Identification of the insured entity or prospect is the first step towards checking for frauds, making customer identification a critical process for insurers. It helps them extract more accurate insights, to properly underwrite risks, to efficiently manage claims, and to cross-sell or up-sell.
It also helps reduce frauds originating from intentional personification or identity theft, which would otherwise severely dent the insurer’s profitability and claims ratio.
Insurance challenges with data linking and identification
Insurers have a difficult task, when it comes to cross-matching of data and identification. Gathering a customer’s identification data, usually ends with the collection of ID and address documents. However, ID documents are only the first step to building robust data sets. It is essential that these documents (and other public records, or other data related to customer identification) are converted into digital form completely, and without resorting to short-cuts.
Furthermore, digital records of ID must be validated against the original source in order to establish authenticity. Given that everything needs to be mobile and quick, there is increased pressure to do all of this quickly with minimal customer effort.
A customer may seek to buy more than one insurance policy and they may have stacked more than one policy, including one or more from an insurer being approached for cover. Therefore to check on suspicious activity and to take an informed decision on whether to underwrite or reject the risk, the insurer must have the requisite insight on the customer. It’s a careful balance between rejecting a risk (with potential revenue loss), and the loss from underwriting high risks without due diligence.
Challenges for understanding the customer journey across insurance brands or segments
At LexisNexis Risk Solutions we typically hear comments from insurance providers, indicating the difficulties they see in reviewing or analysing a customer’s policy history, even in cases where the customer has bought a policy before. This is because several data points of the policyholder would have changed over a period of time. So, unless there is clear identification, it will be very difficult to resolve all the policies belonging to a person.
Multiple identities of the same customer also pose various challenges, such as:
- The true risk, once identified, may not being worth underwriting
- The actual risk may not get priced appropriately
- Customers with lower risks might not get a better deal, and they might be lost to a competitor
- The identification of fraudulent claims from false positives becomes difficult.
As the home insurance and commercial property/SME insurance industries in the UK move toward contributory database platforms or pooling industry data, customer identification will be key to drawing insights from industry data. Lack of proper identification of customers in the database, will contradict the purpose of a contributory data platform.
Additionally, it is important to know exactly how many customers you have. Accurate data across the whole sector will ensure that multiple policies bought by an individual are clubbed together. Insurers will then know how many customers they individually have, and the total number of people covered by all of them. The exact figure available today is only the number of policies issued.
Ways to improve customer identification and achieve a 360-degree view
The following are a few ways to improve customer identification:
- All essential data must be collected: In the battle of compromise between data entry costs and subsequent data quality, it behoves insurers to focus on data quality, because the benefits of good data quality are reaped not just at the current interaction, but throughout the life of the customer. So all essential information related to identification documents should be collected and entered into the system. For example, it would be useless if the driving licence number is entered, but nowhere is there a data cell to mention that this data point is the driving licence.
- Collect accurate data: Insurers should upgrade their systems to validate the accuracy of the data being entered. Accurate data, and data verified from cross-industry sources, is necessary for identification match rates to be high.
- Digitise the data collected: The digitisation of all data, including making external data ready for the insurance workflow, should be considered as important as attracting more customers, and more business from existing customers. If this step towards data accuracy is taken, then data analytics for the rest of the insurance continuum can become highly effective.
- Check the brokers and intermediaries: Another issue is that insurance intermediaries can sometimes be more concerned about their own income, and less about the insurers’ need for complete identification data. This can lead to problems in how they collect and pass on data to insurers. This is another factor to support automation in the collection of ID data, helping to reduce errors in manual data entry.
- Use all data available to identify a customer: Insurers do duplicate checks on their database but the data used to carry out these checks is often deficient, hindering the reliability of such checks. Even when an insurer does not have all information, it is possible to enrich from a variety of sources and then perform accuracy checks. When no direct source is available, accuracy can be determined based on quality scores that use frequency and distribution of reporting on contributory databases.
LexisNexis Risk Solutions helps insurers collect information to serve the intended purpose. The identity information collected by insurers and the documents collected as ID proof and address proof are recorded in the data clearly. We have high quality information and time-tested data quality algorithms that can help you solve this unique problem.
LexisNexis Risk Solutions are trusted custodians of data for insurers, brokers, broker platforms and software houses who ask us to help them achieve their strategic aims.
Follow the link to the LexisNexis Risk Solutions website to find out more about how we support insurers.