With technological revolution taking over just about every industry, the applications of the likes of machine learning, artificial intelligence, etc. are no less relevant to the auto insurance industry. In the era of smart phones, predictive analytics, smart contracts and blockchain, the auto insurance industry is set for a huge transformation to improve efficiency, reduce costs and provide greater solutions for customers.

In the current scenario, various kinds of applications are being developed to process claims quicker and artificial intelligence being applied to manage large chunks of data. In addition, predictive analytics technologies are used to assess behavioral habits of drivers and develop price insurance packages accordingly. Furthermore, autonomous vehicles are now applying telematic devices or black box insurance to develop risk profiles for autonomous vehicles. The market for telematics in fleet management is expected to reach $11.5 billion globally by 2021, growing at a compound annual growth rate of 18%. These devices are also able to track high risk drivers and stolen vehicles to improve on-road safety.

Generally, all the big companies are testing waters with smart technologies in auto insurance management. The likes of TomTom, Fleetmac Group, KORE, Allstate Drivewise, etc. are leading the way in the development and adoption of ingenious technologies, while there are other startups involved in the space as well. This article takes a detailed view of smart technologies being applied in the auto insurance industry and a look at the most prominent names involved in the space.

Workflow automation with machine learning and robotics

Auto insurance companies deal with comprehensive paperwork, underwriting and follow-ups on a daily basis. Automation in this respect allows companies to reduce costs and labor hours that are spent on these tasks, freeing the workforce to carry out more creative and important matters. A report from Fukoku Mutual Life Insurance states that the company was able to replace 34 of its employees with artificial intelligence, upping productivity by over 30 percent.

Along the same lines, Robotic Process Automation (RPA) addresses routine and repetitive work efficiently by applying human designated instructions. Using RPA practices, PZU, a European auto insurance company claimed to have increased 100 percent accuracy in data entry while also enhancing operations in preliminary analysis of damage claims and payments. UIPath is such an RPA foundation that builds automation platforms powered by robotic technologies and facilitates the auto insurance sector, along with banking, healthcare, manufacturing, etc.

Automation in claim processing using machine learning

Conventionally, processing claims is a cumbersome process that takes a lot of time. A significant amount of data and evidence has to be collected before a decision for payout is made. Among other smart technologies, machine learning (ML) is playing a vital role in reducing time and costs associated with claim processing. ML algorithms are applied to observe incident footages and landscape imagery using satellite images and drones, eliminating a significant amount of human effort, time and cost.

State Farm is an artificial intelligence company, specializing in object recognition technology applications. The company has developed a claim reporting application that uses object recognition technology to help make auto-insurance claims easier. Using the technology, users can capture images and videos of the insured vehicle and the incident to process and populate data automatically into a claim. Using the app, claims can be submitted from anywhere in the world, with the ability to select policy information rather than having to type it in.

Telematics insurance

Telematics insurance is a state-of-the-art technological car insurance instrument to manage road accidents better. Telematics devices get installed directly onto a vehicle, equipped with GPS system, motion sensors and analytics software. These devices are able to track car speed, location, driving distances and crash accidents, etc., along with other driving-related data. The recorded data is then transmitted to the insurance company via mobile internet for analysis and added to the customer’s personal account. After analyzing the gathered data using analytics software, insurance companies are able to make tailored insurance plans for users.

Auto insurance companies can segment users on the basis of charging them for irresponsible driving and sending rewards for safe driving. Using telematics, business models such as pay-as-you-drive (PAYD), pay-how-you-drive (PHYD) and usage-based insurance (UBI) can be applied. UK-based telecommunication giant O2 has launched a telematics-based car insurance product that detects driving habits and scores drivers on the mobile application. Drivers also get rewarded for driving safely and are able to view their data.

Peer-to-Peer (P2P) insurance

P2P insurance is a popular and highly advanced business tool that allows auto insurance companies to form a network of people that cover similar risks by creating a single finance pool. After each coverage period is finished, the leftover money in the pool is refunded and customers are able to minimize on their costs while mitigating claim conflicts.

A good example of a P2P insurance network is Friendsurance, which forms groups of up to 16 people connected via a mobile app. With this network, whenever a vehicular accident occurs, the incident is claimed for via Friendsurance and is covered. When the contract expires, all members of the pool get pre-agreed cashbacks from funds available in the pool. P2P in auto insurance is still at a nascent stage of development and is prone to drawbacks such as fraud, ethical issues among members and difficulty in achieving consensus.

Future prospects

Digital technologies continue to disrupt the auto-insurance space and are shifting businesses to form more personalized and highly efficient workflows for users. Automation in routine and recurring tasks potentially saves greatly on labor effort and cost, while machine learning algorithms to assess incidents and process claims eases time requirements. Furthermore, telematics and P2P insurance technologies are enabling newfound ways to manage insurances, introducing PAYD and UBI models. Overall, with the integration of smart technologies, the auto-insurance industry can not only expect to provide more accurate risk assessment to customers and enable more proactive decision making regarding incidents, but also enable a better customer experience and become more and more insulated from frauds and scams.