Monetize the customer data you didn’t even know you had
Apr 15, 2022 by Krzysztof (Chris) Daniel and Jeremy Owenson
Apr 15, 2022 by Krzysztof (Chris) Daniel and Jeremy Owenson
Acquiring, managing and using data is central to the insurance business, because risk and customer models drive everything from evaluating market needs and calculating risk, to detecting fraudulent claims.
For decades, insurance companies relied on paper-based forms of data management; some still do. But most of today’s ultra-competitive businesses can’t afford to wait for lengthy, manual processes to prepare and incorporate information.
Their challenge is to move from plodding paper or manually-prepped data to large, quick-moving datasets that generate insights and increase efficiency.
For instance, paper-based manual processing will be able to state where your customers holidayed last year (e.g., a ski resort). But a digital approach using data-driven insights can tell you where they are right now (on a ski slope), what they’re going to do (ski) and a host of other bankable observations. This more profitable approach opens the door to advice (“you don’t have the necessary skills to ski this route”) and just-in-time insurance. Some customer profiling and insurance products require near-real-time stream processing.
To assess your ability to handle data (and adapt to change) you’ll need to ask yourself some basic questions:
Which of the components do you need to acquire or upgrade, to unlock potential in the data?
Although modeling is a nuanced discipline, the Kuhns and Johnson practical definition of predictive modeling — the process of developing a mathematical tool or model that generates an accurate prediction — is as good as any.
Modern data and advanced analytics involve increasingly complex algorithms and methodologies. This intensifies the need for strong validation and model governance, as well as new actuarial tools like predictive modeling, together with a full set of insurance-related modeling principles.
Actuaries will need to adopt a digital core approach, incorporating risk and customer modeling into everyday actuarial practice. And, because data engineering and predictive analytics are continually evolving, best practices will be improved as a matter of course. So, it’s imperative that all concerned keep up with the latest developments.
When modeling risk, insurers need to be able to answer the following questions quickly:
From a customer perspective, insurers need to ask themselves questions like:
Once you’ve answered the questions, you can begin to plan your journey. All highlighted paths to the future share a first step. The map below shows that whatever your goal is, the foundational work should happen around components grouped in the bottom right-hand corner.
Look at the map and ask yourself, “which components should I upgrade first to help my organization now, and which will be of critical value in the future?”
Data is a fundamental asset for insurers, yet it can still be viewed as a component rather than the core of an insurance proposition. Our recommendation is that the key data components, data acquisition, storage (platform) and analytics (price/risk analytics) are the foundation, and need to be reassessed in the broadest terms of product and proposition development.
This is the third of three blogs looking at the purpose and value of domain-related data to insurers. Several industry experts shared their thoughts, drawing on market experience, tech knowledge and current customer base to draw their conclusions. If you missed the first two, you can read the first blog: Get more business value from your insurance data deluge and the second blog: Calculate insurance risk more precisely and turbocharge your digital customer experience.
DXC is the leading provider of core insurance technology globally, with over 1,900 insurance customers serviced by over 18,500 professionals.
Luxoft, DXC’s Analytics and Engineering business, is the preferred partner for banks undertaking strategic transformation, and is providing fresh insight into insurance sector analytics. To learn more, contact: financialservices@luxoft.com
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