We now create and consume quintillions of bytes of data daily with the rise of IoT devices, and 463 exabytes of data will be generated each day by humans as of 2025. Absolutely everything we do daily generates data, from GPS to social media to contactless pay. Big data is essentially wasted if left untapped, which is why it usually gets sold to marketers or advertisers, who then use that data to serve consumers with personalized ads.
Not all big data is used for advertising, however. The purpose of data collection is to better help companies understand their customers and their needs, and then serve those needs. Big data is found in almost all businesses in all sectors, as they usually are flooded with data, even if it is not collected or logged.
Rewriting Insurance With Big Data
While big data is important, it is not the be-all and end-all. All the information in the world is useless if it is not utilized properly. Within the insurance industry, data has been a primary driving factor for several years now. However, to say that it has been utilized efficiently would be a stretch. This is why Genadi Man, CEO of kasko2go, an InsurTech startup focused on car insurance, believes that the current industry challenge has arisen: insurance big data and analytics cannot catch up to the pace of technological change without something to bridge the gap.
Kasko2go, which is based in Switzerland, is known for its advanced tech solutions for the motor vehicle insurance industry. They are dedicated to building the industry’s first risk assessment solution based purely on irrefutable data and believe that is also the key to getting accurate price premiums. This information is made available in the form of risk reports which provide information and data that can be applied to insurers’ actuary and underwriting work to improve their models and pricing. This is certainly fair when considering the fact that low-risk drivers typically bear the high costs of high-risk drivers. Their premium accident probability product and report, called Normal Sigma, makes use of AI and environmental parameters that have a proven influence on accident rates. In addition to insurers, the reports can also be sold to B2B clients, such as car rental companies, so they (and their customers) can similarly benefit from the information.
There is, of course, more to consider for coverage outside of cars, and this is where services such as the Hong Kong-based YAS Insurtech steps in. YAS Insurtech ensures that day-to-day life is not uprooted by accidents or losses in any situation. From hiking trails to public parks to public transportation, coverage exists. This is Hong Kong’s first microinsurance marketplace that utilizes blockchain and data analytics to adapt to customer preference to establish customer loyalty. This is all enabled through decentralized blockchain to support speedy applications and claims processes.
Staying Informed By Observing and Predicting
The insurance industry is already shifting away from “one policy fits all” plans. Technology is finally allowing for companies to use real, accurate data to gauge individual behaviors. In the case of YAS, for instance, the company offers personalized and customizable microinsurance. This involves the use of monitoring devices that provide information about a customer’s driving habits. However, driving habits are not significant without context.
In an effort to get access to greater context for richer data, kasko2go partnered up with HERE Technologies, a global location data, and technology platform that compiles and analyzes advanced traffic data. Thanks to that collaboration, kasko2go now receives high-quality traffic data from three million kilometers of road in the DACH region (comprised of Austria, Germany, and Switzerland,) which can show the volume of cars at a specific road at any given time. Integrating empirical, behavioral, and location-based information together makes it possible for kasko2go to offer a highly accurate risk assessment solution to the car insurance industry.
Big data has had a transformative impact within the industry in its short time and is not going away any time soon. It is a valuable tool for risk management, able to predict from existing data possible liabilities as well as ease fraudulent claims. As the number of IoT devices only increases, so does the data load. With all this in mind, insurers best ensure that they keep up with AI and machine learning advancements sooner than later, and make adjustments in their processes accordingly—lest they get left in the dust.
Source: Benzinga
