We examine the impact of Big Data Analytics on the insurance sector, and look at five ways industry leaders are harnessing data to create competitive advantage.
There’s a revolution sweeping the global insurance industry. A digital transformation of epoch-shattering proportions is rendering old methodologies obsolete, and redrawing the playing field for some of the world’s most venerable corporations. That transformation is being driven by Big Data Analytics. Here we examine the top five ways that industry leaders are harnessing the power of data to generate value and create competitive advantage.
This is the age of data; companies around the world have access today to more points of information than at any other time in human history. 90% of all the data in the world was created in the last two years. Every day, the planet creates more than 2.5 quintillion bytes of information.
“Every interaction with your computer or phone creates data. Every interaction on social media creates data. Every time you walk down the street with a phone in your pocket, it’s tracking your location through GPS sensors – more data. Every time you buy something with your contactless debit card? Data. Every time you read an article online? Data. Every time you stream a song, movie or podcast? Data, data, data,” Forbes writer and business analyst Bernard Marr wrote in a recent article.
As social media usage, cell phone ownership and the ascendant ubiquity of Internet of Things (IoT) devices continue to grow, this trend is showing no signs of slowing down. As you read this, you’re creating more data.
Where does it all go?
Every uploaded picture, downloaded PDF, streamed video, or packet of location-tracking information goes somewhere. Usually, it’s sold with our (somewhat) informed consent to companies that use it to advertise more effectively. Ever had a passing thought about getting a dehumidifier for the house and then seen nothing but ads for the Pro Breeze Electric Mini for the next day? That’s the power of Big Data.
Big Bata is collected and analysed - increasingly by artificial intelligence (AI) and machine learning (ML) powered technology - in order to help companies better understand their customers, their internal workings and the world around them. Disruptive companies with a taste for innovation have been using Big Data analytics for years to develop and maintain a competitive edge. From the hospitality to manufacturing sectors, the companies that are going to survive - and thrive - in the Fourth Industrial Revolution are data-driven ones.
Fortune predicts that, by 2026, the global Big Data analytics market will be worth in excess of $1trn. Every company in every industry around the world needs to be a part of the Big Data revolution, or be left behind. Nowhere is this more true than in the insurance industry.
“Insurtech is having a transformative impact upon the global insurance market - the role of data is absolutely central to the entire project,” observes a recent report by global professional services and accounting conglomerate KPMG. “Data is not simply the facilitator for better underwriting and keener pricing, but is the very DNA of the 21st-century connected organisation.”
The insurance industry is no stranger to data. In fact, it’s probably been drawing insights from large data sets for longer than any other sector. However, this may end up being more of a hindrance than a help when it comes to the next step of its evolution into an increasingly digital age.
Traditionally, insurers have relied on mathematically-skilled actuaries crunching complex sets of numbers to understand risk and write policies accordingly. “Over the past 15 years, however, revolutionary advances in computing technology and the explosion of new digital data sources have expanded and reinvented the core disciplines of insurers,” asserts global consultancy McKinsey’s report Unleashing the Value of Advanced Analytics in Insurance. “Today’s advanced analytics in insurance push far beyond the boundaries of traditional actuarial science.”
Big Data is completely revolutionising core aspects of the insurance sector. Let’s take a look at the five main areas of insurance that Big Data analytics is transforming:
Pricing and Underwriting
The ability to accurately assess risk and price policies accordingly has been the central point of value creation for the insurance industry for centuries. By giving insurers access to larger data sets, and more detailed information about individual customers, Big Data is allowing these companies access to more granular datasets, which enable them to offer policies that more closely reflect the risk posed by an individual, rather than the demographic box they belong to.
However, this doesn’t mean that these older analytical strategies are being discarded. According to a report by the European Insurance and Occupational Pensions Authority (EIOPA), “traditional data sources such as demographic data or exposure data are increasingly combined (not replaced) with new sources like online media data or telematics data, providing greater granularity and frequency of information about consumer’s characteristics, behaviour and lifestyles.” The result is a new generation of companies that are harnessing the extensive experience of their industries in combination with the added power and insight provided by Big Data collection and analysis.
Health and wellbeing
IoT-powered wearables are having a huge impact on the personal health insurance space. In the same way that telematic monitors in vehicles can track customer behaviour to reward safe driving habits, devices like the Fitbit and Apple Watch’s Health App can track and promote healthy behaviour, leading to lower premiums. The data gathered in this individual-focused manner allows insurance plans to be customised to the behaviour and health on a person-by-person basis.
Companies like AliveCor offer devices like the KardiaMobile, a personal EKG monitor that allows cardiovascular health data to be shared remotely with health professionals and insurers. UK-based insurer Vitality offers premium discounts based on the activity points that can be earned via use of Apple watches and demonstrated activity levels.
Settlements and claims
Traditionally, the claims process is a long and arduous one, as adjusters assess the claim and determine liability to see whether a payout is justified. Today, by using mass data gathering to segment and analyse claims quicker using AI. In some cases, companies have been able to fully automate the claims process.
Policy Developing and Tailored Insurance
The increased personalisation of insurance has been touched on several times already above. The trend itself is one that isn’t confined to insurance, as companies around the world use increasingly detailed datasets to tailor the experiences of their customers. Remember the Pro Breeze Electric Mini?
According to a recent report by the The Organisation for Economic Co-operation and Development, “Insurance sets prices by groups of people who have similar risk profiles, whether, for example, by gender or age for auto insurance, which is called risk classification. Big Data provides new sources of information for understanding policyholders, fine-tuning the risk classification.”
By further segmenting these risk groups, insurers are able to use Big Data to offer policies tailored to increasingly specific situations and clients who may not have previously had access to affordable coverage. Jean-Francois Gasc, a Managing Director at Accenture wrote in a report last year that, insurance customers are increasingly “seeking tailored, customised offers from their insurers.”
The new face of customer experience
Another trend that has been sweeping across multiple industries is the increased use of AI and ML-powered Big Data analytics to deliver more personalised and effective customer service experiences.
As mentioned earlier, Lemonade uses a proprietary AI called Jim to manage and oversee claims. Computers are reaching the point where they can be safely expected to handle larger and larger decision-making roles.
AI and ML can even be used to build more detailed profiles of customers by tapping into external datasets to find for similarities in internal data to produce a holistic customer profile. In call centres - often the first point of contact between the insurer and customer - AI can be used to analyse call volume, reason and the types of customers that are most likely to call at certain times of day. Understanding these vast datasets can be key to reducing wait times and ensuring that the most appropriately-qualified customer service representatives are available at the most appropriate time.
Data-driven AI and ML-powered chatbots are even replacing the human point of contact entirely in some companies.
Future-proofing the insurance industry
Change is a constant phenomenon. The global digital transformation of the insurance sector isn’t going to slow down any time soon. As new challengers like Lemonade, Surround and Flock (which is using Big Data analytics to enter into the relatively new market of drone insurance) emerge, legacy insurers need to adapt, adopt and evolve quickly, or be priced out of the marketplace.