This blog is the start of a mini-series that we have written as part of the SERI programme. Since starting our work in April, we’ve been researching, thinking and starting the product innovation process that will allow us to develop and test a climate-ready financial product by November 2020.
We’re always looking for people to join us on SERI and to help improve our thinking. To share your thoughts or to get involved in this programme please contact Michelle at firstname.lastname@example.org
Insurance is a complex industry. In simple terms, paying small amounts, or premiums, over time to an insurer entitles us to claim large sums from the insurer if things go wrong. However, insurance business models depend on complex interactions of industry, data, mathematical modelling, investment structures, commercial and non-commercial stakeholders, and of course, changing circumstances caused by events around us.
Data is a key part of insurance, but the data flows and channels that exist are closed and/or high-friction. Data sharing is often carried out through expensive, bilateral agreements. Furthemore, there is a lack of standard formats across the insurance landscape for data sharing, and data quality widely differs depending on its uses.
As part of SERI, we mapped out the insurance industry landscape to clarify the various segments, how they interact, and the data channels that exist between market participants. By understanding the value chains, data layers and “gatekeepers” of the insurance ecosystem, we aim to identify levers that can facilitate decarbonisation across the industry through shared data. Creating standards that define a robust data infrastructure can facilitate cross-industry inoperability to reach our net-zero targets.
This is the first iteration of the insurance landscape based on findings to date. You can explore it in detail here. If you have any comments or feedback, or would like to collaborate to take this work further, please get in touch.
1. Insurance types and structures
Insurance is broadly split into life and non-life company types, primarily structured such as mutuals or stock / proprietary companies. Other hybrid structures of insurance exist, such as Lloyd’s syndicates, P&I clubs and takaful insurance. Parametric or index insurance is yet another type of insurance and differs from traditional insurance in how the payout is structured.
Life insurance is similar to investment savings and pensions in that there is always a lump sum payment at some point in time. Non-life insurance provides coverage for risks which may cause significant financial loss such as in the event of flooding, fire or a motor accident. Insurance for specific risk themes are known as insurance products. For example, a goods company may purchase a marine insurance product policy to protect its cargo at sea. Policies are specific insurance agreements between a customer and insurer based on that customer’s needs.
The customer buys an insurance policy to off-load a potential expensive financial loss onto the insurer. The insured policyholder thus transfers an unknown financial loss amount to the insurer for a defined price. This is known as risk transfer and is an element of risk management.
Furthermore, insurance companies can purchase reinsurance. Reinsurance companies take on financial risks for a price that may be too large for the primary insurance company to bear. Here, the primary insurance company is the insured, or policyholder and the reinsurance company is the insurer. Reinsurance firms can thus further off-load risk by buying their own reinsurance, which is known as retrocession.
2. Insurance pricing
Insurance premiums and compensation limits are estimated through the pricing of risk. Pricing is derived mathematically from the probability of said risk, namely:
- the likelihood of its occurrence (will it happen?);
- the frequency (how often does it happen?); and
- the severity (how bad is it?).
The above are estimated through a variety of macro and micro data inputs. Different types of data (such as historic, financial, and geographic data to name a few) are used for the pricing of risk, and thus to estimate general premium amounts and compensation amounts for a particular theme or insurance product. Actuaries in the back office estimate the general product pricing range, while the underwriter uses individual factors to accurately price the policy. This exchange of information and consolidation between the underwriter and the back-office is a crucial part of the insurance business model. The underwriter has the final say on what risks the insurance company is willing to insure and at what costs.
3. The insurance business
Levels of risk and their associated premiums from numerous insurance policies diversified across customers, products and geographies are held in the insurance companies’ portfolios. The premiums in the portfolio are invested to grow, while portfolio monitoring ensures appropriate levels of liquidity with respect to risk are maintained. In the event a policyholder experiences a loss, the insurer pays the claims amount from its portfolio once the claim is verified.
Insurance business models are based on carefully balancing the levels of risks due to loss events (and therefore the associated payout amounts) with the multiple premiums from policyholders. Insurance companies make money managing the portfolio to get more income from the premiums than the out-going payout amounts in the event of a loss.