How Analytics can transform the Insurance sector

Gavin Holme, Country Manager, Africa, Wipro Limited.

Rudraksh Bhawalkar, Practice Manager, Analytics, Africa, Wipro Limited.

In the coming years, the Insurance sector will be lit up with trailblazing new technologies that will radically transform the way insurance products are calculated, bundled and delivered to customers.

We’ll see the beginnings of a new form of “social contract” between Insurers and their customers: an exchange of customers’ personal data in return for cheaper, more tailored premiums, and more personalised services.

For example, an individual will agree to his driving behaviour and vehicle diagnostics being monitored via connected sensors. In return, he’s promised that safe driving behaviour will be rewarded with reduced premiums, and that emergency and maintenance crews will be automatically alerted in the event of an incident.

Or, management of an offshore oil rig will allow their Insurer to host connected IP cameras and temperature-reading sensors, and view online maintenance logs – in return for decreased premiums.

These are just two of the many examples of how an Insurer can increase the accuracy of its actuarial models – passing increasing levels of accountability to the customer, reducing the risk that it must bear, and ultimately providing more efficient and cheaper services to customers.

We can summarise the advantages of Analytics in the Insurance sector into these broad groupings:

• 360-degree customer perspectives… Insurers can combine structured transactional data (gathered during on-boarding and subsequent customer interactions and claims), with unstructured data from connected devices, social media scanning, and other channels. This creates a very complete view of customer requirements and enables them to match the right offerings with customer needs.
• Faster claims processing… Customers’ number one source of frustration is the slow processing and payment of claims. With an Analytics-focused approach, customers can be allocated to different risk profiles – and low-risk customers can have their claims fast-tracked. Claims from higher-risk customers, where the Insurer needs to conduct more thorough assessment, will still undergo a detailed assessment.
• Better propensity modelling… With a comprehensive understanding of the customer, it becomes easier to pinpoint their propensity for cross-sell and upsell opportunities. For example, from a seemingly flippant tweet about one’s frustrations with their current insurance service, a quick-thinking Insurer could swoop in with a targeted offer to that particular individual (knowing that they are ‘ripe’ for switching service providers).
• Fraud reduction… Fields like disability and death insurance must deal with the perennial issue of fraudulent claims. Imagine the scenario where – instead of employing private investigators to investigate claims – the Insurer can build machine learning tools that track public social media activity to find evidence of fraud, and repudiate claims.
• Market segmentation and profitability analysis… With detailed analytics, Insurers can work out which areas of their businesses is delivering the best results. They can channel resources and marketing efforts towards the most profitable customer segments or products. For example, one insurance company recognised that the customers of 65 years and older were making the least claims, and had the highest value of insured assets. They focused their business of capturing as much of this market as possible – increasing the overall profitability of their organisation.
• New services… With sharper customer insights, Insurers are able to play a ‘platform-based role’ and add a range of value-added services to its customers. For example, customers could agree to having data about their blood sugar levels and pulse strength automatically streamed to their Insurer via wearable or digestible technology. The Insurer would look for any data anomalies, raise triggers (when sugar levels reach a threshold), and respond with medical services or calls to customers. If a pulse is detected to be weakening, emergency helicopters can be automatically dispatched to the customer’s geo-located destination, for instance.

One thing that the social media revolution has shown is that customers are generally willing to give up aspects of their privacy, in return for value.

The new social contract signed between Insurers and customers involves a similar social dynamic: customers who are willing to give up some level of privacy, and accept greater accountability, will be rewarded with personalised, cheaper, and more value-adding Insurance services.