Data sharing models in the insurance industry | 7wData

• Read original article here

There is a drive for efficiency in Insurance markets, accompanied and enabled by changes in the way that data is captured, processed, stored and shared. Digital innovation and data sharing strategies are designed to reduce costs and develop new, innovative products, services, and distribution channels throughout the Insurance value chain. With the competitive threats of new entrants into the insurance industry, i.e., AI start-ups and technology giants, there is a strong incentive for established firms to respond and adapt to take advantage of advanced digital technologies and Artificial Intelligence (AI) applications. Our recent survey of industry experts expects transformation to occur in 3-5 years but the panel of experts do not perceive an immediate threat over the next 12 months. This is a classic example of the innovator’s dilemma for established firms in markets that are in transition, where clear benefits can be seen, but change is risky and the current markets are still profitable.

Incumbent insurance firms face two key questions. What are the future data sharing and market scenarios, and how soon will these occur? In this article, we explore how data sharing is changing across the insurance value chain, introduce four data sharing models and market scenarios, and identify the imperative strategic choices facing the insurance industry.

Insurance markets are defined by the contracts agreed between the insured and the insurance firm, and the exchange of information starting from the customer and then along the insurance value chain, which is comprised of a set of different types of organisations connected together through relationships to form a market network. Figure 1 is a schematic illustration of how retail and business customers, insurance firms, brokers, e-marketplaces, re-insurance firms, capital markets and regulators are connected together in a complex insurance value chain.

Insurance policies require a diversity of data types, which vary between policies dependent on the particular insurance line, e.g., retail automotive insurance or property and casualty, and the purpose of the communication such as to share customer data, fraud prevention, or broker a deal between a customer and an insurance provider. However, some broad categories can be defined for all insurance markets:

It is well established that data sharing between separate companies improves operational efficiency, increases data transparency and accuracy within a value chain, and enables a much more effective, coordinated response to external changes in the marketplace (such as changes in demand, new product designs and regulatory requirements). The recent TECHNGI survey of insurance industry experts confirms that they see numerous significant advantages to better sharing of data in the insurance value chain. However, although there is strong evidence of innovation in bi-lateral agreements between close partners, the experts also confirm that there remain significant barriers to wider data sharing, which can be categorised into three groups:

This raises the issue of how these barriers will be overcome, how quickly, and by whom.

In addition to the continuation of the current insurance value chain shown in Figure 1, which is a system characterised by the dominance of bi-lateral relationships, experience in other sectors suggests that four market scenarios could emerge: electronic marketplaces; smart business networks; data platforms & ecosystems (these would typically be controlled by a single, large technology firm); and data trusts.

Electronic marketplaces are digital platforms that connect multiple buyers and multiple sellers together, with fast and low cost switching between competitors. In markets where the level of inter-dependency between the customer and the supplier is low, and where a strong ongoing relationship is not crucial to delivery of the service, then electronic markets are economically attractive.