The future of insurance is rapidly emerging, and it’s most certainly digital. With this comes a new age of data, enabling insurers to see a bigger picture and gain a faster and deeper understanding of risk exposure. Here, Lorenz Graff, CEO of bsurance, explores big data analytics and the opportunity it provides insurers to meaningfully advance their future ambitions.
In a world accustomed to personalised, on-demand services like Netflix and Amazon Prime, the insurance must move with the times. It must become faster, cheaper and more relevant. No longer can insurers sell standard, commoditized indemnification products through a network of agents or serve customers with tiresome application forms and lengthy policies
This will be seen in the transition towards embedded, digital insurance solutions as a way for businesses to connect customers to insurance products that anticipate and address their individual needs, inspire demand, are simple to purchase and flexible to use.
But it won’t be an easy process, and will require a newfound ability to adapt quickly to changing customer requirements, emerging trends, climate changes, world events and the like – with data at the fore.
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 it is changing. Thanks to the digital economy, today’s insurers have access to high resolution external data sources – in real time. 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.
In relation to customer profiling, 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. With minimised real-life contact, this data can prove invaluable in identifying opportunities to enhance existing solutions and cross-selling opportunities – say, a specific demographic where the customer is likely to purchase life and household insurance in close proximity.
Analytic tools can also help insurers to determine the highest-value clients and high-potential leads where much of the team focus should be spent. In this way they can work smarter not harder in order to achieve the highest return while moving away from the churn.
Importantly too, a data-driven approach can even influence behaviour and compel customers to make better decisions to alleviate risk. This is seen in the auto world where telematics used to monitor driving habits in real-time, enabling insurers to accurately create tailored, bespoke policies based on their usage, driving behaviour and likelihood of risk.
It can even redesign products too. This is seen in the rise of digital parametric insurance – whereby products are based on the probability of a predefined event happening – based on rich data intel – instead of indemnifying actual loss incurred. In areas prone to natural catastrophes this is breaking the mould by enabling greater transparency and quicker pay-outs so that people are able to recover from a situation quicker than ever before.
A good example is the Climate Corporation which is revolutionising the crop insurance market. Here, data and analytics on weather patterns, soil characteristics and the like is used to inform a new age of risk-assessment designed to better protect farmers from losses resulting from an ever-unpredictable climate.
But it is important to remember that not all data is the same and while there are many benefits to be had by the new age of data, the sheer volume can pose a hazard in terms of the inability to manage it correctly and the potential for analysis paralysis.
Going forward much more attention should be placed into making sense of the immense amount of public and private data insurers have access to in order to effectively sort from ‘the good, the bad and the uncertain’.
Besides increased automated data processing and analytics, in the near future this will be achieved through inhouse data analytic teams focused solely on navigating the data jungle, picking and identifying the relevant information for better decision-making.
Technology, a digital customer, and changing market dynamics continue to challenge the traditional insurance model and drive the case for digitalisation. Big data and our increasing ability to analyse it has a key role to play in providing the actionable business intelligence needed to make this age-defining transition a smooth one.
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