This need for a consistent framework for data management complements other regulatory initiatives, such as the Basel Committee’s Principles for effective risk data aggregation and risk reporting (BCBS 239) and Fundamental Review of the Trading Book (FRTB). However, a “consistent” framework does not mean an inflexible framework that cannot accommodate different data needs, different ways of defining data quality and different departmental and geographic timeframes for data preparation.
The office of the CFO and CRO will each have their own unique requirements, approaches and operating rhythms. Finance departments typically work to produce monthly and quarterly snapshots which require data sets that conform to stricter sets of externally defined rules, such as the official exchange price at a particular official market close. Risk managers might need similar price data, but such data needs to be available on a daily basis and aligned not just at market close but at a consistent times across all markets. Put another way, risk management is concerned with how things might change from “now” looking into the future, whereas finance want more a snapshot of “now” and how we got to “now”.
However, this picture is changing. Regulation seems to be driving more convergence between the data needs of risk and finance. Internal models for calculating market risk capital requirements may face more prescriptive controls as a result of FRTB, while risk management concepts such as Expected Credit Losses are being brought into finance by regulations such as IFRS 9 itself. To facilitate this convergence between previously siloed approaches, firms will need enterprise data management systems that are sufficiently flexible to accommodate a full range of complex workflows.