at the very beginning of understanding the financial impact of geopolitical risk and cybersecurity risk. We may also see AI risk added to the roster – we are seeing applications of AI in so many different parts of the industry, that the degree to which they have been tested, the explainability of the results of these applications and the reputational risk it could pose is going to emerge as a key issue.

What subjects interested you the most during your college days?

I graduated with a degree in Computer Science, and my favorite subject was neural networks. In fact, my thesis was on personalized search using contextual dimensions – training a neural network model based on a user’s preferred search terms and choice of results, and this was way before Google made it cool!

What excites you about the Financial industry?