Applying AI on Incomplete Data Leads to Incomplete Solutions — Kroll CDO

(US & Canada) Samir Mehta, Chief Data Officer at Kroll, speaks with Gavroshe Chairman and CDO Magazine Editorial Board Member Derek Strauss, in a video interview about his professional trajectory, leveraging data to gain actionable insights, and utilizing AI to create organizational growth opportunities.

Kroll is a leading independent provider of risk and financial advisory solutions.

Mehta begins by reflecting on his professional trajectory spanning three decades and what led him to hold the CDO role for over 10 years. At the onset of his career in the early to mid-nineties, Mehta worked at capital markets in the NYC area, wherein he noted a gap between the front and back-office business units.

Next, Mehta discovered that both the units spoke two different corporate languages, which fueled the gap. To address this, he found a treasure trove in the language of data, which he utilized to bring the two entities together.

Eventually, this gave rise to an interest in business intelligence, which means making sense of the assembled data, Mehta adds. Additionally, he states that the first iteration of AI was business intelligence, or finding intelligence in the data that brings businesses together.

As CDO roles surfaced after the financial collapse of 2008, their initial mandate was to control the organization through a defensive approach of risk and control management. Over time, CDOs started strategizing ways to generate organizational revenue, becoming more offensive.

According to Mehta, that is when the CDO role made it to the C-suite, and he affirms being a part of that journey. Combining all his past experiences of working in manufacturing, financial services, and tech, he notes that for the most part, the data challenges have been the same.

However, Mehta maintains that the solutions to these challenges differed because the end product expected by the companies and clients is different. With vast experience, he brings the advantages to Kroll to elevate internal workflows and provide better solutions to customers and clients.

Responding to how the CDO role leverages massive amounts of data to gain actionable insights, Mehta states that in addition to the vast data, Kroll also has different types of data across the landscape. As an organization, Kroll is made up of multiple service lines across two primary business units: financial advisory and risk advisory.

Furthermore, each of those service lines has unique clients in the silos that they operate in, says Mehta. However, as the CDO, he is trying to build an organizational connected data ecosystem to bring financial advisory, risk advisory, and service line data together with internal firm’s services data.

This will create a truly 360 view of the organizational data, says Mehta, which would enable cross-pollination around the service lines and create unique data sets. Thereafter, the organization can bring a different type of product and service to its customers. The true challenge lies in finding the value in data by bringing it together, he adds.

Sharing his thoughts on leveraging AI to create growth opportunities, Mehta states that Kroll does not want to rush into incomplete solutions. He says that not giving in to the current AI rush will be beneficial for the external client base and also for internal practitioners.

Therefore, Kroll is cautious about applying AI anywhere within the organization. The standard practice is to make the organizational workflows better, says Mehta. Nevertheless, everything starts with advancing organizational data because applying AI algorithms on top of incomplete data sets will lead to incomplete solutions, he notes.

In conclusion, Mehta says that the organization is focused on getting data organized to apply AI to a complete data set. Once the data set is ready for AI use, there will be no need to rush to AI, as answers will flow seamlessly.

CDO Magazine appreciates Samir Mehta for sharing his insights with our global community.