Digital Insurance Agenda

Data-Driven Value Creation: Opportunities & Challenges

Written by Roger Peverelli and Reggy de Feniks - Founders The DIA Community on Mar 8, 2022

When talking data, new generation cross-selling might in some cases sound a bit outdated because it has been discussed for years. At the same time, there’s still massive potential there. Leveraging all that is available from data, can help insurers gain an uplift in conversion rates of 10 to 20 times. However, leveraging data also bring many challenges. In this editorial, Simon Kaesler, Partner at McKinsey & Company and Jonathan Larsen, Chief Innovation Officer of Ping An Group, share some knowledge about creating value from data without compromising individual data rights.


Understanding what data resources can do exactly and taking value from them is something companies often try to gain profit from, but in general do not maximize the full potential. Many of the underwriting models are still very basic, using basic regressions, not sophisticated machine learning models. In this regard, data-driven value creation has just passed the beginning of possibilities – but with a lot more in store.


How then, do you do that? For one: find low hanging fruit for data driven value creation also on the beaten track, using existing and external data. The way data analytics can be applied, is becoming easier. There are much more use cases readily available, which can be implemented very easily.


Simon Kaesler: “From our perspective, when we had insurance companies developed a use case, a few years ago, this was the multi-month project. Today, it’s basically a few weeks because a lot of the things are readily available in the market and the impact can be quite massive. But then there are lots of challenges regarding technology and data landscape.


The data in insurance is fragmented and the data quality is variable. So, in our projects, we spend probably 80 percent of the time to consolidate data, to enhance the quality, to connect data before we start analyzing, interpreting and optimizing. That’s not a good data culture. Data is collected in all parts of the insurance organization, but not connected. And often, it’s not even collected. So, you can get an insurance policy with many carriers without leaving your mobile phone number, without leaving your email address. That’s not possible in other industries anymore. I would say that in insurance, data culture is one of the topics that has lots of room for improvement.”


Other challenges in data-driven value creation lie in data security and data regulation. Many companies struggle with enhancing data without putting the customer’s data rights in jeopardy.


Jonathan Larsen: “Data sovereignty, data security but also the privacy of individuals data are of growing concern for Chinese regulators. I think there’s probably been a fair bit of misunderstanding internationally with respect to sort of the way data is used and shared in China. I’m very sure that if you go back six, seven, eight years, you could have characterized it as a pretty liberal environment. And that’s probably not because there weren’t guidelines and laws. It’s probably because those laws were either not understood on the one side and or not enforced on the other.


But in recent years, there’s no doubt that, certainly the big, listed companies that you would know about, obviously including companies like Ping An, take data security extremely serious. We certainly can’t take data from Ping An Bank and give it to Ping An Life or vice versa. We certainly can’t take Good Doctor data and give it to Ping An Health or vice versa. That’s totally illegal and unacceptable.


So, what we’ve been working on are models that very much the kind of thing that Google might do, which is to be able to take profile data and aggregate that anonymously using customer identifier keys. And then being able to then enrich the profile of a customer with any individual entity with a profile data that is non-specific relating to that customer.


If you do that, you’re not sharing specific details or compromising specific information with respect to what customers are doing. With this kind of model you’re able to be helpful to customers, able to anticipate needs, customize offerings and so forth without actually compromising individual data and data rights.”


In the Executive Education Course ‘Next Level Insurance Innovation in the Age of Data’, Simon Kaesler and Jonathan Larsen discuss other opportunities and challenges in the process of implementing innovate business strategies to make data their business’ game changer in insurance.

Interested in learning all do’s and don’ts in developing new business models? And to discuss these with Simon Kaesler and Jonathan Larsen directly? Then make sure to
apply as a participant. The course kicks off on April 26, 2022. Classes are online, 9 weeks, 3 hours per week, conveniently scheduled at the end of the workday; 2 hours on Tuesdays and 1 hour on Thursdays.

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