Lessons Learnt from Covid-19 ... or Not?

Covid-19 is a health crisis, a business crisis and an economic crisis which has struck the insurance industry hard.

Claims spiked in some areas while volatile financial markets made it almost impossible to steer the investment portfolio, and lockdown measures kept staff at home while struggling to cope with surging call and claim volumes. Meanwhile, there is vocal pressure from some quarters for a “flexible” approach to claims, where “flexible” is shorthand for dishing out large amounts of money for claims which may or may not be covered.  

How has the industry coped, and what lessons has it learned?

To answer that question, Crescendo Advisors carried out a series of structured interviews with a selection of risk and finance professionals from insurance firms. Most of the firms were UK based, with an aggregate turnover of £120 billion in 2019.

Although the firms varied in size and portfolio mix, there was a high degree of consensus in their opinions. Here are Crescendo’s top five findings and conclusions:

• While most UK firms have weathered the crisis to date, it appears that few did so as laid out in their pre-Covid-19 business continuity planning.  Business continuity plans usually assumed local outbreaks and had to be re-created in the face of a total and global shutdown.

• All firms who viewed their lockdown experience as ‘successful’ attributed that to excellent, ongoing communication from senior management to all stakeholders;

• The traditional hostility to staff working from home has changed from “not possible” to “why not?”. Going forward firms expect staff to continue working at least part-time from home, and hence plan on reductions in their office footprint;

• As remote working and virtual teams have become the post-Covid vogue, the purpose and value of The Office is being critically re-evaluated. It may still be the best place for meetings and staff onboarding, but do we really need all those desks crowded together?

• With staff working remotely, the cost-benefit dynamic of outsourcing could be changed so that firms will find it beneficial and desirable to bring activities back in-house.

Interestingly, while most participants anticipated the need for a lessons learnt exercise, only one of them acknowledged at the time that his firm was already kicking off such an exercise.

Are insurers perhaps being complacent? They had six weeks to prepare for lockdown and they put the time to good use. By the time staff were required to stay home, many did so with newly acquired laptops and secure connections. The main limitations on productivity came from the lack of suitable home office facilities or from inadequate broadband speeds. The show stayed on the road with remarkably few wobbles.

Next year UK insurers are likely to work in the implementation of operational resilience requirements.  There are lessons to be learnt from Covid-19.  But here’s a thought, if working from home is no longer the backup disaster recovery plan – it is the new normal – what is the new disaster recovery plan?

This post has been written by Isaac Alfon (Managing Director) and Shirley Beglinger (Advisory Board Member) at Crescendo Advisors.  

Crescendo Advisors (www.crescendo-erm.com) is a boutique risk management consultancy.  We would be happy to share an overview of the findings of this survey.  We can also support your efforts to both learn lessons from Covid-19 using the tools we developed for this survey and consider the implications of working from home arrangements for the risk and control environment.

Operational Resilience

By Shirley Beglinger, Advisory Board Member, Crescendo Advisors

In today's interconnected financial world, "organisational resilience" must be taken to mean much more than just "a fully tested disaster recovery plan". Regulators are requiring boards to see beyond the walls of their own firm and identify its position in the economic, IT and service-delivery ecosystem with an emphasis on important services provided. This is a completely different perspective on risk.  Boards and CROs need to reconsider many tried and tested risk methodologies and metrics.

In reviewing the drivers of potential operational disruption, the CRO may identify several which are difficult or expensive to address. "Reliance on legacy infrastructure" for example will likely lead to a lengthy boardroom discussion of the expense and dangers of IT integration projects. Supply chains and data sharing quickly lead to the realisation that even if the firm's own arrangements are top-notch, there are probably other firms in their ecosystem who may not have the same level of preparedness.

Having identified potential sources of disruption, the board must then quantify potential costs (internal and external) and assess the ability to recover from severe and plausible scenarios of operational disruption and compare these with the firm's stated tolerance for operational disruption. Where necessary, remediation plans must be put in place.

While no board member wishes to explain to the regulator why their firm was the first domino in the ecosystem to fall over, such far-reaching change needs to be carefully managed.  To implement these requirements firms will benefit from a pilot that enables them to develop an understanding of the steps that would be required.  This will be less disruptive and more beneficial than a firm-wide initiative.

However, the need to scale up means that firms will need to identify or acquire in-house "resilience capabilities". A key aspect of the output from a successful pilot project would be to identify exactly what capabilities are required and how they can best be embedded within the firm's business.

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ERM in Three Lines*

One of the challenges with enterprise risk management (ERM) is how much is written on the subject.  I find it useful to identify the key components.  This provides a structure to sort out the detailed views and comments, though it is also more than that. If you are a busy CRO or senior risk leader, identifying the key components enables you to take stock and think about challenges and improvements that may be relevant to your priorities. 

Here is an attempt to sum up ERM and provide that clarity in three headlines.

1.       A vision of the ERM purpose 

My preference for financial services is ‘protect and enable’. This highlights that risk management is more than just about avoiding the downside; it is about how risk management supports decision making, including the role of the CRO in that decision making. (More on ‘protect and enable’ and different views from practitioners shared on Crescendo Advisors’ blog are available here.)

2.       An articulation of how to deliver and embed ERM in the business 

This is your ERM framework, roles and responsibilities, policies, and risk appetite. They must provide the right balance between the level of detail and clarity to create a durable product and support business implementation.

3.       Evidence of the outcomes of vision and articulation of ERM (1 and 2 above) 

This is the outcome of the ERM, i.e. the assurance that is provided to the Board. This means that a feedback mechanism that supports improvement is in place. This is partly about risk or thematic reviews, but it also represents a wider perspective that involves 1^st line and 3^rd line as well. I also find that focusing on assurance is more ‘real’ than a discussion on the extent to which processes are implemented or embedded.

At the risk of oversimplifying, here is my own take on the UK insurance business position on these three aspects

• The articulation of the ERM vision is progressing but there is still work to be done. There is a sense that, broadly speaking, people operate according to the ‘protect and enable’ vision without articulating it as clearly as it could be.  

• Good progress has been made articulating how to deliver and embed ERM in businesses; all businesses have ERM frameworks and policies in place.  Some are considering external reviews after the frameworks have been in place for some time.  

• The biggest challenge ahead is evidencing ERM implementation and providing structured assurance to the Board about ERM expectations. This is a challenge for risk management function (risk reviews?), first line (business and control reviews?) and internal audit (coordinate with first and second line?).  Please get in touch if you want to receive a paper with initial thoughts on this challenge. 

Do you agree with views about these views about the insurance sector in the UK? How about banking and asset management? How is this seen in other countries?

*  No pun intended about the three lines of defence.

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The New and the Old in Risk Management

I have been writing about the new and the old in risk management over the past year. This starts with the slow pace of adoption of FinTech by incumbents in financial services. I have suggested that an important component of the change needed includes incumbents amending and enhancing risk management frameworks to reflect new FinTech innovations. (See my last post on the subject.)

Recently, I came across an article from McKinsey that makes a similar point in the context of model risk and the adoption of artificial intelligence (AI) and machine learning. It turns out I am in good company! 

McKinsey’s article notes that banks have developed and implemented frameworks to manage model risk, including model validation reflecting specific regulatory frameworks, in this case from the US Federal Reserve (here). They recognise that the implementation of these frameworks is not appropriate to deal with the model risk associated with AI and machine learning. Banks are therefore proceeding cautiously and slowly introducing new modelling approaches even when these are available.

The article then shows how a standard framework for model risk management is used to identify extra considerations required for this framework to cover appropriately AI and machine learning models.  The key message is that the challenge of adopting AI and machine learning can be addressed through a careful consideration of existing approaches. 

Two further thoughts from McKinsey’s article. Firstly, the article rightly refers to model management rather than validation. It is always useful to reiterate that model validation undertaken by the risk function is just a component of how models are managed in the business. Secondly, model management should not apply only to internal models used to calculate regulatory capital, but should apply more widely to models used in the business such as those used for pricing, valuation of assets and liabilities.

The article ends with a cautionary tale of an unnamed bank where the model risk management function took initial steps to ready itself for machine learning models on the assumption that there were none in the bank. It then discovered that an innovation function had been established and was developing models for fraud detection and cybersecurity.

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Risk Management as Infrastructure for Artificial Intelligence and FinTech

During 2018, I wrote several posts about FinTech, Artificial Intelligence (AI) and risk management.  I was kindly invited to present to the Network of Consulting Actuaries, I chose to use this opportunity to consolidate my views on the subject.  

There were several ideas flowing through my mind.

Firstly, informal evidence suggests that, for all the hype, FinTech and AI have not yet become mainstream in insurance or in financial services more generally.

Secondly, the largest business transformation arising from FinTech and AI is the adoption of these technologies by incumbents.  Indeed, I explored this in the context of banking through the group project at the Oxford FinTech Programme I completed in December 2018.

Thirdly, someone who works for a multinational insurer made the observation during an InsurTech event in London that as a regulated entity, the insurer has responsibilities and obligations towards their customers and must follow due process before they roll out new technologies.  There was a hint of an apology in this observation to the nimble start-ups in the audience.

Putting all these thoughts together led me to see the main challenge to the adoption of FinTech by incumbents as governance, including how risk management is applied in practice.  If the aim of risk management is to ‘protect’ or block, then the incumbent does not have an obvious lever to support the introduction of AI tools and FinTech.  

If, on the other hand, the aim of risk management is perceived as to ‘protect and enable’, then risk management can be part of the solution.  Risk management can lead to the creation of necessary infrastructure to ensure that AI tools achieve their transformational potential.  This includes articulating a vision of how a control framework should be leveraged, considering the impact of FinTech and AI on risk management frameworks, focusing on explainable AI, and articulating the implications for the target operating model.  This will facilitate incumbents’ adoption of FinTech and AI.  

Take a look at the presentation I gave (here) for a more detailed articulation of these points.

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Monitoring the Risk and Business Impact of AI-Based Solutions

AI-based solutions can shape how financial services businesses make money, whether the business model is the same or not. For an existing financial services business, the motivations may vary and range from efficiency to expanding the business. There would be project risk as with any development, but leaving that important consideration aside, it is worth bearing in mind that AI-based solutions would also impact the risk profile of the business. This may or may not be the original intention, but it becomes more likely. The key implication is that implementing an AI-based solution would require a radically different risk oversight approach by the business.

Standard computer algorithms which are not AI-based can—and do—solve complex problems. The main feature of such algorithms is that the problem is somehow defined and an algorithm developed to solve it which will produce the same answer as long as the same inputs are provided. So a credit-scoring mechanism calibrated to capture a certain type of client gives you just that.

The answers offered by an AI-based system may change over time. New data is used to reassess the underlying relationships and recalibrate the relationship between the target variable and the potential explanatory variables. This “learning” can also happen in a standard programme when there is a process of recalibration. The difference is that in the case of AI, learning would happen on a real-time basis—that’s the essence of AI.

Alternatively, with AI a target variable may not have been defined. That’s not as unusual as it might sound. For example, algorithms assessing a loan or credit card underwriting may fall in this category because there is no single rule to predict a borrower’s likelihood of repayment. New data can lead to a certain recalibration or can be used to identify new relationships between certain data. For example, over time an AI-based system might identify that outstanding debt is a better predictor of the likelihood of borrower repayment than repayment history and penalise someone with a relatively good track record of timely repayments.

The first type of AI-based solution is called “supervised machine learning” and the second one “un-supervised machine learning”. The key difference is the extent of autonomy that goes with the learning.

Consider the potential impact on conduct risk of AI-based tools. One of the expectations from Treating Customers Fairly (TCF) with respect to product governance is that they are designed to meet the needs of identified consumer groups and are targeted accordingly. This requires a clear business strategy, including identification of the target market through a combination of qualitative and quantitative research and oversight of the business to ensure that it is aligned with initial expectations of customers and business generated. Take the example of automated investment services covered in a recent FCA review. These providers would rely on some type of AI-based solution, whether supervised or unsupervised machine learning. The possibility of capturing different customers or the advice generated being different from what was envisaged cannot be ruled out. The challenge is how to put in place a monitoring approach which ensures that outcomes and risks which arise are consistent with the expectations in the business plan.

Something similar can apply from the perspective of credit risk, impacting the quality of the portfolio and performance. Suppose you have been targeting retail customers with a specific risk rating for a credit card business. If you roll out an AI-based solution to enhance the efficiency of product underwriting, you would need to have in place mechanisms to ensure that the credit quality of the portfolio is consistent with your expectations—or else change those expectations. Both options are fine. You may want to keep your target credit rating constant and seek more volume, or perhaps you see AI-based solutions as a more robust tool to support decision making and, in a controlled manner, can relax your target rating. Regardless of your choice, you would need to put in place a credit risk monitoring approach that is suited to the new AI-based solutions, as well as ensure that the business understands the portfolio implications of “learning” that is at the core of an AI-based solution system.

The salient point to take away is that the roll-out plan of AI-based tools may focus on the launch. However, the greatest challenge may well be the need to provide for the ongoing and timely monitoring of the AI-based tools and their integration in business governance and risk management, which I will cover in the next post.

Risk Assurance: The Challenge Ahead

I wrote about risk assurance a while ago (here). More recently, I have had a chance to talk with a few people in banking and consulting about it, and to reflect further on the subject.

By way of background, my working definition of risk assurance is a structured activity undertaken by the risk function (second line) which is aimed at evidencing that risk management is embedded in the business. Feel free to comment on this definition.

The important thing about risk assurance is that it matters because it contributes to shifting (or to maintaining, if you wish) the appropriate risk culture in the business. What do I mean by this? I hope we can all agree that the appropriate risk culture in financial services is one that includes the following:

• the business takes into account risks in decision making and can evidence that, including compliance with regulatory requirements; and
• the risk function provides the parameters for taking into account risk in decision making (risk appetite framework, stress testing, etc) and aggregate risks.

Truly achieving that is a challenging journey that takes time. Many insurers and banks started the risk management journey as a result of regulatory requirements—Solvency 2 or Basel. In practice, this has meant that sometimes risk functions have taken up activities like approvals that belong to business functions. Risk assurance will generate evidence about how risk management operates in practice. It will also help to shift the focus of the risk function—and, in turn, the business—in the appropriate direction.

I have worked with a number of clients to implement programmes of risk assurance. Interestingly, these engagements have turned out to be rather different because they must reflect the starting point for the business. In one case, the risk function was well resourced, and the focus was planning. In another case, the focus was a combination of up-skilling and evidencing through pilot risk reviews that the activity can add value.

Leaving aside the considerations associated with implementation, it is important that there be a shared perspective about the overall aim of risk assurance, i.e. ‘integrated assurance’. This reflects two simple observations:

• internal audit functions already provide assurance about the overall control environment;
• from a Board perspective, assurance is assurance, regardless of which team/line of defence provides it.

In other words, the aim would be to develop a risk-based assurance plan which covers deliverables by 2LOD and 3LOD in such a way that the Board can understand where independent assurance has been provided.

I would be interested to hear your thoughts.

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Risk Reviews: Not 'a Bridge Too Far'

The role of a Chief Risk Officer (CRO) and her team in the context of a three-lines-of-defence model in financial services can be best described, in my view, as ‘to protect and enable’ (click here for an earlier post on the subject).   Consistent with that, financial services supervisors in the UK and EU refer to the oversight role that the CRO's team provides. 

There are many issues and considerations in embedding effective risk management in financial services businesses.  At one level, oversight requires the CRO’s team to develop the appropriate engagement with the business to provide support, to challenge and to ensure that risk management features ultimately in decision making.  This may result in recommendations for senior management. 

On its own, this is unlikely to be adequate to evidence appropriate and effective oversight for two reasons.  Firstly, the rationale for covering certain business areas or aspects would not be evident.   Secondly, there may be overlaps with the areas reviewed by Internal Audit. 

The answer is not to restrict the engagement between businesses and the CRO’s team.  Instead, the CRO should put in place a programme of risk review which is coordinated with Internal Audit to avoid overlaps or underlaps.

A structured programme of risk reviews requires consideration of the risks to which the business is exposed and their materiality, as well as business cover.  For example, it would not be sensible to cover just one business area, even if that is the main source of risk. 

The key aspect of the development of a programme of risk reviews is identifying a number of potential reviews that map into a grid of risks, materiality and business areas.  The list of reviews is then whittled down in discussions with the CRO and the leadership team to a programme that is consistent with the scale of the business and the maturity of the CRO’s team.

The Board (or a Risk Committee) should review the proposed programme of risk reviews.  Some businesses require a combined submission from Internal Audit and the CRO to identify a complete assurance landscape.  The CRO’s team should then plan the reviews, including setting out terms of reference agreed upon with the business and delivering them throughout the year.  The CRO should also provide regular reports to the Board about the findings of the various reviews and management delivery of recommendations.

Overall, a programme of risk reviews complements Internal Audit’s activities because of the involvement of the CRO’s team on a real time basis in key business processes such as business planning and product development.  Experience suggests that overlaps with Internal Audit can be avoided and that performing these reviews enables the CRO team to get even closer to the business and embed risk management ― ‘to protect and enable’.   

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Feedback Loops and Enterprise Risk Management (ERM)

One should not take things for granted and this also applies to ERM.  In the case of ERM, this would mean identifying feedback mechanisms about the effectiveness of ERM to provide assurance to boards about the value generated.  This should also generate further insights to enhance ERM’s value added.  

This connection between ERM and value has not escaped supervisors.   On a company level, EU directives covering prudential regulation of banks and insurers include requirements that aim to formalise these feedback mechanisms.

While boards and regulators may be interested in the effectiveness of ERM in specific companies, there seems to be less evidence at an industry level.  Wouldn’t it be useful to understand the link between ERM effectiveness and the role and experience of the CRO? How does board oversight contribute to ERM effectiveness? 

These are challenging questions, which are considered in a recent working paper by Cristina Bailey, assistant professor at the University of New Hampshire, using data for publicly traded US insurers.*  There is a fair amount of statistics and econometrics in this paper which would have been covered through peer review.  There are differences between regulatory requirements on the two sides of the Atlantic, which could challenge the ability to infer from US data for Europe.  However, it would seem that ERM effectiveness is driven by the underlying business rather than regulatory requirements and that the lessons should be transferable. 

So what can we learn from this paper?  There are a number of measures of ERM effectiveness and benefits.  The effectiveness of risk management can be gauged by reference to the ratings awarded by S&P for risk management.  There are five possible ratings: very strong, strong, adequate with strong risk control, adequate and weak.  In the paper, ERM is defined as holistic risk management and is associated with the top two S&P ratings.  ERM benefits can be considered by referring to the volatility in stock returns.  ERM benefits can also be inferred using a measure of strategic industry positioning defined as the difference between the return on assets for the insurer and the top quartile.

Normally, it is important to consider the experience that the CRO brings to the role.  A number of experiences are specifically identified: oversight (e.g. prior experience as CEO or COO), financial (e.g. accountancy qualification or prior role as CFO or financial controller), industry (previous employment in the insurance industry) and risk (previous experience as a CRO or a senior risk management position). 

The analysis suggests that the breadth of the CRO’s experience is positively related to ERM effectiveness after controlling for a wide range of relevant factors.  However, this logic does not seem to apply to the expertise of the risk or audit committee.  But before you despair about the value of effective risk governance provided by a board committee, consider the impact on ERM benefits mentioned earlier by reference to volatility or strategic industry positioning.  The breadth of expertise of the committee members turns out to be a significant determinant of the ERM benefits. 

This result is a useful reminder of the difference between outputs (effective ERM) and business outcomes (e.g. risk reduction).  A potential way of pulling together these results is as follows: a CRO with broad expertise can successfully shape the effectiveness of ERM.  However, the wider ERM benefits depend on shaping the overall direction of the company which requires, amongst others, board committee members with a similar breadth of experience to act on the outputs that the CRO leading an effective ERM system would generate.  The above points to the importance of the qualities of CROs. 

Headhunters Hedley May have also published an interesting paper on the role of the CRO – and the risk function – based on discussions with CROs in banking, insurance, investment management and other stakeholders.**  Their analysis seems to support the above hypotheses about the difference between an effective ERM system and delivering business benefits such as lower volatility.  The qualities of a good CRO were found to include relationship building, influence and an ability to synthesise. These would provide the CRO with appropriate credibility in front of the board to go beyond an effective ERM and affect business decisions.

* ‘The Effect of Chief Risk Officer and Risk Committee Expertise on Risk Management', (forthcoming, www.ssrn.com)

** ‘The Post Financial Crisis Chief Risk Officer: The Teenage Years’, 2015

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Is the Governance Map Also the Territory?

One of the financial crisis’s lessons for regulators has been discovering the ‘accountability firewall’ of collective responsibility which prevents actions against individuals even if they are approved for specific roles.  This was one of the lessons from the UK Parliamentary Commission on Banking Standards from 2013.

UK regulators have been tasked with the challenge of breaking down that ‘firewall’ for both banks and insurance.  The UK has had a regime of approved persons for some time.  The PRA and the FCA have been consulting on proposals aimed at strengthening the accountability of senior management.  For insurers, this is referred to as the Senior Insurance Managers Regime (SIMR).

The proposals may well increase the scope of senior managers, and will strengthen conduct requirements that apply to them.  It seems to me that the most innovative (and, dare I say, revolutionary) aspect of the proposals is the requirement that firms produce a ‘governance map’.   As with all good ideas, it is simple.  The regulator identifies a set of responsibilities and then asks firms to map them to senior managers who are subject to regulatory approvals and sanctions.  

The list of responsibilities is long.  For example, the list for insurers is as follows:

1.       ensuring that the firm has complied with the obligation to satisfy itself that persons performing a key function are fit and proper;

2.       leading the development of the firm’s culture and standards;

3.       embedding the firm’s culture and standards in its day-to-day management;

4.       production and integrity of the firm’s financial information and regulatory reporting;

5.       allocation and maintenance of the firm’s capital and liquidity;

6.       development and maintenance of the firm’s business model;

7.       performance of the firm’s Own Risk and Solvency Assessment (ORSA);

8.       induction, training and professional development for all the firm’s key function holders;

9.       maintenance of the independence, integrity and effectiveness of the whistleblowing procedures, and the protection of staff raising concerns;

10.   oversight of the firm’s remuneration policies and practices.

For banks, there is no direct equivalent to 7 even if there is an ICAAP.   However, the list includes the following additional responsibilities:

1.       funding is also mentioned in 5. above as well as an additional responsibility in respect of the bank’s treasury management functions;

2.       developing a firm’s recovery plan and resolution pack and overseeing the internal processes regarding their governance;  

3.       managing the firm’s internal stress-tests and ensuring the accuracy and timelines of information provided to the PRA and other regulatory bodies for the purpose of stress testing; 

4.       safeguarding the independence of and overseeing the performance of the compliance function, internal audit and risk function respectively; these are three different responsibilities.

There are some interesting differences between banking and insurance.

The overall message is rather simple: there is an individual presumption of responsibility in the event of a breach.  In those cases, the relevant individual will need to demonstrate that he took reasonable steps to prevent the breach in the relevant area. 

Firms’ senior managers will spend time discussing the mapping of responsibilities.  This may well be the easy part.  Undoubtedly, the challenge for senior managers will not be the map, but the territory, i.e. how to manage the relevant responsibility.  For some responsibilities there will processes, teams and awareness within the company to ensure that something happens; think of item 7 above, the ORSA.  In other cases, the challenge will be determining which business function will assume the relevant responsibility and what approaches, processes and resources will be needed as evidence that reasonable steps were taken.  What should be done to prove that ‘firm’s culture and standards’ are developed and embedded?  

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Risk Is Exciting

You hear people say that risk management and regulation are not exciting topics.

However the 30,000 pageviews on this blog since Nov 2014 suggest that risk management and regulation are more interesting than it seems.  Your comments have also been very useful and instructive.  Please keep them coming.

Thank you all!    

Losses Are Not Failures of Risk Management

Well, not necessarily.  But we need to remind ourselves and our stakeholders that that’s really the point.  Losses will happen with certain regularity.  This is the message of a system of a risk appetite system where the limits are calibrated to a 1-in-10 chance over a one-year horizon.   Whether the implications are really appreciated is a different point. 

A paper by Rene Stulz (here) is a good reminder that losses may not represent a failure of risk management.  This is particularly the case where “managers [know] exactly the risks they faced―and they decided to take them.  Therefore there is no sense in which risk management failed”.  He goes on further to say that “deciding whether to take a known risk is not a decision for risk managers.  The decision depends on the risk appetite of an institution.” 

This is consistent with the practitioner’s view as expressed by James Tufts, Group CRO of Guardian Financial Services, expressed in a guest post in this blog: “[T]he objective of the ‘Risk Function’ should not be ‘risk management’.  That’s a business objective.  The objective of the ‘Risk Function’ is to provide the ERM [Enterprise Risk Management] framework and the source of challenge and oversight on all aspects of the business model, relative to this framework.”

There may be risk management failures nevertheless and Stulz’s paper goes on to provide a useful classification:

1. Mismeasurement of known risks  
2. Failure to take risks into account 
3. Failure in communicating the risks to top management 
4. Failure in monitoring risks 
5. Failure in managing risks 
6. Failure to use appropriate risk metrics

I find these categories rather intuitive and I wonder how they can be used in practice.  There is an increasing regulatory expectation of formal assessment of the effectiveness of risk management and these categories could usefully feed into that process in two complementary ways. 

Firstly, banks and insurers track a range of risk events/incidents.  It would be useful to consider if reported incidents fall into any of the above categories.  Alternatively they may be consistent with risk appetite.

Secondly, insurers and banks using an internal model are expected to use it to support a profit and loss attribution.  This means explaining actual profits and losses by reference to the output of the internal model and the risk categories considered.  It would be interesting to consider if the losses arise from changes in values consistent with risk appetite or any of the reasons set out above. 

The above might seem a simple idea but learning from failures, or risk management failures in this case, is usually anything but a simple idea.

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The European Commission’s Impact Assessment of Solvency II: Some Useful Points

The European Commission recently published a draft of the Solvency II ‘implementing measures’.  The ‘implementing measures’ expand on the requirements set out in the Solvency II directive.  Alongside the ‘implementing measures’, the European Commission also published a draft impact assessment.  This is one the many procedural requirements that apply to the policy-making process in the Commission. 

I thought it would be interesting to review the impact assessment.  As a user, I want to consider the extent to which the impact assessment can help me to understand Solvency II. 

What did I learn from this exercise?

1.    The importance of objectives in the EU policy-making process

The impact analysis is structured around a definition of problems that the policy making will address.  During the discussions about the directive, these objectives were enhancing policyholders’ protection and the integration of insurance markets in the EU. 

The Commission’s impact analysis acknowledges that there is now a third objective that has been taken into account: fostering growth and recovery in Europe by promoting long-term investment.  In the case of insurance, the main challenges that arise relate to the low interest rate environment and the volatility of asset prices. 

2.    A useful summary of how the calibration of asset risk has evolved

The third objective mentioned above has shaped the structure and calibration of capital requirements for assets risk which has evolved over a number of years.  However, it is not easy to see in a succinct way the end product where the answer is set out over a number of articles in the implementing measures.  Surprisingly, this can be summarised in a simple table (below).

3.    The scope of impact analysis remains a tricky issue

The Commission seems to have overcome the challenge of undertaking an impact analysis that seeks to cover the impact of all rules.  The Commission states,

“The options assessed have been selected to cover the most important and representative issues from each of the three pillars of Solvency II and each of the areas of the objectives and problem trees. The areas that are merely technical, have been settled in the Directive or are uncontroversial are not assessed in detail …”

This is reasonable and can result in a more productive use of scarce analytical resources but it can also have unintended consequences.  As far as I can see, the impact analysis did not cover the treatment of long-term guarantees.  I am frankly not sure if this is because it was settled in the Directive or because it turned out to be uncontroversial.

4.    The relative priorities of the Commission: the importance of reducing over-reliance on ratings

The concern about over-reliance on ratings is not new if you have been following the development of Solvency II.  However, given the breadth of Solvency II and the focused impact assessment, I found it surprising that the Commission went out of its way to include a full two-page annex summarising the requirements aimed at reducing reliance on external ratings in the risk management of insurance “such as

          ▪ external ratings shall not prevail in risk management;

          ▪ as part of their investment risk management policy, insurers and 
          reinsurers should have their own assessment of all counterparties;

          ▪ as part of their reinsurance (or other risk mitigation techniques) policy, 
          insurers and reinsurers should have their own assessment of all 
          counterparties.”

5.    And finally, a puzzle about policy making

The Commission’s impact assessment notes that one of the issues that emerged from the QIS5 was the application of a limit to the amount of Tier 2 capital (i.e. debt) that would be allowed.  This issue has remained unclear since then. 

Interestingly, if all you read is the relevant section of the impact analysis on pages 38 to 46 which also summarises EIOPA’s recommendations, you could be forgiven for thinking that the limit would not apply.  It is only the summary on pages 50 to 51 that suggested that I might need to reconsider my initial views.  Indeed, the draft implementing measures clarify that the sum of Tier 2 and Tier 3 capital must not exceed 50% of the SCR, which is an interesting development. 

This illustrates one of the key operational challenges of impact analysis: the need to keep up with the policy.

This was a selective but nonetheless in-depth reading of the impact assessment.  Have you read the impact assessment?  Did you learn any useful points from it?

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