Over the past decade or so, the financial services industry has witnessed a significant increase in new regulation. The initial primary driver of this new regulation was the 2008-2009 Financial Crisis (or ‘Credit Crunch’) which saw an increase in credit spreads against government secured lending due to concerns regarding the credit worthiness of certain financial institutions. This caused liquidity issues for the financial sector which in turn led to several financial institutions failing, including Bear Stearns and Lehman Brothers in 2008. In addition, various banks considered ‘too big to fail’ required government funding in order to remain operational during this time.
In response to this, various governments worked together to agree a set of principles to prevent such a chain of events from occurring again. This culminated in a set of commitments made in 2009 by the G20 in Pittsburgh to promote greater transparency, increase trade and transaction reporting, and move to centralised clearing of derivatives. In addition, initiatives such as Basel III looked to enhance capital provision within the industry so that a large set of bailouts – such as those seen in 2008-2009 – would not be needed again. More recently we have also seen a significant focus on ESG reporting obligations, with the EU, UK and other jurisdictions outlining additional reporting requirements within this domain.
Whilst the exact rules and subsequent requirements vary across legislation and geographies, one constant theme has been the requirement for more data. Here we explore some of the areas where firms may be able to extract additional business value from data, above and beyond regulatory compliance. We also look at what this means for regulators as they access and digest the available data.
Whilst the exact rules and subsequent requirements vary across legislation and geographies, one constant theme has been the requirement for more data.
The extended reporting requirements made both directly to the regulator and also to the wider market have given financial institutions access to significantly more information regarding the amount and types of transactions performed with clients and within the broader market. Given this enhanced data availability, some firms are capturing the data with a view to analysing it using a variety of analytics or other toolsets (such as AI) to draw inferences that can be used in future decision making.
For example, data collected from the market may highlight enhanced client interest in a certain product or service. By analysing other variables, a firm may then decide to amend the marketing and sales strategy accordingly. Similarly, firms may also consider prices published and contrast with their own models in order to ascertain if any changes in the pricing strategy may need to be considered.
Implementing a successful regulatory response within the structure of a business requires that organisations incorporate operating model considerations into their programme. In particular, firms need to incorporate new regulatory business requirements into their existing operating model to highlight any potential gaps or other insights that can be utilised within the revised target operating model (or TOM).
Within this target operating model design, organisations should also consider the use of KPIs and other metrics to dynamically capture operational performance. A focus on metrics is a key component in measuring the efficiency and robustness of a firm’s operating model in a post regulatory environment.
A focus on metrics is a key component in measuring the efficiency and robustness of a firm’s operating model in a post regulatory environment.
Ensuring continued regulatory compliance over time relies on a robust set of controls, policies, and procedures being put in place. The objective of these measures is to ensure that ongoing compliance is achieved as part of ‘business as usual’ and that any potential issues can be picked up internally and potentially rectified by the firm before a regulatory breach is identified by the regulator or other parties. Depending on the exact use case in question, the techniques and processes used to implement these measures may often be leveraged in other areas to proactively reduce operational errors, improve productivity, and enhance opportunities for further straight-through-processing.
Given current climate concerns and the push towards net zero in most developed countries, we have seen a significant increase in ESG (Environmental, Social and Governance) reporting requirements since the start of the decade. This means that organisations must now effectively source and manage their environmental and climate related data to create a more complete internal view of their current ESG position and start to construct an action plan to achieve net zero. As we move through the next decade, this will be seen as increasingly important in the eyes of clients, investors, and other key stakeholders as more and more decisions are based on ESG credentials, proving that the value of ESG data goes beyond reporting requirements.
As we move through the next decade, ESG reporting requirements will be seen as increasingly important in the eyes of clients, investors, and other key stakeholders.
With the increase in data now available to global regulators comes heightened challenges regarding how this data is accessed and analysed in a timely manner. As part of this, we expect a key regulatory theme to be a movement from data ‘push’ to data ‘pull’, whereby regulators can access all regulatory data from one reporting database. This trend may help regulators to highlight any inconsistencies in the reported data that may not have been picked up on when using separate reports.
In addition, this enables regulators to spend less time combining data from different sources and facilitates analysis of the bigger picture. This will allow regulators to more quickly highlight any concerns from a prudential regulatory perspective and raise them directly with the regulated firms. With this in mind, regulated firms will need to be more proactive in identifying any potential issues regarding data quality or completeness early on so that they can be adequately resolved before being raised by the regulators.
As the above examples highlight, regulatory data can often have powerful business impacts over and above pure regulatory compliance. Although there is often a natural tendency to move on after achieving compliance with a major regulatory milestone, it is frequently beneficial to understand what advantages can be brought to an organisation after the heavy lifting of sourcing and managing the necessary data has been achieved. Regulation can often bring business or market changes and organisations may find that business advantages accrue following the regulation go-live. Nevertheless, these advantages will rarely be realised without the necessary investment in time, resources, and management focus.
Regulatory data can often have powerful business impacts over and above pure regulatory compliance.
With dedicated practices in data and risk and compliance, Projective Group are uniquely placed to help organisations realise the benefits from their regulatory data. To speak to one of our experts, please contact us here.
Established in 2006, Projective Group is a leading Financial Services change specialist.
We are recognised within the industry as a complete solutions provider, partnering with clients in Financial Services to provide resolutions that are both holistic and pragmatic. We have evolved to become a trusted partner for companies that want to thrive and prosper in an ever-changing Financial Services landscape.
