Drowning in Data - Regulators Need a Data Strategy Too!
The problem for regulators & for banks alike is agreeing what good data looks like & how to share it to create a modern, flexible, shared data model. Read more.
“The Foundation of good decision-making is good data.” So said Gareth Ramsey, Executive Director for Data at the Bank of England earlier this year. The problem for regulators and for banks alike is agreeing what good data looks like and how to share it. In the UK, the FCA and the Bank of England have taken the lead in exploring new ways to not only to reduce the cost of regulatory reporting but increase its utility. The European Central bank and national banks around the world are also exploring this exciting potential. At the heart of these efforts is desire to create a modern, flexible, shared data model.
Every year the FCA estimates that it receives over 500,000 scheduled regulatory reports from regulated businesses, and that’s before additional ad hoc reports. The flurry of regulations post 2008, plus increasingly wide-ranging reporting requirements for anti-money laundering, terrorism funding, cyber-risk and numerous other threats mean that both banks and their supervisors are struggling to produce and consume better data, faster. In the face of these demands regulatory reporting systems are creaking.
Today regulators are demanding more granular data to better assess risk. EU banks are still struggling to meet standardised requirements of BASEL III even with the recent COVID related delay. Regulators are not getting the data they’d like to better mitigate systemic risks, respond to external events and formulate good monetary policy in good time. Each bank interprets principle-based regulations in different ways. There is no ‘right’ way to do things which leads to duplication, overlap and confusion. Principles were established for individual pieces of the puzzle. Although rulebooks exist in each jurisdiction, they differ from each other and they often resemble a collection of chapters written by different authors for different stories in different languages!
Forward thinking regulators are driving a new and better approach. A new data strategy and Digital Regulatory Reporting (DRR) are central planks of the UK regulator’s response. At an EU level the Banks’ Integrated Reporting Dictionary (BIRD) is designed to create ‘a harmonised data model’. All are looking to better use data to predict outcomes and to reduce the burden of reporting on firms and the regulator itself. This shifts emphasis from principles and interpretation to a more definitive system of rules and definitions better-suited to the data-centric bank of the future.
Across the region most regulators are currently focusing on data standardisation as the first phase of digital reporting. The goal is to increase clarity and shared understanding around rules and data through a shared collaborative platform. In our world we recognise this as a shared data model – an agreed dictionary for a data-literate reporting system. Creation of this consistent data model is not only the heart of rules-driven reporting system but the key to increasing utility and speed whilst reducing workloads.
Creating reports that call for specific, consistent data removes the need for interpretation. If requirements change and new reports are needed, they can build on existing data. Currently new regulations often demand reports that share the same data just in different ways. The data model approach will avoid this. Automation of reporting becomes more straightforward saving time and money and increasing accuracy. Early pilots have been successful in demonstrating how these data models can work. The challenge now is scaling this technology-driven approach to cope with the thousands of reports and millions of data points that constitute a big bank’s regulatory reporting workload.
Collaboration with big data experts with deep sector experience is critical to deliver this new dawn of regulatory reporting. We are excited to see the groundwork being laid for machine-readable and automated reporting that can deliver higher quality reporting at lower cost. The logical next step would be to move to a pull-model. Creating standardised platforms to which banks can push data for regulators to access as needed could be a workable innovation in that direction. It may seem like science-fiction to many, but it has the promise of accurate, frictionless reporting that significantly reduces costs for banks.
Every year the FCA estimates that it receives over 500,000 scheduled regulatory reports from regulated businesses, and that’s before additional ad hoc reports. The flurry of regulations post 2008, plus increasingly wide-ranging reporting requirements for anti-money laundering, terrorism funding, cyber-risk and numerous other threats mean that both banks and their supervisors are struggling to produce and consume better data, faster. In the face of these demands regulatory reporting systems are creaking.
Today regulators are demanding more granular data to better assess risk. EU banks are still struggling to meet standardised requirements of BASEL III even with the recent COVID related delay. Regulators are not getting the data they’d like to better mitigate systemic risks, respond to external events and formulate good monetary policy in good time. Each bank interprets principle-based regulations in different ways. There is no ‘right’ way to do things which leads to duplication, overlap and confusion. Principles were established for individual pieces of the puzzle. Although rulebooks exist in each jurisdiction, they differ from each other and they often resemble a collection of chapters written by different authors for different stories in different languages!
Forward thinking regulators are driving a new and better approach. A new data strategy and Digital Regulatory Reporting (DRR) are central planks of the UK regulator’s response. At an EU level the Banks’ Integrated Reporting Dictionary (BIRD) is designed to create ‘a harmonised data model’. All are looking to better use data to predict outcomes and to reduce the burden of reporting on firms and the regulator itself. This shifts emphasis from principles and interpretation to a more definitive system of rules and definitions better-suited to the data-centric bank of the future.
Across the region most regulators are currently focusing on data standardisation as the first phase of digital reporting. The goal is to increase clarity and shared understanding around rules and data through a shared collaborative platform. In our world we recognise this as a shared data model – an agreed dictionary for a data-literate reporting system. Creation of this consistent data model is not only the heart of rules-driven reporting system but the key to increasing utility and speed whilst reducing workloads.
Creating reports that call for specific, consistent data removes the need for interpretation. If requirements change and new reports are needed, they can build on existing data. Currently new regulations often demand reports that share the same data just in different ways. The data model approach will avoid this. Automation of reporting becomes more straightforward saving time and money and increasing accuracy. Early pilots have been successful in demonstrating how these data models can work. The challenge now is scaling this technology-driven approach to cope with the thousands of reports and millions of data points that constitute a big bank’s regulatory reporting workload.
Collaboration with big data experts with deep sector experience is critical to deliver this new dawn of regulatory reporting. We are excited to see the groundwork being laid for machine-readable and automated reporting that can deliver higher quality reporting at lower cost. The logical next step would be to move to a pull-model. Creating standardised platforms to which banks can push data for regulators to access as needed could be a workable innovation in that direction. It may seem like science-fiction to many, but it has the promise of accurate, frictionless reporting that significantly reduces costs for banks.
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