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

Regnology explores how – with the appropriate platforms, partners and processes in place – supervisory technology can be utilised as a driver of transformation.

Central banks are facing a big data problem. Amid rapid innovation and steadily increasing regulation across the financial landscape, the number of firms and disclosures they must supervise is increasing rapidly and is straining limited resources.

Regulators have a constant incentive to demand additional information in reporting – the more timely and granular the data, the better they can spot vulnerabilities and detect critical risks, leading to more effective supervision. The logical extension of this desire for granularity is to entirely do away with time- and template-based reporting cycles, which provide only point-in-time snapshots, in favour of an automated data flow between regulators and the regulated. 

Collecting, assessing and applying data at this scale is incredibly complex, so central banks have made various efforts to implement supervisory technology – known as suptech – solutions. But, despite the presence of innovation labs and other internal working groups, many of these initiatives face challenges getting off the ground because of skill gaps and limited bandwidth. With staff often pulled in too many directions, vital supervisory work winds up taking precedence over suptech innovation – even if these initiatives could lead to long-term benefits.

But simply having a solution in place is not a silver bullet. At its most transformative, suptech can unlock the potential of mountains of data, robust communication workflows and deep regulatory knowledge. At its best, it can serve as a springboard to more comprehensive risk oversight and better, more useful regulations. To achieve this exciting vision, central banks need modern systems and a plan to bring it all together.

Data deluge: why a holistic approach is essential

When it comes to data, central banks need efficiencies in two core areas: collection and analytics. This should not be an either/or proposition. Getting the most out of suptech necessitates a unified approach, with a clear plan for advancing both pillars.

This isn’t always how it plays out. Regulators often opt to put data collection challenges on the back burner in favour of evolving their approaches to analytics. After all, artificial intelligence and machine learning remain major buzzwords – new capabilities are always being released, and debates on their transformative potential loom large in industry discourse. Focusing on the most exciting and seemingly impactful parts of the process seems natural.

But this approach ignores data only being as useful as it is accurate – next‑generation analytical capabilities won’t lead to more effective supervision if the underlying data is of a low quality. Central banks that want to truly achieve data transformation must do so holistically. The focus should be on creating seamless supervisory workflows across the data spectrum, from collection and analytics all the way to decisions and approvals, robust documentation and auditable processes. 

The Covid-19 pandemic has only exacerbated this problem. Thanks to lockdowns and social distancing protocols, many central banks were prevented from visiting offices in their jurisdictions for months or even years, severely increasing the difficulty of on-site examinations. Central banks that invested in suptech prior to the pandemic – particularly solutions for digital communication and data sharing – were better prepared for this unprecedented disruption. While most jurisdictions have now fully reopened, the lessons learned will linger. Regulators cannot afford to have their supervisory activities curtailed by the next black swan event.

A platform for efficiency: three keys to suptech success

All this leaves central banks at a crossroads. The status quo is untenable, but building a proprietary system that reflects these considerations is nearly impossible – technology budgets simply aren’t large enough. That means the most logical way forward is usually to work with a third-party suptech provider with the necessary skills and experience. Regnology’s work with central banks and financial regulators worldwide has offered a unique perspective on how technology can be leveraged to make suptech visions a reality.

Regnology’s work technologically enabling the transformation and modernisation initiative of one European central bank is a good example of how flexible, scalable technology can drive efficiencies across the board. In an effort to treat regulatory data as an asset containing valuable information, this central bank is focusing on data maturity across the organisation, from collection to analysis to dissemination. The goal is to enrich all manner of insights and create a more resilient financial ecosystem.

It’s a long road to get to that point, but one worth travelling. To reach your own destination, consider the following keys to success.

Flexible, scalable technology

Suptech should never hold you back. Central banks looking to transform their approach to data must have the flexibility to handle an array of data management challenges, new legislation and more – and that begins at an architectural level.

The cloud has revolutionised data management, unlocking a level of scalability and elasticity that central banks increasingly need to support granular data. Through enhanced computational performance, they can focus less on processing highly sensitive data and more on actually working with it. Every minute a regulator spends worrying about minutiae, such as increasing server RAM, is time that cannot be spent on core supervisory functions, so working with a trusted third party is usually the optimal approach.

While modern cloud security is highly advanced and continuously improving, there remain concerns, and adoption has thus been slow in many jurisdictions. Central banks yet to migrate should consider the risks of the status quo versus the benefits of increased data granularity. In some cases, the answer may lie in a hybrid model, with cloud-based tools running in concert with certain on‑premise solutions.

Along the same lines, suptech should be able to integrate and communicate with just about any other system or content in the supervisory workflow. This article will offer examples of this flexibility, but one area in which it can lead to powerful results is analytics. For example, a suptech platform might include microservices that can run machine learning algorithms to identify anomalies, enabling users to better assess risk and make more informed decisions.

Collaboration and communication

New and granular reporting requirements can be highly burdensome for central banks and for the firms they supervise. To combat this, suptech must facilitate smooth communication and collaboration between these entities at every step of the process. With a technology infrastructure serving as a connecting hub between regulators and the regulated, the flow of information becomes seamless and much closer to real time. 

For example, much of the friction around data quality stems from misinterpretation of the information central banks are requesting – particularly when it comes to aggregated fields. Definitions can vary, and the context may shift depending on the firm or department in question, the types of customers they serve and more. 

Shared data models and data exchange via an application programming interface (API) can eliminate the risk of this ambiguity, making it far easier for central banks to collect the granular data they need. Instead of periodic reports on large exposures, for example, they can view a bank’s full loan book, set their own parameters and perform their own analysis of where the risk lies. By increasing the accuracy of initial collection, information gaps are reduced, aggregation is eased and validation rules such as variance analysis and plausibility checks become that much more valuable. 

These benefits are present even at the most preliminary stages of a regulatory initiative. Instead of creating explanatory decks on new projects to gather input from regulated firms, central banks can share the actual code that will be used, enabling compliance teams to drill down into the nitty gritty. A simple exchange of PowerPoint files is not enough. This heightened level of communication and collaboration is the only way to evolve past time-based reporting cycles and in‑person examinations. 

Suptech should also facilitate real-time communication with the regulated, so regulators can send back queries on reviewing the data. Once a new regulatory framework has successfully been rolled out, the platform should give central banks the ability to share their data models and reporting workflows not just with the firms they regulate, but with other regulators as well.

None of this is possible without the right tools for interaction – and shared data models and API connectivity represent the way forward.

Global and local expertise

All the communication in the world won’t mean much if specific legal and jurisdictional considerations are not accounted for. Suptech must be able to reflect any set of rules and requirements and should, ideally, come with access to people with deep experience bringing these solutions to market.

The key here is versatility. The system should offer prebuilt templates for widely applicable regulations out of the box – such as European Union Solvency II regulations – but also a strong ability to implement specific content and rules supplied by the central banks themselves. After all, each regulator has its own supervisory processes and experiences its own pain points. But, while there’s no substitute for localised inputs, effective supervision requires a global perspective as well.

For example, Regnology recently worked with two central banks – one in North America and one in Asia‑Pacific – to upgrade their data collections to conform with the final phase of Basel III. Working on these projects simultaneously offered the opportunity to assess implementation in different jurisdictions and solve mutual issues. Now Regnology can leverage this experience to assist other clients. This global experience can provide other central banks a solid foundation for compliance so their work to adapt to new requirements doesn’t need to start from scratch.

Of course, there are also times when central banks must perform supervision that is highly specific to their jurisdiction. In one recent proof of concept, Regnology worked with a North American regulator to assess how climate events might impact the risk of bank defaults. This required the regulator to input its own highly complex data model to our platform – on weather patterns, disaster response preparedness and more. The result was another example of the powerful combination of platform flexibility and regulatory expertise.

With more than 800 staff working from 14 offices worldwide, Regnology brings the skills and knowledge to help central banks more efficiently implement new regulations and manage related data – no matter where in the world they are. 

Conclusion: taking action to create the future of suptech

The right approach is valuable, but only insofar as it can be translated into action. This article offers a few key principles and concludes with some best practices. 

It’s usually best for central banks to take a phased approach, focusing on one function at a time. This is especially true for regulators in the early days of their suptech evolution – working at a smaller scale allows them to freely experiment and pore over results. This is not mutually exclusive with a holistic approach. Any initiative should be mapped to a larger suptech strategy, and lessons learned incorporated throughout the organisation.

Another key is vendor collaboration. Outsourcing a project does not mean the work is completely removed from the central bank’s docket – managing each provider requires resources, and the more voices brought into the process, the greater the risk of logistical difficulties and delays. Because of this, finding proven partners that can easily collaborate and integrate is often a good approach.

Finally, there is no substitute for ongoing person-to-person dialogue. By sharing their perspectives, engaging in debate and collaborating closely on regulatory and compliance initiatives, regulators and the regulated can realise benefits far beyond streamlining data operations and enabling resource reallocation. With smoother reporting workflows that support data granularity, communication protocols that enhance collaboration and open systems that support any kind of integration, central banks can drive a convergence of regulatory technology and suptech, creating a new status quo with transformative benefits for all parties. 

In pursuing this path, central banks can leverage suptech not as a mere efficiency play, but a true driver of transformation across their jurisdiction. It all starts with having the right platform, partner and process.

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