The Covid-19 crisis and the experience of 2021 have validated the role of technology in the regulatory regime for financial services. In a speech entitled ‘The necessity of using supervisory technology’, Pentti Hakkarainen, a member of the supervisory board of the ECB reinforced that message: “There is great potential to use technology to get the most from the large amounts of data available to banking supervisors. And digital solutions will offer efficiency gains that will allow supervisors to focus their time on the more constructive aspects of their work.”
One of the most productive technologies for streamlining and modernising the way financial regulators fulfil their role with financial services organisations is through the cloud. Recently published IDC figures show the significant inroads cloud is making among financial services organisations with predictions that spending on cloud services by banks will grow from $32.1bn in 2020 to $85bn in 2025.
Cloud is an ideal data exchange platform for regulators to access a firm’s data, run their own reporting and communicate in real-time with disparate systems. By accessing data from multiple systems, regulators can instantly view and analyse all relevant metrics, such as financial transactions, sales orders and stock levels and measure system risk in real-time.
The attractions are clear. Cloud technology can modernise interactions between regulators and financial firms and provide greater agility and scalability.
Trends in financial supervision are leading not just to more data but to greater data complexity and enhanced scrutiny of regulated entities.
These factors are creating significant data management challenges, particularly for data interpretation and transformation. Financial regulators are seeking to address these issues by working to reduce the regulatory burden and receive data in a more timely manner.
Regulatory data management is a crucial component of the regulatory life cycle. AI and machine learning are becoming more prominent as technologies that can be deployed to process the data and ease the burdens of complex data management.
The use of APIs allows financial institutions to consume machine-readable reporting rules and data models directly from regulators, increasing reporting quality, reducing the time and effort required for compliance, and minimising the risk of reporting errors.
By automating the collection of data, APIs provide the foundation for machine-to-machine (M2M) reporting and machine learning. Machine learning techniques are already used in regulatory reporting to extract historical data sets from data warehouses and identify previously considered trends. This knowledge can be transferred to assist in real-time regulation.
Regulators can integrate machine learning models into the data collection platform to generate predictions. Machine learning in regulatory reporting can add real value to the regulatory life cycle and address some of the challenges around data.
APIs enable seamless data and metadata exchange between different parties in machine-readable formats, combining a well-defined data model with open standards for data sharing to promote innovation. API connectors can push data to downstream systems, such as partner agencies, document management systems and ERP systems. Open APIs enable supervisors to share data quickly and maintain integrations at a lower cost.
The most efficient way for regulators and financial institutions to achieve their goals is to align the technology and software they use.
The impetus toward greater alignment of RegTech and SupTech in 2022 and beyond will achieve significant cost savings and enable resources to be used more efficiently. By fully aligning systems used by financial regulators and the institutions they oversee, they can eliminate duplication of effort, make the implementation of new regulations more straightforward and reduce the cost of fines for late or mistaken submissions.
The Australian Prudential Regulation Authority (APRA) is replacing its existing Direct to APRA (D2A) system with our data collection solution named APRA Connect. Under the new system, which went live in September 2021, regulatory changes can be validated and consumed instantly, and test submissions can be run against APRA Connect data validation rules to discover any failures or warnings. A powerful analytics dashboard includes full reports on performance, fund expenditures and insurance. The software is immediately aligned with current and future APRA Connecting reporting standards.
While Austria’s largest bank group, representing around 90% of the market has created a joint venture called Austrian Reporting Services (AuREP) to make it easier to evolve with the regulatory landscape. Processing over 1.4 billion records at each reporting date, it runs on Regnology’s software platform, creating an interface between the banks and Austria’s central bank Oesterreichische Nationalbank (OeNb).
The venture uses an input-based approach built on data cubes. The cubes are enriched with additional data and become ‘smart cubes.’ Each ‘smart cube’ is analysed, signed off and submitted to the OeNB. As a result of the programme, Austria has reduced the cost of regulatory reporting nationally and has reduced the instances of risk exposed to banks by changes in regulation.
Closer alignment of SupTech and RegTech creates a frictionless relationship between regulators and the regulated, replacing slow, outdated and expensive processes. It allows for a seamless flow of data and a clearer interpretation of regulations. Data quality is also improved. If processes are updated, RegTech and SupTech rules are kept in sync automatically so financial institutions are always using the very latest ruleset.
Advanced analytics is going to become increasingly valuable for regulators in 2022 and beyond. A core benefit of SupTech is the ability to identify trends and predict problems before they occur. AI and machine learning can be used to spot trends in data that would be almost invisible to the naked eye.
The European Central Bank is already using the technology to identify trends across multiple jurisdictions and using advanced analytical models to gain new insights from the vast amounts of data it holds. Using these analytics can offer financial regulators greater intelligence around trends.
To provide a concrete example, Andrea Enria, Chair of the supervisory board of the ECB, stated in a speech in September 2021 that “advanced analytics and applications help us to get the most from large quantities of data”.
Our experienced team of analysts is paying close attention to emerging Supervisory Technology trends. The benefits are clear in helping authorities enhance data collection and analysis, automate routine tasks, develop new analytical techniques, and provide better insights. Our team can help authorities understand how innovations in SupTech can improve their data collection, management capabilities and data quality.
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