Data governance isn’t just for megabanks anymore. Asset managers are gradually joining the crowd of believers, creating rulebooks for how data quality is ensured enterprisewide with business lines at the helm.
That was the consensus of panelists and attendees at a TSAM North America fund management operations event last month where data management took center stage as a priority in 2017. Of the dozen operations managers from fund management shops attending the gathering in New York who spoke with FinOps Report, five say that their firms have already implemented a new data governance model while three will be doing so next year. The remaining firms are in the “discussion phase” between business units, technology managers and C-level executives.
Historically, asset management firms haven’t enjoyed a holistic view of their data. “Data management fell into the domain of the IT group who didn’t understand how it was really used,” says Paul McInnis, head of enterprise data management for BNY Mellon subsidiary Eagle Investment Systems in Boston. “Each business line had its own IT budget, so there was little alignment across the broader organization. The business lines adhered to their own rules which led to different ontology standards and permissions of who could access and oversee the data within the various units.” The result: inconsistent or duplicative data.
“The journey toward data governance for asset management firms is just beginning,” asserts Kenneth Lamar, principal partner at Lamar Associates in New York. “C-level management at the big banks have already tapped chief data officers in charge of enterprisewide programs.” Their reason: the financial crisis and subsequent bankruptcy of Lehman Brothers showed their vulnerability in identifying market, credit and counterparty risk for many of the asset-backed and mortgage-backed debt instruments as well as the swap contracts they traded.
“Chief executives are realizing that the tsunami of regulatory requirements has increased the need for accuracy and transparency; therefore, policies and procedures for who manages data quality and how it is managed need to be developed” says Richard Lane, senior enterprise data management and technology project manager for buy-side technology consultancy InvestTech Systems Consulting based in Boston. Incorrect or stale information can lead to incorrect regulatory reports on holdings, valuations and risk metrics. Most of the attendees at the TSAM event,who spoke with FinOps, cited the European Market Infrastructure Regulation (EMIR), Markets in Financial Instruments Directive (MiFID), Alternative Investment Fund Managers Directive (AIFMD), and Solvency II as the most data-intensive measures that were keeping them awake at night.
Of course, regulators aren’t the only ones concerned about data. If they are given the wrong information it stands to reason that clients will as well. If the securities watchdogs don’t catch the mistakes, rest assured the investors will. Nothing will damage an asset manager’s reputation faster than a disgruntled customer.
“One of our customers picked up a discrepancy in our reports which was ultimately traced back to an error in reference data,” one fund management operations manager attending the TSAM event tells FinOps. “We were then forced to do a top-to-bottom review of all of our data and discovered inconsistencies between business lines.” Ultimately, the asset management shop decided it was time for change and came up with a data governance program comprising six business lines.