It is no secret data is now the most valuable resource in this century. Hail as the "new oil", it has become the foremost game-changer for the insurance industry in recent times, and insurers around the world, including Mr Jeremy Lian, Senior Vice President of Technical Services at MSIG Insurance (Singapore), are fast realising that tapping into troves of data can uncover new ways of reinventing the economics of insurance.
Data sets range from internal and proprietary data such as claimant history and coverage, to diverse external data sources such as response to online advertisements, social media sentiments, sensor data and demographic information. Owing to the use of telematics and IoT-enabled tracking devices, insurers can now gather more real time data regarding their customers’ behavioural patterns and preferences. As such, a massive opportunity exists for insurers to harness valuable data assets that can offer critical insights to drive business impact.
With so many ways to utilise big data, insurers need to discern where they can best use it to drive true business value, and they are taking note. In fact, 84% of the insurance sector participants surveyed in a PwC’s 2017 Global FinTech Report said they would invest in data analytics within the next 12 months.
Combined with the use of artificial intelligence, insurers are growing their analytic capabilities in a bid to draw further insights that could enhance their customers’ user experience as well as their own distribution, risk selection, pricing and claims management.
Customers stand to benefit from greater market efficiencies
The real value in collecting, harnessing and utilizing customer data is not merely for the benefit of optimizing processes for the insurer. Having a firm grasp of customer behaviour allows companies to leverage on behavioural economics to eliminate market inefficiencies resulting from information asymmetry between the insurer and its customers.
Not unlike other industries, the market fundamentals supporting the insurance sector are essentially demand and supply. Today, digital technologies are not only optimising and simplifying the customer journey but are also opening up opportunities for insurers to acquire an in-depth understanding of their customers. Using data collected from various interactions with the customers, insurers will be able to more accurately predict and address customers’ areas of needs and demands, and proactively look into product development to address emerging needs.
With greater market efficiency, insurers can create more affordable coverage for customers. Usage-based insurance (UBI) is one such example that utilises smart data technology to reinvent traditional insurance model.
Under the UBI pricing model, customers have the opportunity to adjust their premiums and terms, and are therefore incentivised to moderate their behaviour to reduce risk during the coverage period. The real-time feedback the customers receive from their self-tracking devices can also be a source for reinforcing or catalysing risk-minimising behaviour.
Take the automotive sector, real-time data collected from the telematics devices installed to the customers’ vehicles can shed light on their mileage, the time of the day they are driving, traffic conditions as well as driving behaviour such as where they are braking too hard or over-accelerating. These data allow insurers to better determine the individual’s risk, refine their policy pricing mechanism and underwrite policies at lower cost. Furthermore, the sharing of data from real-time tracking devices will also speed up the validation and processing of claims. In the same vein, customers can benefit from an improved experience through the connected services provided by the telematics device such as location of vehicle in a theft situation.
The ultimate beneficiaries from the utilisation of big data ought to be the customers themselves, who will directly benefit from the sharing of their data with their insurer. As opposed to relying on the pooling of risk with other customers, they will obtain greater control over their policy plans through data-driven usage models.
Sound data governance
Often, the discussion on data analysis leads to where the data should be hosted. In Singapore, the introduction of guidelines around cloud computing by the Monetary Authority of Singapore has led to insurers considering cloud hosting as an alternative to traditional storage options.
However, collecting and analysing large real time data sets require a complex and robust infrastructure, and setting one up comes with a unique set of challenges especially for the highly-regulated financial sector.
To govern the collection, use, disclosure and care of personal data in Singapore, the Government has set out a regulatory framework by establishing the Personal Data Protection Act. Financial institutions dealing with large amounts of personal information bear the added responsibility to ensure data protection and privacy for their customers, without which their customers would be resistant to sharing their data.
To encourage wider adoption of IoT-devices, insurers need to demonstrate greater sensitivity and transparency in how they use their customers’ data.
For one, establishing a good data governance structure will set some level of consistency in the way data is collected, managed and secured across the organisation. The ability to uphold these standards will build on customers’ trust in insurers.
Ultimately, insurers need to lay the groundwork in order to fully reap the rewards of big data whether it is investing in a digital infrastructure, analytics capabilities or displaying greater transparency in how customer data are being utilised.
The promise of the big data revolution has captured the imagination of many and is driving change across all sectors. As insurers engage with the wider digital ecosystem to cater to their connected customers, they will need to continually harvest opportunities made available through the big data revolution. Insurers cannot afford to wait out if they want to get ahead of the curve. They need to move quickly and the evidence is compelling.