Data-driven innovation in the insurance sector

Data is being used by new entrants in many industries and the insurance sector is no different. CIOs and other senior managers can learn a lot from examining the strategies adopted by startups as they both challenge and partner with incumbents.

Data is a core input to the insurance sector where it is used to calculate and put a price on risk. While established insurance brokers and underwriters may be experts in risk management, new entrants are leveraging new sources of data and analyzing it in ways which are transforming the sector. Incumbents have an advantage in terms of the data they already hold and the trusted brands they manage but a number of the largest firms are partnering with data-driven startups to create innovative products and services.

4 key parts of the insurance value chain are being transformed by the application of data: customer prospecting, risk calculation, application process streamlining and the creation of new business and revenue models.

Finding and helping customers with data

The web is awash with the data users leave behind as they use search engines and post and share content across social media platforms. Tools for social media monitoring are widely available and allow companies to track when keywords are used across a range of social platforms. Responses can then be tailored to respond and offer suggestions for possible products.

Consultants, Accenture Interactive recently created a social media listening service for a major US insurer using the Salesforce Social Studio suite of applications to allow the company to monitor in near real-time what was being said about them online. The result was a system that allowed the insurer to view social media comments and posts mentioning them within 10 minutes of posting and join in the conversation where appropriate.

Calculating risk from a selfie

In 2016, Legal and General America partnered with startup Lapetus Solutions to allow consumers to apply for life insurance by simply uploading a selfie. Their SelfieQuote service claims to be able to estimate an applicant’s age, gender and body mass index (BMI) from a single photo. It uses Lapetus’ AI-based facial analytics platform to streamline the application workflow and normally lengthy form filling for such a process. While this may appeal less to more mature consumers, the company hopes it will be attractive to a more tech-savvy audience that may not have previously considered life insurance.

Recent research from McKinsey indicates that while 70% of people may go online to start gathering information about life insurance options, fewer than 30% go on to complete the purchase of a policy online. As a new generation of digitally native consumers enter the market, companies in all sectors need to be sure they are not putting barriers in the way of bringing them on board.

Using data to improve the claims process

Apart from annual renewals most consumers have no dealings with their insurers after the initial application process unless they need to make a claim. Traditionally, this has been a cumbersome process for many insurers due to the checks which have to be made and the paperwork that goes with it. This is expensive for the insurer and often frustrating for the customer. Increasingly sophisticated bots can help with speeding up customer interactions and the application of AI and machine learning algorithms can reduce fraud through pattern detection.

However, the integration of external data can also improve the customer experience and form part of new premium, value-added insurance products. Berkshire Hathaway’s AirCare travel insurance offers automatic refunds to clients if flights are delayed or cancelled by monitoring third party flight data in real time. According to Forrester Research, some customers find out flight delays from an AirCare refund before hearing about it from the airline itself.

Building new business and revenue models from data

The rise of the Internet of Things (IoT) and associated technologies are transforming the ways that data is being generated from everyday activities. This is particularly apparent in the automotive insurance sector where the installation of black boxes in drivers’ cars is allowing much more personalized premiums based on actual driving behavior. Root Insurance in the US has captured more than 1 billion miles of driver data and is using this in conjunction with its mobile app to create a more consumer-focused service than many incumbents in the 210 billion-dollar US auto insurance sector are able to offer. Only 3 years after founding Root raised 100 million dollars in funding valuing the company at 1 billion dollars. Insurers that can collect user data in this fashion will create powerful barriers to entry for latecomers to this new world of data-driven insurance. Network effects have the potential to create virtuous circles of innovation and improved customer service that will be increasingly difficult to compete against.

How incumbents are dealing with the digital challenge

Established players across all sectors have a range of options in dealing with the rise of nimbler, data-driven startups. They can develop their own in-house programs and teams to transform their business processes and build new products and services. Alternatively, they can acquire the expertise through corporate acquisition and expand their portfolios that way. These are and will continue to be sensible approaches for some companies, but digital transformation can take far longer than the market may allow and acquisitions often fail to deliver the synergies and benefits promised.

A third option is to partner with new entrants to draw on their expertise in niche areas and combine that with the assets which only a large, established firm can offer such as access to large datasets, financial resources and brand recognition. This is increasingly a trend in the financial markets and plays to the strengths of all parties. One thing is for sure, not doing anything is no longer a viable option.

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Copyright © 2019 IDG Communications, Inc.

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