On Data Governance. Interview with David Saul.
“The increasing complexity and pace of global regulations is making it more difficult and expensive for financial services organizations to comply. At the same time, firms want to derive value from their data assets. How do they create synergy between these two seemingly divergent goals? The maturation of semantic technologies, when combined with increased acceptance of industry standards, holds out the promise of resolving those issues.” –David Saul.
I have interviewed David Saul, Senior Vice President and Chief Scientist at State Street Corporation. Main topics of the interview are the governance and management of data, and semantic technologies.
Q1. What is your role at State Street Bank?
David Saul: State Street has a long history as an innovator in financial services and my objective is to help maintain that leadership position. I work with our clients, internal developers, vendors, regulators and academics to identify and introduce appropriate innovations into our business. For the last several years I have focused on the development and adoption of semantic data standards.
The concept of the semantic web was first proposed over ten years ago by Sir Tim Berners-Lee, the creator of the World Wide Web, and has since been realized in multiple implementations. Semantics is a natural evolution of earlier work on metadata, language dialects and taxonomies for regulatory compliance. Examples include the SEC’s XBRL mandate and OFR’s Legal Entity Identifier (LEI) as part of the Dodd-Frank legislation.
Q2. What is Data Governance?
David Saul: State Street’s most important asset is the data that we ingest, process, store and distribute on behalf of our clients. Data Governance encompasses the management and controls needed to maintain stewardship of that data while in our custody.
Effective data governance can be measured by the ability to answer the following four questions:
- Do you know where your data is? Are you able to identify the critical business data in the firm, who owns it and, most importantly, and what it means?
- Do you maintain a catalog and monitor current and future regulatory requirements?
- Do you understand the existing products/services solutions used and can you identify any gaps?
- Do you participate in and influence relevant industry data standards?
Q3. What makes a good Data Governance Program?
David Saul: A mature Data Governance program provides a balanced framework to monetize data while also complying with regulatory requirements. The application of semantic data standards allows synergy between data analytics and risk management.
One example is the Financial Industry Business Ontology (FIBO) from the Enterprise Data Management (EDM) Council and the Object Management Group (OMG). Recent publications from regulators in the US and elsewhere have endorsed the use of data standards as the only way to deal with the increase in the scope and complexity of their responsibilities. For example, in its 2014 Annual Report the US Treasury Office of Financial Research (OFR) devotes its entire section 5 to “Advancing Data Standards”.
Semantics provides additional advantages over traditional technologies in its speed and flexibility. Developing Extract, Transform and Load (ETL) processes and data warehouses cannot keep pace with changes in business models and relevant regulations. The ability to easily create and change semantic maps of data ecosystems is being offered today by a number of vendors. The open nature of data standards like FIBO not only provides transparency but also provides assurance that these standards will be long lasting. Current academic research is showing our semantics can be a path into more leading edge technologies like machine learning and natural language.
Q4. How do you handle possible organizational conflicts from overlapping functions when dealing with Data?
David Saul: Effective governance and management of data requires a balance between distributed ownership and centralized control. The organizational role of the chief data officer at State Street has evolved to provide centralized policies, procedures and controls for data stewardship while maintaining operational management within the business processing units.
Beyond individual institutions, the application of data standards provides benefits to multiple constituencies:
- Financial services firms gain additional revenue from their clients while keeping risks at an acceptable level.
- Product and services companies have clearer requirements to innovate, develop and sell.
- Regulators and supervisors receive the information they need to meet statutory mandates and ensure that laws are complied with.
- Standards organizations follow their mission to enable simple and effective communication among the parties.
Q5. What are the main challenges in corporate, financial services, and regulatory sectors, especially on issues of Big Data, Analytics, and Risk Management?
David Saul: The increasing complexity and pace of global regulations is making it more difficult and expensive for financial services organizations to comply. At the same time, firms want to derive value from their data assets. How do they create synergy between these two seemingly divergent goals? The maturation of semantic technologies, when combined with increased acceptance of industry standards, holds out the promise of resolving those issues. Semantics and ontologies provide greater transparency and interoperability, thereby enhancing the overall trust in the financial system. Enhanced trust benefits all constituencies who have a direct interest.
Q6. You previously contributed to the Financial Stability Board Data Gaps Implementation Group. What are the main contributions of such group?
David Saul: State Street is an advocate for global data harmonization in multiple forums. Contributing expertise to industry associations and standards bodies benefits both the firm and the industry as a whole. Just one example is the International Organization of Securities Commissions (IOSCO) work on the financial industry Unique Product Identifier (UPI).
Q7. You also contributed to the White House Task Force on Smart Disclosure. What are the main results obtained?
David Saul: On May 9, 2014, President Barack Obama signed the Digital Accountability and Transparency Act, or the DATA Act, which had been passed unanimously by both the House of Representatives and the Senate. It requires the Department of the Treasury and the White House Office of Management and Budget to transform U.S. federal spending from disconnected documents into open, standardized data, and to publish that data online. State Street was among stakeholders from the tech industry, nonprofit sector, and executive and legislative branches of government who convened in May 2016 at the DATA Act Summit to build a shared vision for making the DATA Act a success.
David Saul, Senior Vice President and Chief Scientist, State Street Corporation.
David Saul is a senior vice president and chief scientist at State Street Corporation, reporting to the chief information officer. In this role, he proposes and assesses new advanced technologies for the organization, and also evaluates existing technologies and their likely evolution to reinforce the organization’s leadership position in financial services.
Mr. Saul previously was chief information security officer, where he oversaw State Street’s corporate information security program, controls and technology. Prior to that, he managed State Street’s Office of Architecture, where he was responsible for the overall enterprise technology, data and security architecture of the corporation.
Mr. Saul joined State Street in 1992 after 15 years with IBM’s Cambridge Scientific Center, where he managed innovations in operating systems virtualization, multiprocessing, networking and personal computers.
Mr. Saul serves as a trustee of the Massachusetts Eye and Ear Infirmary. In 2007, he was honored with a Computerworld Premier 100 IT Leader Award. He holds his bachelor’s and master’s degrees from the Massachusetts Institute of Technology.
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