ERM reboot: how insurers are turning risk decisioning into strategic advantage

Enterprise risk management (ERM) is a powerful strategy to identify, assess and manage risks across the business. For insurers, two ERM objectives are critical: ensuring regulatory compliance and establishing a framework for healthy investment risk appetite

The panel

• Scott Kurland, Managing director, SS&C Technologies
• Paolo Laureti, Product manager, insurance, SS&C Algorithmics
• Moderator: Sakshi Sharma, Commercial editor, Americas, Risk.net

In an exclusive Risk.net webinar convened in collaboration with SS&C Technologies and SS&C Algorithmics, a panel discussed the key factors reshaping insurance firms’ ERM thinking, and why a more agile approach to incorporating emerging risks and innovations can help avoid losses, prevent financial instability and enhance reputation. Here we reveal the key themes emerging from the discussion.

Developing a best practice ERM framework

Paolo Laureti, SS&C Algorithmics

An efficient ERM platform can provide insurers with a framework to manage financial risks across the entire enterprise in accordance with a set of business objectives. The main goal, according to Paolo Laureti, product manager for SS&C Algorithmics risk analytics solutions for insurers, is to protect the firm from adverse events and create value for internal and external stakeholders, including auditors, rating agencies, regulators and the wider society, for whom the insurance ecosystem is extremely important. 

“One of the key principles for a best practice ERM is that the data and models must be complete, reliable and consistent. The aim is to set up an end-to-end framework, based on a single version of truth, where a reliable data source feeds all functions from the back, to the middle and to the front office and it is trustworthy,” said Laureti.

“Today, systems still struggle with fragmented data, inconsistent calibrations, separate software tools and a lot of manual interventions and Excel spreadsheets,” he added.

A key ingredient, according to Laureti, is to generate market-consistent projections of the balance sheet under a set of stochastic scenarios. 

“Stress tests by themselves and deterministic projections are no longer enough. Assets must be modelled very precisely, to the most granular level, and the simulations must cover the entire portfolio, including private and alternative assets, with the ability to perform a look-through into the funds. Liabilities must also be projected, often using proxy techniques, under a common risk factor universe; so we project assets and liabilities in a correlated structure.” 

High-performance computing and flexibility are also important for interactivity, said Laureti, so business users can access the ERM platform without the help of IT. For example, they can run what-if scenarios or set up a stress test in real time, and inspect the risk profile changes under the new portfolio and market conditions. The solution must serve not only risk management purposes but also asset-liability and investment management functions.

Regulatory compliance and investment goals

Insurance investment portfolios have become more diverse because of the long period of low interest rates where yields on traditional fixed income and vanilla instruments were insufficient. This led to an appetite to move into private and alternative investments, credit instruments and real estate, either organically by expanding the investment mandate, or inorganically through acquisition or partnership.

At the same time, as insurers’ investment objectives changed and the portfolios moved into the private space, regulators such as the US-based National Association of Insurance Commissioners (NAIC) and the Bermuda Monetary Authority started taking a closer look at this area. 

As an example, the NAIC has relaxed the risk-based capital factors – the capital required to be kept as surplus as a life insurance company – when investing in limited partnerships or direct real estate. This means investor capital can go further, and these types of capital investments have become more attractive. 

Moving forward, regulators will require more transparency and better classification of private market investments, with more specific cashflow modelling related to private market equity and debt instruments. 

Scott Kurland, managing director at SS&C Technologies, warned that firms will have to take these aspects into account when it comes to risk models and ERM systems on the investment side of the portfolio.

Changing approaches to ERM

Scott Kurland, SS&C Technologies

Kurland also highlighted several trends prompting insurers to reassess their ERM strategies. First, property and casualty (P&C) insurers have found it hard to drive profitability on the investment side of the balance sheet, being restricted to “more short-term liquid investments that traditionally have not offered substantial yield”. As a result, some have broadened their offerings through the launch of life insurance or longevity reinsurance products and business lines. These typically have longer-duration liabilities, allowing them to expand into longer-duration investments, such as alternative assets or credit instruments that offer the potential for a higher yield and further diversification of their portfolios. 

The second trend, according to Kurland, is “a flurry of firms launching new captive insurance arms, driven in part by the rising costs of commercial insurance in areas such as P&C or cyber”. He added: “These firms believe it may be … more cost-effective to set up [their] own captive or collective, or participate in a rental captive and, in turn, self-insure and consider … reinsurance”.

As a result, more insurers now have multiple lines of businesses – property, casualty, life and annuity, and reinsurance – resulting in more complex portfolios with very long-duration investments, as well as extremely short-term cash or cash‑equivalent investments. 

Therefore, an ERM framework must allow for long and short time horizons, and look across the business to see how events such as a rapid escalation of interest rates or an uncertain environment could affect the liability and product sides of balance sheet claims, as well as the investment side of the book.

ESG capital and liquidity measures

Kurland highlighted environmental, social and governance (ESG) investing as a “sensitive and tricky topic that insurers and the wider investment community on both sides of the pond are trying to navigate”.

Insurers need to find a reliable source of data because the ESG scores provided today are often inconsistent with each other and therefore not trusted by investors and regulators. “Increasingly, we have to look at the raw data and try to analyse it and come up with a better measurement of ESG criteria,” Kurland said.

Better data is also required for strategic asset allocation and to optimise portfolios. ESG scores will play a major role going forward, he added. 

Reputational risk is a key concern in this area. It is important for firms to upgrade their systems’ data and policies to comply with new regulations and reduce their carbon footprints. For insurance and reinsurance businesses, climate risk is a priority in respect to both physical and transition risk.

Physical risks are particularly important for non‑life insurers, including earthquakes, floods, droughts and other phenomena that are exacerbated by climate change. Meanwhile, transition risk has a bigger impact on financial investment portfolios.

Overall, insurers can help facilitate the transition to a net-zero emissions economy by increasing the allocation to green assets and critical infrastructure, such as solar or wind farms. Insurers also play a key role as they can allocate capital to mitigation and adaptation projects that can be prioritised by their underwriting functions. “When you think of climate risk modelling, insurers are at the forefront of developing risk models that can then be reused by regulators and governments,” said Laureti.

Future developments

A flexible approach to ERM will be required to incorporate evolving risk types, such as climate risk, according to Laureti. “We added liquidity a few years ago and now we see other emerging risks, including climate. If you want a common base of risk factors to do your stress tests and then, ultimately, incorporate climate into your pricing functions, this holistic view of risk across the enterprise is mandatory.” 

Laureti also pointed to such innovations as machine learning. Examples of recent applications include portfolio optimisation for strategic asset allocation or portfolio replication, whereby a stream of liability cashflows is well represented by a calibrated asset portfolio.

In summary

Ultimately, firms require an ERM platform that is dynamic and flexible, and provides a holistic view of risk across the organisation, said Kurland. It must be agile enough to cope with assets and liabilities, allow flexibility of modelling, incorporate external benchmarks, and cover single and multifactor models. It needs to act as a powerful tool to run analysis quickly and accurately, and include interoperability of data modelling to increase transparency.

With rising risks, climate and ESG in focus, ERM frameworks cannot be seen to play catch-up – instead they need to be at the forefront of innovation and cutting-edge technology.

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