Insights

Animation: Insurance Risk Management 2025

Navigating a Digital Future

How could the insurance industry look in 2025, and what are the implications for the Risk function? Our video below offers a futuristic glimpse of a rapidly evolving industry.

How could the insurance industry look in 2025? 

Our animation presents the “LifeMap” proposition of our hypothetical insurer “Cognition” in 2025, and offers a glimpse of how insurance products and services could evolve over the coming years. Below we use examples from the video to discuss the most important considerations for Risk functions as they prepare for the future.

An Evolving Risk Landscape

Although Cognition is exposed to the same broad categories of risks as today’s insurers, the nature of these risks and the way it is exposed to them is different.

Real time pricing, underwriting, and management of traditional risk types

Decision-making in 2025 happens much faster and more dynamically than today. Policyholders receive advice and buy insurance cover or savings products via virtual-assistant "Eleanor”. Automated pricing and underwriting is facilitated by the large amounts of structured and unstructured customer data to which Cognition has been granted access. This results in a very dynamic asset-liability mix and hence a volatile market and insurance risk profile, which must be understood and managed in real-time. Robust, automated asset-liability management processes and approaches are required to stay within risk limits.

This new way of pricing and underwriting also requires a different way of thinking about insurance risks. Today, these are mostly modelled and managed using static risk factors, such as age. In the future, unstructured data from sources, such as social media and the internet of things, will play a much more significant role (assuming policyholders allow access). The associated risk factors need to be properly understood, modelled, and managed.

Digital operational risks

Large parts of Cognition’s processes are automated and performed by intelligent software or robots. This exposes Cognition to the risk of software making sub-optimal decisions on behalf of the company. Consequently, many of today’s operational risks, such as financial reporting risk, become “digital” risks in the future. As important, the use of “intelligent advisor” algorithms changes the nature of misselling and conduct risk, making them much more systemic (from the point of view of the company) than idiosyncratic. Both the controls framework and the risk assessment and quantification framework need to be adapted.

In 2025 cyber risk plays an even greater role for Cognition, as all Cognition’s systems are interconnected. If not managed carefully, these may be more susceptible to attacks.

Risk Readiness?

The Risk functions of today’s insurance companies are not set up to provide oversight and challenge for such a business model and risk landscape. Insurers in Europe have focused much of their time in recent years developing their Solvency II models and becoming Solvency II compliant. Their finance and risk system landscape is often fragmented. Much effort is spent performing manual calculations, reporting, and on risk model calibration and documentation processes.

Today’s Risk functions and their capabilities are at risk of being outpaced by developments in other parts of the business. There is a real possibility that the Risk function will become a constraint for business development and innovation, and therefore become itself a strategic risk to firms.

Future-proofing Risk Management

Future-proofing the Risk Function is essential and this should happen across all key areas:

Embracing new approaches and technologies

The world is changing quickly. New risks are emerging and existing risks are changing in nature. Coping with this requires Risk functions to enhance and automate their risk identification processes and make better use of alternative sources of data. For example, some firms are looking at combining externally-sourced structured data, as well as social media and other unstructured data with more traditional internal data sources. This may allow better measurement and prediction of those risks that are typically hard to quantify, such as political and reputational risk.

In addition, advancements in digital technologies are available to automate existing risk and reporting processes, like the ORSA, and make dynamic real-time information and analysis available for senior management to access. This would allow management to perform dynamic ‘what if’ analysis on demand against specific risks, and understand the impact of various scenarios on solvency, liquidity, and profitability. Firms would have improved visibility of their own risk position and consequently this will enable better, more informed decision making.

Using external expertise or industry-wide collaboration

Too much time is currently spent on quantifying “vanilla” risks (such as interest rate risk and investment grade corporate bond spread risk) that are not specific to a given company. Individual firms, and the insurance industry more broadly, should consider how the modelling and documentation of vanilla risks can be outsourced or automated using new digital technologies, or even centralised in an industry funded body providing services to its members. This would free up time and resources for companies to understand and quantify risks that are idiosyncratic to their business.

Completing the talent puzzle

Risk management in the future will require a different and more balanced mix of skillsets. There will be fewer traditional financial and actuarial specialists, and more resources with people, business, technology, and coding skills. However, demand will be high for similarly skilled resources, both internally and externally; insurers are already competing with banks and technology companies for the limited pool of coding talent. Risk will therefore need to find creative ways of attracting, developing, and retaining the right people.

A Final Word

The insurance industry of 2018 is already highly complex. However, this complexity is only likely to increase as business models evolve, the speed of change regarding data and technology accelerates, and the risks that the industry faces change and expand. For many organisations, the Risk function’s ability to keep pace with these changes will be a defining factor in their survival and success.