Ex-LSEG execs partner to offer data strategy consulting

Tom Dunlap, former group chief data officer at the London Stock Exchange Group (LSEG), and John White, former CEO of consultancy 3di and global head of data sourcing and distribution at LSEG, have formed a partnership between their two consulting firms, to offer data management and strategy advisory services to startup data providers, private equity firms, banks and asset managers.

Dunlap’s Diacsus and White’s Watchdog Data Services began collaborating last month, and say they are already working with several client types and have partnership relationships in place with bulge-bracket accounting and consulting firms, as well as law firms, to gain greater exposure to potential client opportunities.

Combined, the pair have more than 60 years of financial services and data industry experience. Dunlap—who before joining LSEG spent 18 years at Goldman Sachs in various roles, including global head of enterprise data strategy and global head of reference data, prior to which he held a range of roles in Citi’s Worldwide Securities division, including head of portfolio accounting and reporting, and head of data management and control—brings experience of the policies and operational procedures associated with running a CDO office.

Before joining LSEG in 2010, White was global head of market and vended data services at State Street, prior to which he was VP of data management and strategy at FleetBoston Financial, and VP of data integrity at Wellington Management. He brings to the table significant experience in data licensing, data audits, and usage and cost optimization.

Dunlap says the two will continue to operate their respective companies, but that forming a partnership allows them to better serve clients, address bigger and broader client opportunities, and grow their brands and businesses faster, focusing on providing advisory services, commercial due diligence reviews, and transformational projects with clients.

“Bringing together our skills, experience and networks helps us fulfill more of what clients are asking for in terms of solving for their pain points, challenges, and opportunities,” Dunlap says.

Aside from working on data management projects as required by well-established financial firms on the banking and asset management side, the pair can also bring their experience and expertise to bear in building commercial data policies for companies bringing new data products to market.

“We’ve done a lot of research. There’s a whole area of fintech companies who are asking ‘Do I have the right policies and governance in place to create a commercial offering? And if I do, am I able to leverage that to take advantage of commercial opportunities in the market today?’” White says.

For example, startups offering alternative data and ESG data face a number of challenges, including integration and aggregation. Typically, these lack the understanding and governance of established data companies. They know that their data may be valuable, but don’t have the resources to take it to market in an effective manner.

“I can work with them on this and on distribution channels, and how to get their name and product out there without a large direct sales staff,” White says.

Other potential clients may be technology providers who want to make data available on an as-a-service model, but who first need to understand whether they own the data in question, and whether they are intermingling it with other data or distributing it in a way that could constitute a breach of license.

For example, if a private equity firm wants to invest in a tech or data company, they may enlist White to perform due diligence to confirm that the company does indeed own the data it’s distributing.

There’s a degree of overlap between what the two offer. Dunlap, for his part, also works with PE firms to perform due diligence on any potential investments in companies and assists growing data companies looking to expand their brand and customer base in capital markets.

“Part of that is leveraging my relationships, and part is taking a look at their products and delivery functions and capabilities, working with fintechs and regtechs to identify pain points, concerns and opportunities, and how they can best present their products in a way that resonates with senior leaders in the capital markets space,” he says.

Dunlap also works with firms on the buy side and sell side on what he calls “transformational” activities, identifying processes that can be improved within a firm’s data management function, which can involve changing policies, procedures, or performing a functional redesign.

One use case that the pair will focus on initially is ESG data, which presents challenges for all market participants due to its staleness. Many of the companies that ESG-conscious investors want to invest in aren’t publicly traded, and therefore report financial information infrequently—perhaps just once per year. Between those reporting periods, that data becomes outdated. Specialist providers may contact companies for interim updates and may apply their own views and interpretations.

The issue of stale data isn’t only about best practice: if, during that stale period, a company is placed on an exclusion list, investors and potential investors need to know. Aside from potentially being forced to divest at a loss, investors could face penalties as well as reputational damage—and in the ESG space, that’s something that clients care about.

So do regulators. And with benchmark and index providers now required to attest to the quality of their data inputs under Benchmark Regulations in the UK and EU, Dunlap works with both buy-side firms and data suppliers on ways to maintain and refresh that data. As part of this, White would look at the data contractually and determine whether there are any licensing issues with how the data is obtained or distributed, where the responsibility for data quality sits, and what’s required under the service-level agreement. And if a supplier cannot meet the requirements of the SLA, he can also assist in breaking a contract and can suggest alternative providers for a particular dataset.

“Tom and I both have experience on the end-user side and on the vendor side. So, we know what we know, and we also know what we don’t know. And if we can’t fulfill a particular technical need, we have strong relationships with other organizations that can do that,” White says. “We’re obsessive about data quality—because we both know what bad quality can lead to.”