SIBOS
Embracing change From creative destruction to disruptive technology, Alex Tsigutkin, CEO of AxiomSL, is finding alternative ways to deal with the new normal Some of you might remember Harvard professor and economist Joseph Schumpeter, who believed that creative destruction was what a firm faced when the choices that once drove its success become those that destroy its future. Many more theories followed, including the innovator’s dilemma, disruptive innovation and disruptive technology, to mention only a few. Today, between the UK’s vote for Brexit, Donald Trump’s successful bid for the White House, 2017 elections in Europe, a slowdown in Chinese economic growth and other world economic factors, the old order is being turned upside down. So how do financial institutions (FIs) ensure sustained growth in this unpredictable geopolitical climate, with ever-changing regulatory regimes and market margins that are under pressure? To identify and recognise opportunities that originate from turmoil, they should create an innovative technological environment that will adapt quickly to these paradigm shifts. A flexible, data-driven technology with strong controls combined with data and process governance are the foundation to meet those demands. To this end, we have seen the financial services industry make significant investments in risk and regulatory compliance systems over the last few years. Today, with technology budgets tightening, firms have to leverage existing processes and enhance their capability to integrate them effectively with remaining legacy systems to address internal management changes and evolving regulatory regimes. Many studies concur with that approach and analysts predominantly suggest that firms need to adopt a technology platform that can be leveraged repeatedly and across projects and applications to be cost-effective, reduce time to market and achieve sustainable growth. Complying with the multitude of
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regulations is a complex, time-consuming and costly activity, especially when the regulatory bar keeps rising to meet global standards, such as BCBS 239, or regional standards, such as US Federal Reserve CFO Attestation. These industry initiatives have pushed data lineage to the fore. In the past, data lineage was a concern primarily of the back office and auditing function; 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 without being overwhelmed by them. The cornerstone of data governance begins with data lineage. Let’s use an analogy with a GPS system. Imagine driving on a long journey equipped with
Manual processes used to capture data lineage in Excel are not sustainable only a 20-year-old paper map. The chances that you will take the shortest and safest route and get there on time are very slim. GPS was revolutionary because it provided us with an easy-to-use navigational tool that told us the direction for each turn you needed to take to reach your destination. Today, regulatory bodies closely examine FIs’ 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 to submit regulatory reports using XBRL, which require prescribed data point taxonomies. As a result, senior executives need to find a reliable tool to get their firms to a data governance strategic advantage point in a
cost-effective and sustainable manner. Let’s look at some data challenges that 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 a high volume of disparate data sets; managing business requirements and processes through legacy corporate data warehouses; and data lakes becoming extremely challenging projects. Systems are ill-equipped to handle these demands and outside of these technical challenges, business and IT leaders are not working collaboratively, which has exacerbated firms’ data problems. To address these challenges and rising global and regional standards, many FIs have begun evaluation and implementation of data lineage tools. However, getting data lineage right is difficult work, starting with the metadata. Some of it is incomplete and when it is available, it is often dispersed. Even when it is effectively funnelled 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 examples of this are the recent requirements for trade and transaction reporting – e.g. the second Markets in Financial Instruments Directive (MiFID II), the European Market Infrastructure Regulation (EMIR) and Consolidated Audit Trail – 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 it is used to track the use of a particular data element in assembling records of data from a bottom-up perspective at the downstream processes. On the other hand, someone else might want to track iteration upon the data from the top-down direction, starting with a particular end-product report and Autumn 2017