By James Burton, Senior Director of Product Management, LexisNexis Risk Solutions UK &I
Ironically, however, this activity brings reputational risks by sheer virtue of the fact that it often brings a fresh set of customer data to assimilate and integrate within the business.
The headache of data integration
Integrating data for consistent use across the business is far from easy. Consumer data can end up being stored in multiple silos where it risks becoming outdated, incorrect and inconsistent. It means individuals can appear multiple times across disparate customer databases within the same insurance group with no link being made between the records. To compound the challenge, the customer might be listed at different addresses or even have different representations of their name due to life events or simply because of input errors.
This makes it difficult to know with confidence that Mr J. Jones who has applied for motor insurance today, is the same John J. Jones who had a home insurance policy last year and is the same Jon Jones that had a claim for a commercial van policy three years ago.
Aside from the potential lack of clarity this also creates for poor customer service, duplicate or outdated consumer information can lead inaccurate pricing, the risk of fraud, wasted marketing budgets, lost cross-sell and upsell opportunities and unnecessary data storage costs. This can all have a detrimental impact on business profits and growth.
Linking and matching disparate customer data
Linking and matching customer data to create a single customer view can feel like an impossible task but the data analytics skills and technology now exist to solve this problem.
Patented linking and clustering methods can now help insurance providers to link all their data assets together. This means one ‘golden record’ can be created, for one individual, giving insurance providers a consolidated, view based on every contact or policy they have had with that person.
This one single record then creates the basis for all future dealings with that customer, allowing accurate data enrichment and helps build up the picture of their risk as more data is accumulated.
It’s a process of joining the dots – finding common threads between records to match up disparate data pulling on a wide range of external data sets including public records and insurance policy history data gathered from across the market. Records with commonalities are linked together and are then assigned the same unique identifier.
By pulling together data from multiple touch points – quotes, renewals, claims and marketing, insurance providers can build a comprehensive and accurate representation of a customer’s identity, at whatever point they are in their dealings with the brand – customer, claimant, applicant or prospect. It also means they have a consistent methodology for standardisation and matching of customer data across multiple databases.
Marketing, customer service, pricing, underwriting, portfolio management and claims can all benefit. By consolidating details about a policyholder, insurance providers can see all points of a relationship with that person and provide more relevant and customised products and services.
A recent White Paper by ResponseTap(ii) with input from LexisNexis Risk Solutions underlines the value of this insight when it comes to customer service and ensuring customers are not having to repeat details about themselves unnecessarily. When people were asked why they chose not to buy insurance over the phone in the last 12 months, 42% said: “I don’t like going through the automated IVR system (e.g. press 1 for motor, press 2 for home)” 14% said: “I thought it would be more expensive.” A further 49% said: “I don’t like having to repeat all my details again over the phone.”
In the same survey, when consumers were asked whether they would pay more to speak to an insurance specialist on the phone, 40% of respondents said they would, if the experience was as quick and easy as buying online.
A similar sentiment was expressed in a recent PwC report “The Future of CX”(iii), which highlights an 18% gap between customer experience and expectation. The study found that people buying car insurance would be prepared to pay a 7% premium increase in return for good customer service.
Clearly, access to the full picture of a customer or prospect can help insurance providers understand the lifetime value of the customer, supports more targeted and efficient direct marketing programmes, as well as accurate pricing based on an accurate understanding of the overall risk on the individual and their assets at point of quote.