He goes on to explain that customers feel like they need to lie in order to get what they’re owed, telling white lies to the insurer: “I park my car in a secure garage overnight” rather than “my car has never been in the garage because it’s full of stuff”. Masking the real story because they’re worried they won’t be covered. This negative relationship perspective also impacts the insurer themselves, having to wade through
What if the answer to this untrusting relationship was Geospatial data? What if Geo data could make the insurance playing field more transparent, quicker and customer-centric?
For example, GPS Telematics data found in black boxes reduces any possibility of fabrication of where the car was parked, because the insurer knows the exact location of the vehicle at all times. This allows for much greater accuracy in terms of pricing and risk reduction. This also gives the customer peace of mind knowing they don’t have to prove the car was in the garage because the insurer knows this already. The data acts as a neutral fact, benefiting both customer and Insurer.
Geospatial data also opens up doors to new possibilities of in-real-time prevention of risk; when vehicle theft is increasing in a neighbourhood, insurers are able to notify their customers to be extra vigilant with their vehicles.
Without wanting to sound too utopic, there is an awareness that all of this comes at a cost. The most accurate geospatial data can be very, very expensive. However, untruthful policies and customer dissatisfaction are also a great cost to the insurer, so an ROI calculus must be done.
As well as transparency, Geospatial data allows for the possibility of reducing the application process, creating a quicker route Some insurers have begun to use geo data to pre-populate fields for property insurance. Instead of the customer filling out extended forms answering questions like: “Is there a Neighbourhood Watch near you? Has your property shown signs of heave, landslip or subsidence? When was your home built?” – the answers have been prefilled using address and postcode layered data. As well as being transparent with no room for fibs, it means what once took the customer a substantial amount of time, researching elements that they may not have known off the cuff, is now significantly reduced. This
Within the wider context where the age of automation and digitalisation means “Over half of motor insurance (52%), and a fifth of property insurance (24%) is purchased directly by consumers” (ABI, 2015). The customer needs to be the centre of the thought from purchasing through to the claiming process.
It is understood that there are benefits across the board for this utilisation of geodata. With a better understanding of the location as well as the external factors affecting the likelihood of an incident, the underwriting process can be far more precise – allowing for cheaper quotes and posing less risk to the company - and in turn, more profitable For those working within Insurance it means a dramatic decrease in operational processes, such as follow-up calls. For the Customer, an experience that is easy, smooth and reliable – which will aid customer retention, another big industry struggle.
Although it should be noted, this process is not a risk-free task. Data protection, data quality and public trust are all of pivotal importance. However, these challenges are seen as worthwhile difficulties, as it’s widely accepted at both the strategic and operational level, that those who do not adopt a valued, smooth and customer-centric process, will be left miles behind.
