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7 factors that could drive enterprise risk management in 2030

Corporate Risk Tools and Technology|Insurance Consulting and Technology|Reinsurance
Insurer Solutions

July 24, 2019

Nine of our risk experts forecast how today’s innovations and trends can shape tomorrow’s risk and insurance industry.

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About our ‘A Year in the Life of the Strategic CRO’ series

 

In our ongoing A Year in the Life of the Strategic CRO series, risk experts from our Insurance Consulting and Technology team, Willis Re and other parts of Willis Towers Watson cover how how a strategically focused CRO can drive corporate strategy through the enterprise risk management planning process and throughout the year.

 

The chief risk officer can and should develop a long-range vision of what enterprise risk management might look like at some point in the future. As a part of our AYear in the Life of the Strategic CRO series, we collected the thoughts of nine Willis Towers Watson experts to envision both how the environment might change over the next 10 years and also how the ERM function might react. 

A big part of strategy is having an overall vision for an organization at some fairly distant point in the future.   Strategy then becomes the link between the current state and that future vision. And a key aspect of constructing a vision requires a forecast of how the world might change over that horizon. 

A Strategic CRO wants to participate in the vision, forecasting and strategy-formation processes within their organizations. One way for CROs to demonstrate that they have the requisite capabilities is for them to develop a vision and strategy for the enterprise risk management (ERM) function that they manage. That is a big challenge, mainly because the world of the CRO has been changing rapidly over the past decade and is likely to continue changing significantly over the next 10 years. 

To help in creating a vision, we brought together nine experts from the US, Europe and Asia from our reinsurance broking, consulting and insurance broking teams to brainstorm possible future scenarios for ERMs. Strategic CROs might use these as a jumping off point in their deliberations. The future may resemble one or more of these scenarios or parts of all seven, as they are not at all mutually exclusive.

  1. Continuation of market consolidation trends
  2. Scale is essential to compete in the insurance industry of 2030.  As customers have increasingly opted to shoulder market and insurance risks, product differentiation has waned and cost-efficiency has risen to the top of insurers’ priorities. Only a handful of viable insurers remain in each market. The strategic CRO is then presented with new challenges facing these “mega-insurers.” 

    For one, the ability to recover or maintain the business with minimal adverse impact in a time of crisis is essential, and “killer” operational and behavioral risks are a bigger threat than traditional risks associated with demographic and economic change. Thus, the CRO’s role is increasingly focused on monitoring environmental, social and governance (ESG) data and customer sentiment (a leading indicator for mass lapse) and contributing to the organization’s social media policy and strategy. 

  3. Increased use of quantification techniques
  4. As the modern world enters its fourth major revolution era, technologies such as clouds, blockchains, or artificial intelligence (AI) enable us to get a better understanding of complex interactions. Considering 90% of the world’s data has been created in the past two years, this trend presents opportunities to better understand risk exposures, develop risk pricing models and project future financial flows.

    Businesses typically identify measure and mitigate their risks on an individual basis using historical loss models. With today’s technology and prevalence of data there are two opportunities for understanding risk:  increased use of quantitative techniques to support assessment of exposures and the ability to assess risk on a portfolio basis allowing for correlations and thereby determining diversification. This will allow for increased use of data analytics to understand and predict future losses through AI and spot trends in advance. And the internet of things will drive understanding of interdependencies and move risk management processes from reactionary to real-time.

  5. Extreme specialization
  6. Insurance has become increasingly, needs-driven, which means cover is more bespoke and specific to a given time period. With driverless cars for single trips more prevalent, top-up personal liability may be purchased for each ride, life insurance tailored for certain events such as child birth etc. 

    Customer distribution is increasingly “pushed”. Big data, AI and machine learning (ML) enables insurers to anticipate customers’ insurance needs and interact with them in real time. Customers are increasingly aware of social, ethical and economic value provided by insurers. 

    Access to real time information, blogs, comparator sites and misinformation provides consumers with an array of information relating to products, value for money, company ethics and claims-paying track records. Company reputation online and in social media is paramount, resulting in increased fraud, conduct and regulatory risk. Niche insurers come and go to provide for these needs and the successful ones are acquired by the mega insurance groups. 

  7. Enhanced insurance risk hedging
  8. Many insurers implement risk management hedging strategies for market risks, using the results and scenario tests from their risk and capital models, which incorporate derivatives and other market instruments. There is less scope to do that for insurance risks, save at a much broader level through reinsurance or portfolio-level securitizations. By 2030, insurance risk is well understood by investors and actively traded in the investment markets, providing investors with an additional source of return and diversification.

    Insurers are able to take on or cede insurance risks actively and at a very granular level.  Standard approaches to issues such as treatment of basis risk between different risk portfolios are understood and implemented. This, coupled with more powerful data analysis and real-time performance of risk and capital models enables insurers to dynamically manage their insurance and market risks for optimal efficiency in near-real time.

  9. Greater use of artificial intelligence and machine learning
  10. In 2030 AI and ML are very much business as usual. AI and ML are widely used to help detect changing risk patterns, not only by detecting clusters of insurance claims with similar characteristics and causes, but also by flagging topic clusters in scientific papers, lawsuits, social media and news reporting that could indicate changes in insurance risk.

    Automation enables ongoing modeling and re-modeling of known and emerging risk types, generating a time series of models and model parameters. Risk managers are able to detect changes in patterns much more quickly. ML enables the development of common risk driver modeling to replace copulas for modeling dependencies. Risk managers with high analytical skills and training are needed to help explain the patterns and linkages detected by AI to non-technical audiences.

  11. Focus shifts to different risks
  12. As the 2008 financial crisis has become history, different issues will take center stage in shaping ERM. The looming US retirement crisis creates opportunities for insurers, but may also introduce new risks and outsized longevity exposures. Concerns about climate change may cause actuaries to revisit risk models, including life insurance actuaries who have historically considered climate impacts less material for their business. Continuing threats of cyber-attacks make cybersecurity a primary focus, and CROs may need to augment their teams with individuals who have specialized skills in this area.

    The trend towards decreased customer loyalty accelerates moving customer retention closer to the top of the risk priority list. Quantitative risk metrics, need to be supplemented by an emphasis on qualitative key risk indicators to address threats that do not lend themselves to traditional modeling techniques. Successful ERM functions evolve to be nimble enough to react quickly when new risks emerge.

  13. Real-time risk monitoring
  14. Displaying key risk indicators (KRIs) and metrics in a clear and timely manner and informing senior management of changes in risk profiles and priorities, risk dashboards have long been standard practice for strategic CROs. While best practice was historically monthly updates of KRIs and other key risk metrics, the trend is toward more frequent and faster analysis enabled by automation technology and data analytics tools.

    Real-time risk dashboards are the new norm by 2030. Furthermore, with advances in technology and computing power, economic capital models even for large organizations can be run very quickly allowing management to update and use capital model projections in nearly real-time decisions. 

    Users should be able to run multiple scenarios to compare the impact of different strategies, e.g. how to spend the next dollar or decide which management action delivers a better risk/return trade-off in a matter of minutes and access such analysis online any time, any place, anywhere.

You may have noticed that each of these scenarios follow fairly positive trends into the future and are not the kind of scenarios that CROs are accustomed to. The strategic CRO might also want to think about the ramifications of a serious recession on these future trends. Some of these scenarios could be delayed while others might well be accelerated. 

Peering into and preparing for future possibilities is what both ERM and strategy are all about. This exercise will require chief risk officers to peer into their own futures and make strategic plans for the risk management function, which is what is usually asked of the business centers each year as a part of the strategy and planning process.

Previously in the A Year in the Life of the Strategic CRO series: 12 questions chief risk officers should ask after a major loss

Wil Bruce, Stas Eratt, Matthew Ford, Paul Headey, Esther Huang, Dave Ingram, Kenny McIvor, Mark Mennemeyer, Alice Underwood contributed to this article.