Big Data in Insurance: From product development to claims management
Updated: Jun 16, 2020
Multiple segments of the insurance industry have found ways to deploy big data techniques, but initially it is looking most useful to health, life, motor and property insurers. In Health, when combined with smart devices that can record client data, health insurers are encouraging clients to live healthy lifestyles, providing rewards for those that do. In motor insurance data is being collected through “black boxes” placed in vehicles that can record driver ability and care and adjust premiums accordingly. In Home insurance, Big Data collection is allowing insurers to become an asset in protecting the home rather than just paying out on claims.
Big Data is providing business benefits to those insurance companies that are pursuing it in earnest. Big Data analytics is enabling insurers to shift towards customer-centricity by analyzing preferences, behaviors, and attitudes. It can be crucial in enabling insurers to identify fraudulent activity in the event of a claim and can play a significant role in enriching the customer experience, resulting in increased customer satisfaction and retention. Insurers can face challenges in understanding customer profiles, as customers may not always want to reveal their true identities or characteristics. Insurers can use Big Data analytics to overcome the problem of adverse selection, as well as to access a multi-faceted customer view to settle identity issues and establish matches between an individual and their identity and profile.
The use of data in insurance is still relatively limited. There are several high-profile examples, but these are isolated. The immediate future for the industry will be defined by a data race, with insurers trying to work out how best to analyze and use data to avoid being left behind by competitors. There is a strong argument that the biggest challenge facing insurers in the whole insurtech revolution is not coming from start-ups, tech companies, or expensive system upgrades but simply inactivity and allowing competitors to edge ahead. While incumbents have struggled to adapt, it is only a matter of time before some big players gain a competitive advantage by doing so.
There are a few key areas that insurers need to focus on if they want to make Big Data work for their business. This includes creating an environment that allows innovation to thrive. Insurance companies have been criticized in the past for lacking truly innovative new ideas and Big Data opportunities could be easily stifled by a change resistant culture. Effective partnering is essential; there are many expert Big Data companies that can provide solutions, insurers need not waste resources on developing expensive bespoke analysis techniques, when many already exist.
Most of the world’s biggest insurance companies have been exploring data analytics techniques for decades, but the information locked in Big Data collection is still relatively new to insurance. For the most part the leading insurers’ actions include close monitoring and consultation with Big Data analytics suppliers and finding ways to capitalize on their better understanding of clients’ needs and actions.
Big data in life and health insurance
The health insurance sector is where the impact of Big Data is most evident, with wearable technology increasingly used by large insurers, which offer cheaper premiums, reward schemes, and health benefits in exchange for personal data. Leading the way in the UK is Vitality Health, which offers discounted Fitbit devices, cheaper premiums, and rewards for customers reaching a target of 10,000 steps per day. While wearables are designed to monitor fitness and promote healthy lifestyles, the next step is in preventive care, where insurance becomes more of a service. Currently there are many private healthcare companies that offer round-the-clock access to doctors, generally via an app. The more access to consumer data that insurers are permitted, the deeper this can develop – from body sensors, exterior monitors, and workout machines to monitoring lifestyle through social media posts. Cheaper premiums, fewer claims to pay out for insurers, and the younger generation being more comfortable sharing personal data mean these steps appear inevitable. Fitbit, for example, has done an impressive job in making people wear and care for what is collecting data for them. Health insurance company FitSense is looking to use health data to bring more diabetics – a group that has always struggled to find affordable insurance – into the market.
Big Data in motor insurance
Motor insurance has already been influenced by Big Data. Telematics and driver analysis technology are not yet in common usage, but the popularity of the technology is increasing. The benefits for customers are clear: if you agree to have a black box installed in your car and drive safely your premiums will go down. Driver analysis can be used in two ways at present: pay as you drive and pay how you drive. The former bases premiums on the amount of miles driven, while the latter considers a variety of factors, including speed, acceleration, cornering, braking, lane changing, fuel consumption, and location. A recent high-profile story saw Admiral attempting to use a form of price optimization, whereby it would judge noninsurance-related factors on Facebook. Factors included the length of status updates and the manner in which people made arrangements – for example, naming a specific time or just saying “later” – hinting at how insurers are looking at other ways to price premiums. However, this was eventually blocked by Facebook. One start-up potentially demonstrating the future of motor insurance is Octo Telematics. It shares drivers’ details with insurers, which then bid to have them as customers. This will lead to cheaper premiums for safer drivers and, theoretically, less risk taken on by insurers. In addition, if driverless cars become popular, insurers will need to dramatically alter how they work. Firstly, there will be the question of whose fault an accident was, the system or the driver, and secondly whether motor insurance is even necessary if driverless systems become flawless (or as close to flawless as is possible). With changes happening so quickly and new possibilities emerging, a major consideration for the future of the industry is how regulators will cope.
Big Data in property insurance
Property insurance is arguably the area with the most potential to use Big Data, but the price of equipment means it is currently restricted to the top end of the market. With connected home devices customers can monitor everything through a mobile app, from the risk of pipes and boilers bursting to temperature, security, and water leaks. Problems can be solved either through the app or, in an emergency, by calling someone to help. This is very much an illustration of insurance as a service, with the customer and insurer in contact on a daily basis and the insurer taking on the role of protecting the home, as opposed to just paying costs. In the UK buzzmove provides removal quotes by pricing up all items in a house and using the data to work out insurance premiums. The key issue for the future is regulators will decide who owns the data: either the customer or, once the data has been submitted, the insurance company. Nest Labs, a smart home tech company, was acquired by Google in 2014. It fits smoke alarms and carbon monoxide monitors free of charge. Customers can receive a discount from insurers on premiums and, in return, insurers receive data from the device. The pattern developing suggests that people are willing to give up personal information if it is easy to do so and they receive something in return. Insurtech expert and Startupbootcamp mentor Damien Seaman explains how smaller, noninsurancebased companies are influencing the market: “The trend is that start-ups are developing clever ways to look at the data that insurers don’t have the time, money, or expertise to look at themselves.”