Innovations in Decentralized Insurance: Peer-to-Peer and Mutual Aids

Runhuan Feng, PhD, FSA, CERA is a Professor of Mathematics, Statistics, Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign. We invited Dr. Feng to share his theoretical research into mutual aids and peer-to-peer insurance models. As proponents of disrupting the insurance status quo, Dr. Feng’s research offers insights into the evolution, transparency and fairness we must achieve in insurance.

InsurTech and Shared Insurance

The InsurTech industry is on the rise worldwide. A variety of innovative business models have emerged with the potential to disrupt the traditional insurance industry using technologies including blockchain, artificial intelligence (AI), Internet of Things (IoT) and big data. These new tools could resolve major challenges in the current insurance industry and improve efficiency in underwriting, risk pooling and claims management.

Along with this changing technological landscape, the sharing economy, a socio-economic system built around the sharing of resources, is evolving and expanding in a wide range of industries. In contrast with the traditional server-client model in which a central authority provides services to all, the peer-to-peer nature of the sharing economy enables the exchange of goods and services among users without the heavy cost of intermediaries. The rise of the sharing economy brings a new channel for individuals to share their underutilized assets and receive rewards.

These two forces have started to merge to produce new insurance models – mutual aids and peer-to-peer (P2P) insurance – that incumbent players should watch carefully.

Mutual Aids
Mutual aid insurance is built on a network of members facing a common risk that enables them to share financial costs. Every member receives the promise of mutual aid in the case of covered contingencies and commits to carry the cost of losses from other members within the risk pool. This concept is not a new one—early forms of mutual aids existed long before modern insurance. In ancient Rome, burial societies covered the funeral expenses of a deceased member within a local community. In today’s internet era, online mutual aid platforms can reach much larger communities without geographic limitations and enforce a more effective loss sharing mechanism via electronic payments. As of last year, the top ten mutual aid platforms in China have amassed over 300 million users and offered healthcare coverage for over 100 critical medical conditions and illnesses. One of the most successful mutual aid platforms is Xiang Hu Bao, a service of Ant Financial under the Alibaba group in China.

P2P
P2P insurance is another internet-enabled business model, popular in Europe and the United States. P2P insurance typically facilitates risk sharing in a small group of family members, friends and other social relationships. All members contribute to a common fund, a portion of which is used to buy an insurance policy with a high deductible. Claimants’ losses are first paid out of the common fund. Any excessive amount beyond the capacity of the common fund is paid by the insurer. Depending on the actual losses, members may receive a refund of the remaining balance in the common fund. The success of Lemonade in the US is a testimony to the viability of such a business model.

The two models have several differences among them and compared to conventional insurance. Conventional insurance and P2P insurance require ex ante payments (before the event), whereas mutual aid cost sharing is typically done ex post (after the event). It is often the case that members join a mutual aid platform without any initiation fee. The cost of coverage only occurs when there are actual benefit payments to claimants within the community. This ex-post mechanism makes mutual aids different from conventional insurance and P2P insurance because the funding of coverage arises after losses occur and is guaranteed to be sufficient without any reserve or capital.

However, the self-sufficiency of mutual aid funding comes at the expense of members’ uncertain payments. In contrast to fixed premiums in conventional insurance, the cost sharing in mutual aids can vary from period to period. The more losses occur, the higher payment is required for each member. Nonetheless, this issue is addressed in practice by most mutual aid platforms by imposing limits on mutual aid cost-sharing.

Further, mutual aid and P2P achieve cost reduction by different means. P2P insurance commonly runs a risk pool for property risk and its members are usually connected through social relations (e.g., relatives and friends). The social interconnectedness of policyholders helps reduce moral hazard as members watch out for each other and share the financial burden of losses with each other. For example, the cost of insurance fraud is heavier with a smaller population so it behooves policyholders’ to self-monitor. Also, the membership size of P2Ps is rather limited in contrast to mutual aid coverage which could include millions of members. Mutual aids can take advantage of the economy of scale and the law of large numbers, which are unavailable for the P2P insurance model. And the scale for mutual aids can be much larger than traditional insurance because there are not the costs associated with policy servicing and entity maintenance.

Why it Matters

Currently, both insurance models are in an infancy stage. Regulators do not have a firm oversight model due to the lack of comparable experience in other countries. As the models mature, a regulatory oversight model will provide much needed structure to the market especially on the topic of actuarial fairness. Empirical analysis from my research team at University of Illinois at Urbana-Champaign suggests that there are equity issues with many current mutual aid plans in the market.

In the traditional insurance market, differential pricing is a mechanism used to reduce adverse selection. Most existing mutual aid plans use differential treatments for broadly defined age groups and on an ad-hoc basis. For instance, most platforms offer policies to three age groups: youth, middle-aged, and elderly. All members share mutual aid costs equally, but the three groups are eligible for benefits in proportion to 3:2:1. However, the morbidity rates of the three age groups are not in proportion to 3:2:1. The cost difference between conventional insurance and mutual aid plans for the middle-aged is much lower than that of the elderly, which to some extent shows that middle-aged groups subsidize the costs of the elderly group. The result is that the more discriminated age groups – like middle-aged or youth – have higher tendencies to lapse, which suggests that members are sensitive to the fairness of mutual aid plan rules. Right now, these plans are benefiting from a growth dividend so new dollars are more than offsetting lapses, but eventually the loss profile for these plans will deteriorate as the plans reach steady state.

New entrants, maturing models and more structure will inevitably work out these kinks. Incumbent players should pay attention to these developments for one key reason – these new models will have a better cost advantage than even direct writers. The core difference of these models is that they alleviate costs related to centralized delivery models as well as excessive stores of capital for future losses. And because the market has become more price-sensitive in recent years, it creates a situation that is ripe for these new players to take a significant share of the premiums. Incumbent players will need to either spin up, acquire new entrants or increase the value proposition of having agents, brokers, and adjusters. Otherwise like disruption from Uber on taxi cabs and Airbnb on hotel chains, conventional insurers will start to feel the pressure of companies like Xiang Hu Bao and Lemonade.

Research into Mutual Aid and P2P

Our research work offers a theoretical framework in which various designs of decentralized insurance can be analyzed and compared, including mutual aid and P2P insurance. By using the theory behind this research, we have the ability to influence the P2P insurance market and other financial industries such as utility sharing (solar energy) or shipping/moving companies. Based on our research, we believe that the ideal decentralized insurance should meet the following criteria:

1. Universal inclusiveness
   Decentralized insurance or risk sharing mechanisms should provide access to all people including unserved or underserved low-income communities. For example, integration with micro-insurance and other micro-financing tools could be essential in gaining community trust and serving their needs. Decentralized insurance can be used to advance social movements, such as eradicating poverty and racial injustice, etc.

2. Disintermediated and shared governance
   With the removal of an intermediary or central authority, a decentralized product could empower ordinary people to take charge of their own financial arrangement. No one person/entity dictates the terms of policy. There is an equitable distribution of market power and shared governance among all participants. This helps develop more trust in the system and more responsiveness to changing needs of participants. A democratically designed risk sharing mechanism should be more appealing to millennials with their changing expectations of financial services.

3. Voluntary participation
   In an ideal world, no government mandate is needed. The product design should be equipped with sufficient incentives for participants to join voluntarily. This goes back to the old philosophy of “one for all, all for one.” Risk sharing helps develop a sense of community.

4. Transparency
   A decentralized risk sharing system should be open and transparent. Every participant can audit all financial transactions. Blockchain could be the right tool for implementation.

5. Cost effectiveness
   Decentralized models provide lower cost alternatives to traditional insurance. The reduction can be achieved through economy of scale, cutting out the middleman, streamlining services and/or lowering compliance costs. Building on blockchain may help reduce underwriting costs, claims investigation and administrative overhead.

6. Actuarial fairness
   Every participant should be treated equally in mathematical rigor, sharing cost commensurate with the risk he or she brings to the system. While there could be different standards of fairness and equity, all could be formulated and tested by theoretical means and experimental designs. This is important to avoid adverse selection and to maintain the long-term economic viability of a decentralized system.

Our focus is on architectural designs of decentralized risk sharing models. There has been much development in academia on the various forms of risk sharing of both mutual aid and P2P insurance. Our hope is to partner with industry players to bring experimental and structural designs of decentralized insurance to practice.

Get Involved

If you are interested in partnering on this practical research, please email Professor Runhuan Feng at [email protected].

About Runhuan Feng

Runhuan Feng is a Professor of Mathematics, Statistics, Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign. He is the Chair of the Education and Research Section Council of the Society of Actuaries. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He serves as an independent consultant to many industry organizations as well as nonprofits and government. He also provides expert testimonies for public policy assessment and actuarial analysis. His consulting work has been used by Illinois General Assembly for pension-related legislative proposals.

Runhuan has a wide spectrum of research interests in mathematics and economics of risk and uncertainty in the financial world. He has published extensively on top-tier actuarial and quantitative finance journals. He is an Associate Editor of Annals of Actuarial Science, North American Actuarial Journal, Methodology and Computing in Applied Probability and Quantitative Finance and Economics.

As an applied scientist, Runhuan strongly believes that the most interesting research problems are discovered in response to the changing needs of the industry and society. He co-founded the Illinois Risk Lab, which facilitates research activities that integrate experiential learning for Illinois students and address industrial problems. Runhuan’s research has been recognized in the practitioners’ community through his applied technical contributions and presentations as invited speakers at industry conferences.