Emerging regulation for life insurers: model, credit and liquidity risk on the rise
At a glance
- Regulators continue to extend and develop their expectations for Non-Bank Financial Institutions (NBFIs). Many regulatory initiatives that were initially aimed at banks are now being extended to other financial market participants; life insurers are no exception.
- Insurance regulators are increasingly interested in three key areas: model, credit and liquidity risk management. For all of these, banks have been under more scrutiny for longer. Insurers that ask themselves what they can learn from banks’ experience to supplement their current approaches will be better prepared for what is to come.
- Now is the time to explore the lessons learnt by banks and blend them with the unique characteristics of the insurance business model, and to consider any areas that might require enhancement before any new rules are finalised.
Context
Regulators are increasingly focusing their attention on the risks posed by NBFIs, including insurers. In the last few years, regulators have extended several regulatory initiatives that were initially targeted at banks to insurers. These include insurance-specific recovery and resolution regimes (and, in the UK, solvent exit rules), and further expectations around stress and scenario testing for insurers (see our detailed article here).
In this article, we explore three key areas where we expect regulators to extend and develop their expectations for insurers in the near future: model risk, credit risk and liquidity risk management. We explore lessons learnt from banks’ experiences of implementing rules and expectations in these three areas, what to expect from the application of similar requirements to the insurance business model and what actions insurers can take to prepare for regulatory scrutiny in these areas. This article is specifically targeted at life insurers, but some elements (such as model risk management (MRM)) are also relevant to general insurers.
- MRM: more models, more scrutiny
The new MRM principles for banks (SS1/23) came into effect in May 2024 (see our article here). Although the PRA has not yet extended its MRM principles to insurers, it now appears more a matter of “when” and “how” than “if”. The Financial Reporting Council (FRC) issued Technical Actuarial Guidance on models used in technical actuarial work in October 2024. This guidance will be applicable to a variety of models used in insurance and is well aligned to the MRM principles for banks in SS1/23. We think it is only a matter of a relatively short time before the PRA does apply its MRM principles to insurers. In the meantime, the PRA has reminded insurers to “take proactive steps to assess the adequacy of their risk management and control frameworks” and “reassure themselves of the continued validity of their models, including the extent to which model risk management principles for banks [SS1/23] could be applied and, in particular, whether current validation remains robust in the face of multiple concurrent stresses”1.
With Solvency UK (SUK) reform now completed, we expect the PRA to start thinking about MRM for insurers in 2025. As was the case for banks, we expect the rules to be extended first to insurers with an approved internal model (IM), although we also expect the PRA to re-iterate that all insurers (including those on the Standard Formula) should assess and manage model risk appropriately. We understand that several insurers have already started to review their models, frameworks and related processes in light of the MRM principles for banks.
|
|
|
|---|---|
|
MRM challenges |
Actions for insurers |
|
1. Scope We expect insurers will have to contend with a much broader definition of a model, just as banks had to do, capturing quantitative methods that were previously not considered sources of model risk. While insurers generally have a robust management of their IM under SUK, they need to make sure all models are subject to appropriate oversight and risk management, particularly those outside of financial or regulatory reporting processes. More fundamentally, insurers need to reflect on the definition of model risk itself to ensure the risk of making poor decisions based on models’ outputs is appropriately understood and managed. |
|
|
2. Driving efficiencies Some banks have been able to benefit from identifying potential synergies between different model-related projects and drive efficiencies. This has enabled them to make optimal use of scarce model expertise and resources (e.g., work on models for IFRS9 and Basel 3.1). Insurers could also explore this to avoid duplication of efforts and use actuarial teams more effectively, while also anticipating the potential MRM principles for insurers. |
|
|
3. Artificial Intelligence (AI) including Generative AI (GenAI) model uses are also captured by the new definition of models. Insurers are starting to update MRM Frameworks for AI/ML models, but few have standards that capture the incremental risks of GenAI uses2. |
|
2. Credit risk management: enhancing capabilities
Insurers are exposed to credit risk mainly through their investments and derivative exposures. By expanding the universe of assets that life insurers can invest in, SUK reforms (including investment flexibility and MA attestation reforms) have reinforced the need for effective credit risk management for the UK life insurance sector.
Although insurers already have considerable experience in credit risk modelling, increasing investment in illiquid assets could present new credit risk challenges. These are asset classes where lack of data and appropriate calibration methodologies can present significant challenges to determining the capital treatment and the internal valuation and rating approaches. Understanding these types of assets will also likely require specialist knowledge and expertise.
|
|
|
|---|---|
|
Credit risk management challenges |
Actions for insurers |
|
1. Risk appetite and limits |
|
|
2. Internal valuation and rating processes |
|
|
3. Governance and MI The PRA recently identified an absence of credit risk appetite metrics in MI, inconsistency in portfolio monitoring of credit risk MI, and data reporting issues for banks. These could signpost areas where insurers might want to focus their attention. |
|
3. Liquidity Risk Management: reporting first
Regulators will start collecting more data on insurers’ liquidity positions through more frequent and regular reporting, particularly given “[m]arket-wide stresses in March 2020 and September 2022 [that] led to liquidity strains for some insurers as well as highlighting gaps in insurers’ liquidity risk frameworks”.
The PRA recently consulted on new liquidity risk reporting rules, proposing more granular and frequent liquidity reporting for large insurers with significant exposure to derivatives or securities in lending or repurchase agreements.
While not requiring insurers to submit as much detail as banks, the new templates are extensive (3,000 new reporting data cells) and will require insurers to amend systems to accommodate more detailed information on liquidity risk, particularly around margin or collateral calls. It will also require updating reporting risk and control frameworks to ensure accurate, timely and consistent liquidity reporting output. The proposed implementation date for the new reporting requirements is the end of 2025.
Although we are aware that the PRA has engaged extensively with the industry prior to the consultation, we expect significant push-back given the extent of the proposals and high costs involved.
|
|
|
|---|---|
|
Liquidity risk management challenges |
Actions for insurers |
|
1. Risk management Although life insurers do not have the same liquidity risks as banks (through e.g. |
|
|
2. Reporting Many insurers will still face challenges in getting the required granular liquidity data ready within shorter or more frequent time periods than the usual quarterly reporting timeframes. If the PRA proceeds with implementing the final rules by 31 December 2025, insurers have relatively little time to update their reporting IT systems and controls to incorporate the new templates and data. |
|
|
3. Stress and scenario testing Stress and scenario testing will be key for insurers to understand how their |
|
Conclusion
There are several areas where insurers will need to follow on the footsteps of banks down a long and winding road. As interconnectedness increases throughout the economy in general and the financial system in particular, it is natural that regulators will apply the experience they have gained from their work in the banking sector to insurance.
Insurers will therefore be expected to comply with increasing expectations and requirements when it comes to model, credit and liquidity risk management, and should learn what is relevant from banks’ experience in these areas to supplement their existing expertise. This will enable insurers to develop an approach to managing these risks that is proportionate and aligned to the features of the insurance business model and achieve a smoother and more effective implementation of the new requirements and expectations.
