How Technology is Driving Big Data & the Insurance Industry

As Big Data gets bigger, we take a look at the challenges faced by the insurance industry and insurtechs collecting and turning information into insights.

Every day, the world seems to move a little faster as technological advances connect businesses and people more efficiently. For the most part, it goes on unnoticed. We barely register the fact that our broadband connections are now so swift that instant video streaming is an expectation, not a luxury. 

However, the speed at which data is being gathered these days and the methods through with it is being collected, are increasing in both efficiency and number. Currently, according to Gartner, there are approximately 25 billion IoT devices in operation globally. By 2025, the IoT will comprise of more than 64 billion. 

As 5G continues its worldwide roll-out and connectivity, as well as the speed and volume of data transfer grows, so will the amounts of data collected, and with it potentially, the issue of data gravity - a term given to the massive glut of information that is collected electronically by companies through the IoT, which is then stored, but not aggregated, and therefore, produces no useful insights. 

Insurtechs and data gravity management

According to a number of reports, data gravity in the insurance industry is predicted to double in volume annually by 2024. This presents all companies with the unique challenge of handling vast swathes of information that on one hand, can provide them with essential KYC insights, but at the same time, in the age of cybersecurity, become a legal liability. 

David Sexton, VP & Head of Insurance Practice at global technology solutions giant, Cognizant, says advances in data availability due to several criteria such as the explosion of smart cities, data analytics and modelling techniques, highlight the need for insurers and re-insurers to treat data as one of their organisation's most important assets. He explains,  “Like any other asset, insurers must protect their data with utmost care. Regulatory compliance requirements, such as GDPR, and data protection acts, form strict guidelines dictating the insurers to deal the data assets with the utmost care, under careful and authoritative data governance processes.”

The opportunities presented to insurtech by Big Data

But while the risk-reward ratio presents a distinct set of challenges, most experts believe it's weighted in favour of greater data collection.

Sean Russell, Senior Data Governance Consultant at DTSQUARED, sees this double-edged sword as a great opportunity, albeit weighted in responsibility. He says the race is on to be among the first to capitalise on the potential for insights into customers, markets, and products. However, he points out, “It also means there are new regulatory requirements to consider, especially in the ESG, Privacy, Security and Ethics spaces. Most importantly, it means that insurance businesses will need to see data as an asset and manage that data effectively.”

The change that insurers are facing in terms of managing these assets, should not be understated though, as more regulatory safeguards will need to be issued. 

Real-time data insights for insurtechs

Lorenz Graff, CEO, and co-founder of bsurance, says while insurers are used to the process of data collection, the future presents them with high-resolution data sources in real-time. 

"Of course, insurers have been collecting data and using it for years – but it has been limited. Take, for example, a standard consumer risk assessment and evaluation. Hereby, the onus is on the intuition and expertise of the underwriter, whereby the price and potential risk is informed by the most basic of data such as the policyholder’s age, address, occupation. 

"But this is changing – and fast. Combined with the latest advances in computing power, the processing and analysis of this data when combined with internal material offers invaluable insights needed to inform better decision making in product development, distribution, marketing, and sales.”

Graff cites customer profiling as a prime example of the way data can be used, even though real-life contact with the customer is minimal. "Through the rich intel provided by social media and telematics, insurers are able to build 360-degree views of consumers and use real-time monitoring to track their habits. This data can prove invaluable in learning more about the customer to enhance existing solutions and even identify cross-selling opportunities – say, where the same demographic of customer is likely to purchase life and household insurance in close proximity.”

Insurtechs must calculate risk versus reward data collection

The pitfalls of increased Big Data - especially at a time when privacy concerns are a primary issue, cannot be understated. Cybersecurity is a huge aspect of the risk/reward ratio, and as incidences have increased significantly since the advent of digital transformation and the pandemic, it looms large in the discussion.

Brian Mullins, CEO of Mind Foundry, describes it as a big threat. “Cyber-attacks and data breaches will continue and the fallout from these is likely to get worse as our digital footprints expand. But opting out will often be even more detrimental than opting in and falling prey to an attack.”

Mullins says the optimal approach involves an understanding that increased access to data comes with risk but these risks can be mitigated with a careful, principled approach that, “utilises the best techniques of machine learning including continuous meta-learning, differential privacy, robust data governance frameworks, and responsible system design.”

Jason Paau, Insurance Lead at Publicis Sapient, agrees. He believes there will be equal amounts of pros and cons to the increase in Big Data.

“It’s not black and white,” he says. “It will depend on how the industry establishes data governance and data management (governance and management will grow in complexity as data usage matures).  This will also be driven by individual carriers based on their own assessment of the opportunity and costs”

Paau says the risks will include stale data, in the form of  “black box” decisioning by AI/ML that affect people’s lives, combining dirty/untrustworthy data. But he also says the benefits will include the potential for a holistic and accurate view to add greater customer value (and therefore loyalty), rather than a  “one size fits all” with advanced data granularity in the form of personalised offers and products as well as, preventative cost-saving opportunities as IoT data on anything from truck maintenance to drone surveys, feedback vital information. 

He notes, “There is also significant upfront investment needed (technical debt) to move [companies] to cloud/digital transformation”

Is insurtech on the edge of maturation?

But how can companies effectively aggregate their data to maximum effect? Which technologies are proving most effective in terms of handling the data surge? And which technologies hold the key? 

Jerome Bugnet, Director, Solution Engineering of the hybrid integration platform, MuleSoft predicts APIs will be essential in enabling insurers to aggregate their data to maximum effect. As Big Data increases, he says, insurers will need the ability to integrate a growing number of data sources quickly and easily. This requires a high level of data agility that enables insurers to manage and access Big Data more effectively, so they can use it to build sophisticated experiences for customers. 

He explains, “Despite being rich in data, agility doesn’t come naturally to insurance providers due to their heavy reliance on sprawling legacy IT estates. Many still store their valuable customer data in disparate silos across the business. This makes it difficult to unlock the insights needed to power more personalised insurance products and better policyholder experiences.”

Bugnet says insurers use API-led connectivity, they can embrace a “composable enterprise strategy” that allows them to more easily draw data from any source to create a single view of their policyholders. This will put them in a far better position to maximise the value of Big Data for creating personalised experiences and building new partnerships.

The future of Big Data in Insurtech

Most experts agree that there will be many challenges to overcome and many more changes to take place in the next few years, as insurtech further establishes itself among incumbents, and the IoT and connectivity develop. Sexton concludes, “Big Data is likely to will expand in ways we can’t even imagine in the insurtech space, but as a start, the amount of data being collected and analysed will only grow. Areas of regulatory concern, such as ESG and ethics mean more data in these areas will need to be collected. 

He adds, “Meanwhile, smart devices and other technological advancements will mean more actuarial, claims, and trend data. Finally, environmental, and political factors will play an increasing role in how new products and offerings are developed and marketed. It’s an exciting time to learn more about data in the insurance industry!”


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