As financial institutions worldwide struggle to process and interpret the enormous volumes of data their businesses must hold, how can Data on Demand create better regulatory reporting structures? 

Since the financial crash in 2008, financial regulators, including Central Banks, have scrutinised the financial institutions they oversee much more closely. Banks and other financial institutions must hold an enormous amount of data as a result.  With that comes the challenge of data management, resourcing, quality and timing for both regulators and their institutions.  

A joint report from the World Bank and Cambridge Centre for Alternative Finance, ‘2020 Global COVID-19 Fintech Regulatory Rapid Assessment Study' says that Covid-19 has pushed fintech up the agenda for regulators and financial institutions. As a result, regulators are facing key internal challenges. These include access to accurate and timely data (29%) and increased Demand on resources (29%).  

Some 58% of regulators worldwide have either accelerated or introduced RegTech/SupTech initiatives to address these challenges and the others listed in the report. 

Meanwhile, the European Commission believes the single digital market, including a data strategy and AI regulation, can become the "lifeblood of economic development".  

Granular Data and Data on Demand in regulatory reporting can help regulators address these opportunities and challenges and lead the way for next-generation financial supervision.  

Supervisory challenges and trends 

Financial Regulators are actively seeking to respond more quickly to emerging risk that can compromise financial stability. The increased focus on financial stability has resulted in changes in reporting requirements that have caused problems, including: 

  • Increased complexity and decreased quality in reporting 
  • Slower turnaround of supervisory activities 
  • Data management challenges – particularly around data interpretation and transformation 

The impact of failing to manage data optimally is more significant than ever, and financial instruments have become more complicated. As a result, financial regulators are seeking to: 

  • Reduce the regulatory burden 
  • Receive timely data 
  • Advance analytics capabilities 

Regulators are focusing on standardising regulatory data models, reducing duplication of data requests, and reducing data interpretation challenges for financial institutions. This focus means there is a clear need for Data on Demand in regulatory reporting, including automated reporting and machine-readable collections, and advanced analytics to unlock valuable information and support data-driven decisions and predict future trends. 

Granular Data and Data on Demand in regulatory reporting enables financial regulators to address complexity, turnaround, and data management issues. By providing a simpler, lower-level view of transactions, fewer calculations, transformations or aggregations are required. This facilitates reduced data validation requirements and well-defined data models where duplication is easily identified, and ambiguity is eradicated. 

Data on Demand is a term used to describe a financial regulator's goal to collect data seamlessly. The aims of Data on Demand in regulatory reporting are to: 

  • Receive more timely data 
  • Reduce human effort and 
  • Reduce human error 

With our Data on Demand offering, there are two types of automated reporting, "pull" where the regulator pulls data from the financial institution or "push" where the financial institution pushes their data to the regulator. Given there is ordinarily one financial regulator and many financial institutions to regulate, taking a "push" approach is more easily implemented, maintained and on-boarded. 

We have found with the rollout of Data on Demand with clients, including the regulator Bank of Ghana, that "push" is the preferred and more prudent approach. Ultimately, either method will mean more timely data with reduced human effort, fewer errors, and better supervisory outcomes. 

Data on Demand in regulatory reporting: into action 

In an ever-changing financial world, financial regulators need to be proactive, adapting to the accelerated rate of change we see today. Regulators must be prepared to respond to plans to build on the European Commission's Open Data Directive in 2021, with plans to liberate high-value datasets held by public bodies. Granular data models can help regulators to innovate their approach to supervision. 

Our latest software release facilitates automated reporting and machine-to-machine data exchange between financial institutions, regulators, and other regulatory partners. The solution provides collections of API endpoints and connectors that allow financial institutions and external agencies to integrate with the Vizor SupTech Platform.

You might also be interested in

  • A SupTech transformation: using tech to support the full supervisory lifecycle


    A SupTech transformation: using tech to support the full supervisory lifecycle

    Central banks are facing a big data problem, the number of firms and disclosures they must supervise is increasing rapidly and is straining limited resources.

    Read more
  • AEOI building confidence in Latin America tax transparency 


    AEOI building confidence in Latin America tax transparency 

    Confidence is building in tax transparency in Latin America, according to a new OECD report. The report highlights the value of AEOI for tackling tax evasion.

    Read more
  • Strengthening data for better AEOI reporting


    Strengthening data for better AEOI reporting

    Data is a core part of transparency. As global standards evolve, tax authorities must be ready to provide more and better-quality data – having the right approach now will support future exchanges of information.

    Read more

Contact us