The main purpose of insurance is for insurers to settle claims caused by accident or damage. Big data and predictive analytics have the potential to change this operational expectation by predicting and preventing claims. New technologies such as the Internet of Things (IoT) offer a completely new approach to the business model of insurance companies. By collecting, analysing, and using all sorts of data sent by insured customers or insured assets, insurance companies have a much better chance to prevent damages or accidents even before a claim occurs.

An insurer’s ability to process and analyse large amounts of varied data and data sources like Google does, to generate deeper business insights, is an emerging and fast growing mega-trend. Other industries such as retail banking, telecommunications, and energy have already shown how they are reshaping their business models by leveraging new data sources. For example, energy providers use smart metering to collect energy usage data of private households to improve energy efficiency. Independent Internet applications such as “smappee”¹ will turn private households into smarter, more energy-efficient homes, by providing real-time energy readings as well as consumption costs to allow appliances to be switched on and off remotely. By combining key mega-trends including “Industry 4.0” and emerging digitization capabilities, insurers have enormous potential to optimize their existing operating environment and business models.

Industry 4.0 is a trend that combines automation and data exchange with manufacturing technologies. It includes cyber-physical systems, the IoT, and cloud computing, and supports a concept called a “smart factory”. In short, cyber-physical systems integrate computation, networking, and physical processes and enable physical processes to affect computers. Smart factory environments converge virtual and the physical worlds through cyber-physical systems allowing the fusion of technical and business processes, key to delivering a new industrial age – the Industry 4.0 concept.

Within modularly structured smart factories, cyber-physical systems monitor physical processes and create a virtual copy of the physical world. This allows them to make decentralized decisions. Cyber-physical systems communicate and cooperate with one another in real time. The basic principle is that by connecting machines, material, and systems, businesses are creating intelligent networks along the entire value chain that can control each other autonomously. Some examples include machines that can predict failures and trigger maintenance processes autonomously, or self-organized logistical systems that react to unexpected changes in production. These emerging system interactions offer some great potential to turn business logics in the insurance sector upside down.

Enormous Potential for Insurance Companies to Gain Profitability

While existing business logics in the insurance industry are focused on innovating primarily across the claim settlement processes, future opportunities will concentrate on technical improvements to prevent claims from occurring in the first place. Following Insurance Europe’s report from the European Insurance and Reinsurance Federation, European non-life insurers paid out €313 billion in claims to insureds in 2014. Of that amount, €98.8 billion was for motor insurance, €94.1 billion for health insurance, and €53.7 billion for property insurance claims.² These figures show the enormous potential for insurance companies to optimize their financial balances and gain profitability by using innovative technologies to prevent claims.

The change of business models will also require a shift in current business logics. In the existing business models, premiums are the main focus to generate profits as insurance companies collect insurance premiums to invest on the capital market. With current ongoing low interest rate policies, this revenue model is at stake. With the appearance of innovative business models, insurance companies need to turn their gaze towards the very beginning of the process chain as it needs to avoid claims to retain profitability. It is a change from a backward-oriented approach towards a forward-oriented approach. This business approach requires a new alignment with all sorts of manufacturers to allow the provision of relevant data.

Big Data Technologies Enabling Data-driven Business Models

Big data analytics is the technique that automates the process of collecting, processing, contextualizing, and analysing large sets of data, commonly referred to as big data, to uncover patterns that help a business make better decisions. Big data analytics differs from traditional data analytics because it can capture and analyse data sets that are very large, move fast, and lack a common structure. In modern digital businesses, data is the currency that guides all decisions and actions. Complete and accurate analysis empowers insurance companies to develop data-driven business models. Unfortunately, the analytics tools and processes most insurance companies rely on are not designed to analyse the volume, velocity, and variety of big data in today’s modern business. To harness the opportunities of big data, insurance companies must adopt a big data analytics platform that is optimized to handle high volume and real-time data streaming.

With new data analytics tools in place, insurance companies can analyse multiple sources of data, from weather patterns to social media, which can help them to profile customer’s behaviour and to streamline costs, be more targeted with the risks they want to underwrite, predict fraud, or identify claims that have the potential to become very expensive. Furthermore, data providing insights on the usage of products or the lifestyle of an insured customer deliver even greater value to insurance companies. Insurance companies will be able to monitor and analyse maintenance cycles and repair statuses of machinery via intelligent sensors, security and safety measures of private homes via smart home devices, as well as health-checks cycles of insured customers via smart watches.

Identifying Sources to Collect and Analyse Relevant Data

Technology and innovative analytics algorithms are one thing. To reshape the existing business models of insurance companies, we also need to find ways to collect data relating to the state of customers’ insured assets as well as causes of damage at every possible point and event within that insured’s life. While more and more physical assets are fitted with sensors and network connectivity, insurance companies need to create new business processes to get hold of these important data sets. While it is in their best interest to improve the reliability of their machinery, manufacturers will take the opportunity to equip their products and facilities with sensors and network connectivity to control and maintain on-premise running assets. Manufacturers can monitor current machinery conditions as well as maintenance cycles to ensure the timely high reliability and availability of all kinds of assets.

This trend will help insurance companies to gather all kinds of relevant data once connected to the manufacturer’s databases. The information collected through big data technology is of high value to insurance companies as it delivers insights into the way policy-holders are taking care of their insured assets. Insurance companies therefore need to find an approach to align their interest with those of the manufacturers and get hold of the analysed usage and maintenance information. This will lead traditional insurance companies to innovate and become a “smart insurance provider”. Insurance companies therefore need to create dynamic business networks with all sorts of organizations such as car manufacturers, machinery suppliers, smart home technology providers, as well as health institutions to collect and analyse all kinds of relevant data (see Figure 1).

This business approach will have a deep impact on the business logic of modern insurance companies. Collecting, analysing, and interpreting big data requires new competencies within the industry and new roles, such as network managers and big data analysts. Network managers will be responsible for organizing and orchestrating the new insurance ecosystems to ensure a constant flow of data from all kinds of data sources. Data analysts, however, will take charge of extracting relevant data points and translating them into pricing decisions. This will help insurance companies to improve their claim statistics and dramatically reduce claim volumes. This approach landmarks a forward integration of insurance companies to make use of digital technologies and significantly increase profits.

Individualized Offerings Based on Prevention Efforts

When collecting machinery and customer data to reduce claim volumes, insurance companies can offer much better terms and conditions to their customers, helping them to prevent accidents or damages. Insurers can also develop completely new individualized pricing models based on the prevention efforts undertaken by the insureds. The more the insureds take care of their assets, the more likely it is that claim volumes will decrease. This means that insurers will be prepared to calculate and offer far more attractive premium rates. This will finally lead to a win-win situation for customers and insurance companies.

But existing insurance companies need to watch out carefully, as this innovative business approach is likely to bring new competitive threats. It allows aggressive startups and data specialists to step into the market and redefine existing business logics. For example, UK-based insurance company Drive like a girl³ offers premiums that are connected to the driving style of the insured. The company fits a telematics box about the size of a mobile phone into the customer’s car. Telematics technology allows the gathering of accurate information about the individual driving profile of each customer, so the insurance company can calculate individual premiums instead of just offering gender-neutral premiums based on group statistics. Established insurance companies are well advised to start their data activities right now and learn how to profit from using big data to extend their current business model and prevent newcomers from gaining significant market share.