Data governance, operations automation, data quality, regulation, blockchain technology, Know your Customer (KYC) and client onboarding were among the hot topics discussed at this week’s A-Team Group Data Management Summit in London.
The first keynote of the day, Data Governance – Winning Hearts and Minds, was presented by Kevin Ayling, head of data quality governance and controls, and Rob Thornewell, data management policy reporting manager, at Royal Bank of Scotland (RBS). They told a compelling story about how data governance is being embedded across the bank, starting with the need to make sure core data is correct and accessible to the staff who need it, and moving on to detail the cultural change and training programmes required to help staff understand, appreciate and engage in data governance.
Ayling explained: “You need to talk to people at a personal level about how data governance will affect them and change culture across the organisation. This takes time. About 300 staff have done our training course and more want to do it. We are definitely winning hearts and minds, data is improving, and everyone is talking about data.”
Dennis Slattery, CEO of EDMworks, which partnered RBS to develop and deliver its training courses, also covered data governance at the Data Management Summit, leading a panel discussion that noted regulatory requirements to improve data governance, but also improvement driven by understanding, education and communication. Considering the do’s and don’ts of data governance, the panel suggested firms should start with small wins and scale up, but should not start without a framework and senior management backing.
Looking at data operations automation, Andy Steele, global head of data operations at Barclays, outlined the bank’s transition from a cost efficiency to a client and regulatory driven strategy, and discussed its use of automation to solve some reference data challenges. Among the automation tools being used or considered by the bank are robotic process automation, cognitive technologies and workflow automation.
While automation is a next step for many banks, Steele said: “The challenge of automation projects is finding the right price point. Software investment is high, but what are the efficiency gains?” Having learnt lessons from early automation projects, he suggested a lean approach to data management before automation and the need for a toolbox of automation solutions rather than dependency on one automation technology.
The Data Management Summit also focussed on data quality, discussing issues including how to define data quality, how to measure it and how to implement it during a time of cost constraint. Practitioners from organisations including RBS, Clydesdale Bank and Deutsche Bank described practical approaches to improving data quality – and the need to win hearts and minds – while practitioners from Legal & General Investment Management, Northern Trust, HSBC and RBS considered the types of technologies that can help financial institutions drive up data quality.
KYC and customer onboarding was another hot topic, with a panel highlighting the need for development projects to focus as much, or even more, on the client as the bank, and aim for an end solution that provides a single service for KYC and onboarding across the enterprise. Again, this will take time, but the outcome is significant in terms of new business opportunities and gaining competitive advantage.
Among the technology solutions presented at the Data Management Summit were SmartStream’s industry-backed Reference Data Utility that mutualises reference data management to reduce costs and increase data quality, and blockchain, or distributed ledger, technology.
Presenting the potential of blockchain technology in data management, John Bertrand, industry value engineer – banking, at SAP, described blockchain as a ‘supreme friend’ to data management as it supports a complete history and provenance of data through its lifecycle, a single source of the truth that can be seen by many, control, security and transparency. It does not support data governance, data architecture, dashboards or predictive analytics. Whatever the pros and cons, Bertrand concluded: “The underlying requirements of data management are in blockchain technology. I think we can expect blockchain activities to start flowing in the next two or three years.”
Last but not least, and certainly not for the first time, regulation was under the spotlight at the Data Management Summit. Ongoing and expected hotspots identified by a panel of experts from both banks and data vendors included Solvency II, IFRS 9, KYC, BCBS 239, SFTR and forthcoming MiFID II regulation. Standard identifiers and data harmonisation across regulations were noted as beneficial aids to compliance, but not so regulators who make the rules but are not data management practitioners.
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