Complying with the multitude and ever changing regulations is a complex, time-consuming and costly activity especially when the regulatory bar keeps rising to meet global standards like BCBS 239 or regional standards like US Federal Reserve CFO Attestation. These industry initiatives have pushed data governance to the fore. In the past, data governance was a concern primarily with the back office and auditing, now it has moved forward to middle and front-office end-users and even senior management requires access to granular details about data flow and governance rules. The cornerstone of data governance begins with data lineage. As an analogy, one can extrapolate and visualize data lineage as being the equivalent of a GPS function. Imagine driving on a long journey and only being equipped with the 20 year old paper map! Chances that you will take the shortest and safest route and get there on time are very slim. GPS was revolutionary as it provides us with a tool easy to navigate which tells us the direction for each turns you need to take until you reach your final destination.
Today, regulatory bodies closely examined financial institution’s compliance processes and governance such as BCBS 239-Risk Data Aggregation and Reporting and other worldwide regulatory mandates demanding back testing, reconciliations to the source data and attestation rules, as well as requiring financial firms (FIs) to submit regulatory reports using XBRL which require prescribed data point taxonomies. As a result, CEOs and CDOs need to find a reliable way to move their firms to a data governance strategic advantage in a cost effective and sustainable manner.
Let’s look at some data challenges FIs have been struggling with: - low-quality business information resulting from data integrity concerns often caused by unreliable ‘black box’ aggregation processes, - lack of data specialists dealing with high volume of disparate data sets, - managing business requirements and processes through legacy corporate data warehouses and - data lakes becoming extremely challenging projects. In a nutshell, systems are ill-equipped to handle these demands and outside of these technical challenges, business and IT leaders are not working collaboratively which exacerbated firms’ data problems.
To address these challenges and rising global and regional standards around data governance, many FIs have realised its importance and began initiating evaluation and implementation of data lineage tools. However, getting data lineage right is difficult work—starting with the metadata. Especially when some of it is incomplete and when it is available, it is often dispersed. And even when it is effectively funneled to one place, many systems are not designed to handle or interact with highly complex and granular regulatory reports which might result in limitations in scaling data lineage projects. Good example can be drawn to more resent requirements for trade and transaction reporting (e.g. MiFID II, EMIR, CAT, etc.), where not only granular reporting is required, but also real-time performance and interface with central repositories. Another issue is identifying the practical purpose of data lineage. Often, data lineage is used to track the use of a particular data element in the assembling records of data from bottom up perspective at the downstream processes, on the other hand, someone else might want to track iteration upon the data from the reverse direction, top-down, starting with a particular end-product report and examining its construction from a business logic or risk analysis based perspective. In all scenarios, a robust data lineage should create a data environment with high quality controls, documentation and governance mechanisms established to align with business goals.
While most FIs believe regulators will continue to increase requirements for data capabilities only a few of them have begun to use data strategically to streamline and optimise business process and ultimately, support business growth. Data lineage can be the roadmap to new business models, innovation and be the enabler to align programs with the overarching data vision and strategy. To this end, CEOs and senior executives should link data content & metadata using a data lineage tool across systems and applications. The data lineage tool could act as your GPS navigation system to establish data governance processes. Such a data governance approach would drive the business growth and make operations more optimal and profitable.
To summarise, CEOs and senior executives should think strategically about their data and recognise that in our current volatile environment, it is paramount to access quickly high quality and “trusted” business information with an integrated while detailed and governed view of data assets. Tactical approaches and manual processes used to capture lineage and even documenting lineage in “Excel” are not sustainable and create operational inefficiencies when building data governance process and delivering an end-to-end accountability for data.