IHS Markit Expands EDM to Non-Financial IHS Data

IHS Markit is adapting its Markit EDM (Enterprise Data Management) platform to manage new data types from industries outside financial services where the IHS business has existing datasets, but which—when combined with other data in the EDM platform—could benefit other industries as well as financial clients.

The vendor is considering which datasets to expand the platform to cover next over the coming 12 months, after spending the past year adding functionality to support the energy industry. Now, IHS Markit is looking at the automotive/transportation and maritime/trade sectors, as these would potentially be of interest to financial firms, benefit from better data management, and also have some crossover with the energy sector.

“Though our strength has always been in the asset management sector, there was always an intent to expand into other areas of financial services and other industries—and with the merger with IHS, we can expand that to alternative data, which is an area that needs data management,” says Andrew Eisen, MD and head of EDM product management at the vendor. “We had a lot of interest from the energy space, which is the second-largest industry covered by IHS… and in fact, it originally started with an internal team in our energy business that realized there must be a better way to get our information out to clients, so they came to us.”

A key addition was the inclusion of two-dimensional and three-dimensional geolocation data to the EDM platform, which would include details such as the map location of an oil well, and also the depth of that well. IHS Markit tested the changes internally for three months last year, and took a working prototype to market around six months ago.

Since rolling out the energy-specific functionality, around a dozen new clients with operations in the energy space are now using the platform. And while three or four are using it purely to support their core business as energy providers, and have nothing to do with finance, the remaining three-quarters of these operate within financial services, and use energy data as part of their investment theses, Eisen says.

“For example, you might want to do a mark-to-market use case of evaluating assets [such as oil or gas] based on other assets produced in similar locations…. Or you could do a comparative analysis to be able to determine whether you should go long in stock of one oil produced or oil service provider, and go short in another, based on production at the individual well level,” he says. “IHS has that data…. What the technology does is provide a scalable, usable application package to use and visualize the information, which makes it humanly readable and adds context, and—through EDM—allows you to marry that with other data that you couldn’t before, such as industries that haven’t been so demanding about [standards and integration between] datasets as financial services.”

The vendor is considering adapting the EDM platform to support the automotive/transportation and maritime/trade sectors next because each presents obvious use cases for financial firms, as well as market participants in those specific industries. IHS’ automotive business line not only creates sales and supply forecasts and supply chain information, but also collects “secondary market” sales data through its Carfax acquisition.

Eisen cites the impact of 2017’s Hurricane Harvey on the auto industry and related areas as an example of how the data can be pulled together. “It destroyed new cars being shipped to dealers, creating a short-term supply shock, while insurers suffered the cost of damages, and there were several third-order areas affected, such as reinsurance and government spending… for anyone who wants to do that fundamental analysis,” he says. “IHS has a rich set of data across those pieces that have never been brought together to analyze an event like that, or mapped those relationships between cars, companies, and financial instruments… that would be of interest to financial services clients.”

Continuing the Hurricane Harvey example, Eisen says a link to maritime/transportation data helps extrapolate the extent of an event’s impact. “With maritime data, which includes geolocation of ships and bill of lading data, I can see the geolocation of replacement cars and when they are scheduled to arrive, so I can understand how long that short-term shock is expected to last.”