The insurance single customer view.. What actually is it ?
In the last week I've had about 5 interesting conversations with insurers about their "single customer view" strategy. It's also been interesting that I got completely different interpretations of what that strategy actually should be.
- Development of an accurate product density view across unique individuals and companies across all my product lines and regions to understand exactly what products my customer are buying to assess bundling and cross-sell
- An ability to recognise, in real-time, existing customers through direct quoting processes such as on websites or price comparison websites to provide a tailored discount based on existing "length of service"
- The creation of a "customer reference asset" (exclusively from external and third-party industry data) to give me a 360-degree view of my customer across data bureaus, public records ++.
- An analytical "customer master" which contains all my historic and operational enterprise data assets, connected together to deliver a single place place to perform enterprise analytics (such as ratings, loss propensity & fraud)
- A deep understanding of a new applicants "connected entities" (locations, vessels, vehicles, ownership structures, associated corporations, directors and officers++) in order to perform deeper due-diligence of that customer for screening, credit risk, ESG & corruption.
In reality, our belief is that there is no "single view" of customer. Because in each of these cases you would not only want to use different data but also different tolerances by which you connect the data (fuzziness). You also probably want to segregate the views based on permissions within your internal staff (especially for sensitive data).
It is also our belief that actually this also shouldn't be limited to a customer view as it can translate to any party (claimant, supplier/provider, witness, employee, agent) or even entity (locations/properties, vehicles or vessels, bank accounts or devices, contact details+++).
That is the beauty of a dynamic holistic view of entity. It can be deployed enterprise-wide, across any data set and can be delivered to serve dynamic views for different teams, business units and value-chain applications.
To learn more about this capability see here as well as a discussion on Linkedin here. Also see the comments for a 4 part blog series on this topic.
We would love to hear more about your experiences of this and where you see the value in your "single customer/party view"??...
@Areefih @Alan_Haskins @Shyam_Bhatt @Arnaud @Marcus_Hayes @Chris Sanders @Delphine_Masquelier @Clark @Patricia Arenas @Molly @Holly
Comments
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I think people miss use the term entity resolution. We have all heard insurers wanting to achieve a customer “golden record” they can have confidence they have created a record of an individual that all future decisions can be based. But insurance companies lack the ability to truly connect siloed data across systems and platforms that were never meant to be connected. And if they’re able to create a record that resembles a golden rerecord it’s a snapshot in time of the individual you are trying to quote a price, underwrite a policy, or base a claims-decision on.
True entity resolution provides confidence that you built a 360-degree view of your customer, applicant, insured, claimants, or third parties, that can be regenerated in real-time as additional data is dynamically brought into the system. Entity resolution is not a one and done customer view it’s an ever-changing target that sometimes does not want to be identified.
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"Entity resolution is not a one and done customer view it’s an ever-changing target that sometimes does not want to be identified". Love it.
As insurance digital interactions become more common (through apps, chatbots, IOT & sensors) it is more critical than ever that the customer/party view continues to update and can be re-built at time of request to execute next best actions.
As insurers expand the use of digital channels, they must be able to do this with millisecond response times across millions/billions of data points to inform a multi-layered analytics approach to things like dynamic ratings, next best actions, engagement scoring and fraud detection.
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See a great 4 part blog exploring how you rethink the customer master data strategy here https://community.quantexa.com/kb/articles/92-rethinking-mdm-and-our-approach-to-it-part-1-4-intro
Thanks @Issam_Hijazi for the content.
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