Data standards such as Polaris` e-commerce standards and ACORD`s electronic standards, forms and software tools facilitate the successful development of smart grids by improving operational efficiency, reducing the cost of exchanging data with trading partners, and defining common business processes throughout the value chain. It is important to note that NBS are more flexible than vertical integration in supply chains, as new organizations can be transferred to the network and organizations that are no longer needed or decide to leave can be separated. They offer more stability than an electronic marketplace, so trust and continuity can be built into the relationship. New technologies such as blockchain could be used as part of digital infrastructure to build a smart business network, and there are warning signs that companies like b3i enable close relationships between insurance and reinsurance companies for the secure exchange of risk data based on a common language. In the insurance markets, candidates for the role of orchestrator are primary insurers, brokers and reinsurance companies. The role requires a combination of influence and prestige resulting from an organization`s existing position in the insurance value chain, combined with a high level of expertise and the ability to innovate and lead digitally. Insurance policies require a variety of data types that vary depending on the line of insurance, such as private customers.B auto insurance or damage insurance, and the purpose of the communication, for example. to exchange customer data, prevent fraud or negotiate a business between a customer and an insurance provider. However, a number of broad categories can be defined for all insurance markets: in specialised consumer markets such as healthcare and B2B relationships between insurance companies and reinsurance, as well as in capital markets, smart business networks will be highlighted. SBNs require close coordination between their constituents, and the role of the ”orchestrator” is therefore crucial. It is a major organization that builds the network around a set of common strategic objectives and plays a leadership role in areas such as technology strategy, innovation and the continuous evolution of the network, including its members. Established insurance companies are the natural contenders for this role, although reinsurance companies and brokers can also be legitimized in this role.
SBNs offer an interesting opportunity for InsurTech companies because SBNs are inherently flexible in terms of new relationships, including technology partnerships, and are therefore more likely to use InsurTech services. Data trusts have great potential to be applied to highly sensitive data such as data loss and loss or the exchange of information between direct competitors. For example, in health insurance markets, it may be necessary to combine genetics, insurance data, and patient information to create AI-based services. Data synthesis is necessary for the development and refinement of AI algorithms, but individual data owners may not be willing or able to share the data with other organizations, so a separate trustee in the form of a data trust can overcome seemingly insurmountable hurdles. A simpler example would be combining claims data from competing insurance companies to combat fraudulent claims. 1 OECD. Technology and innovation in the insurance sector. www.oecd.org/pensions/Technology-and-innovation-in-the-insurance-sector.pdf (2017). 2 Ralph, O. Insurance experts appreciate start-ups that reach the big moment. Financial Times (2020).
3 Deloitte. From Secret to Mastery: Unlocking the Business Value of Artificial Intelligence in the Insurance Industry From Secret to Mastery: Unlocking the Business Value of Artificial Intelligence in the Insurance Industry. www2.deloitte.com/content/dam/Deloitte/xe/Documents/financial-services/Artificial-Intelligence-in-Insurance.pdf (2020). 4 Timms, P., Hillier, J. & Holland, C. P. Increase data exchange or die? A first look at natural disaster insurance. eartharxiv.org/repository/view/2059/ (2021) doi:doi.org/10.31223/X5K313. 5 Christensen, C.M.
The innovator`s dilemma: when new technologies cause large companies to fail. The Innovator`s Dilemma: When New Technologies Cause Large Companies to Fail (Harvard Business School Press, 1997). 6 Denenberg, H.S. The legal definition of insurance: the principles of insurance in practice. On the. Insurance against risks. 30, 319–343 (1963). 7 Eling, M. & Lehmann, M. The impact of digitalisation on the insurance value chain and risk insurability. Geneva Pap. Insurance against risks.
Topics Practice. 43, 359–396 (2018). 8 European Commission. What are the consent requirements of the GDPR? gdpr.eu/gdpr Consent Requirements/(2020). 9 Malone, T. W., Yates, J. & Benjamin, R. I. Electronic Markets and Electronic Hierarchies. Community.
ACM 30, 484-497 (1987). 10 Polaris UK Ltd. 11 Products Heck, E. V. & Vervest, P. Smart Business Networks: How the Grid Wins. Community. ACM 50, 28–37 (2007).
12 Tanguy Catlin, Lorenz, J.-T., Nandan, J., Sharma, S. & Waschto, A. Insurance Beyond Digital: The Rise Of Ecosystems And Platforms. McKinsey Co. 16 (2018). 13 Zarkadakis, G. Data trusts could be the key to better AI. Harv. Bus. Rev. (2020).
14 Ngai, J. Building a Technology-Enabled Ecosystem: An Interview with Jessica Tan of Ping An. McKinsey Q. (2018). It is well known that sharing data between individual companies improves operational efficiency, increases the transparency and accuracy of data within a value chain, and enables a much more efficient and coordinated response to external market changes (e.g. B, changes in demand, new product designs and regulatory requirements). The latest TECHNGI survey of insurance industry experts confirms that they see many significant benefits for better data exchange in the insurance value chain. While there is strong evidence of innovation in bilateral agreements between close partners, experts also confirm that there are still significant barriers to wider data sharing, which can be divided into three groups4: In the TECHNGI survey, the panel of industry experts was asked how and when the exchange of reinsurance data would change and over what period of time.
The majority expected a significant change within a time horizon of 3 to 5 years, but not within 12 months. They felt that the result would likely be a mixture of the scenarios described above. It is not clear which, if any, will dominate, although participants preferred electronic markets. The 3 to 5 year delay is important to illustrate a certain reluctance to change, supported by a remarkable minority of survey participants who still see the status quo in 3 to 5 years. However, our interpretation is that there is a much greater urgency for change and that the inertia of established companies is typical of the innovator`s dilemma5 and underestimates the disruptive impact of data platforms and ecosystems. Electronic marketplaces operate effectively in areas where products are standardized and there is no need for close cooperation between buyers and sellers. Electronic markets will therefore continue to thrive in consumer markets where insurance services are standardized and well understood, auto and home insurance comparison sites .B. There are also standardized markets in B2B markets where the concept of open data is likely to thrive. Here, the entire industry is committed to exchanging information and not using data ownership as a basis for competition. Oasis, for example, is an open hub that enables the free exchange of environmental data and risks, supported by a common modeling language. The common good and the need for a better global understanding are more important than the competitive advantage of a single company.
A data platform shifts the focus from insurance data to a data platform that can be managed by an e-commerce or automotive company, or a tech giant like Tencent, Google, or Apple. In this scenario, insurance data would be part of a much larger ecosystem12, and the insurance service would be subsidiary to other services such as transport and mobility, healthcare, real estate services or e-commerce. Tech giants potentially have significant advantages in data and analytics over incumbent insurance companies and could use them to integrate and integrate InsurTech companies into their platform, which would provide specialized industry expertise. Insurance markets are defined by the contracts concluded between the insured and the insurance undertaking6 and by the exchange of information between the customer and the insurance value chain7, which consists of a number of different types of organisations linked by relationships with a market network. Figure 1 shows schematically how retail and commercial customers, insurance companies, brokers, electronic markets, reinsurance companies, financial markets and regulators are connected in a complex insurance value chain. A data trust is a legal and technological construct that enables the compliant, ethical and secure exchange of sensitive data between a network of data providers. Willis Towers Watson is actively exploring this concept and has tested its use in the insurance industry.13 Trust in data can remove much of the friction related to the business, legal, and technological barriers identified in the TECHNGI survey. .