The Knowledge Expert View: Getting your head around the benefits of Big Data
Chris Varley, Zurich’s head of rating tools, talks about the importance of data and how insurers can help brokers make sense of it
Everyone working in insurance should care about data. Data is crucial for brokers in understanding and managing their customers’ risks while obtaining a fair price to cover them. And while brokers are at varying stages of Big Data evolution there is a much wider recognition of the value in data.
Harvesting data can require specialist skills but the good news is that brokers already have many of the key skills needed, specifically in respect of understanding their customers’ needs and identifying their problems that need solving. Brokers are also close enough to their customers to be able to recognise emerging market trends and have the ability to apply critical thinking to evaluate those emerging risks.
Blending traditional and non-traditional data
Insurance has traditionally relied on a relatively small number of risk factors. But there is much more to an underlying risk profile than what’s collected on a proposal form and reliance on claims data is insufficient to price risk accurately.
Increasingly, we are able to tap into new data insights that go beyond the traditional approach. For example, we can use everyday sources of publicly available information, including company financial records, reputation insight and other social media data, to help build fairer pricing.
The vital skill is in selecting which data to use and this goes back to the customer problem you’re trying to solve, what you don’t currently understand and how data might help. This might involve trying to understand the market and risks in emerging industries by using online and offline media to develop and price appropriate insurance products.
If brokers understand the activities, risks and exposures inherent in an industry – alongside the associated customer needs – this helps insurers to tailor products and pricing outside of traditional rating factors.
For example, two technology companies that might look the same on a proposal form can actually be quite different in practice. In the future we may be able to collect data to better understand their exposures; for example, how they manage their customer’s data, their social media policy, exposure to contractual breaches or their stewardship of Intellectual property.
By understanding the needs of individual customers through data insights, brokers can show their expertise when working with underwriters in these emerging industries, just as they do in more established sectors like manufacturing or construction.
This heightened awareness of data is an extension of the traditional broker-customer relationship; in essence, the broker developing an understanding of a customer’s business even before getting face-to-face with them.
Data and the pricing/product difference
The connection between data and pricing is clear: better quality risks cost less to insure and with greater insight we can identify the higher quality risks and provide a more appropriate price.
Within the broker community and our own organisation there has been a shift in attitude to data: collectively, we are more comfortable testing, learning from and validating data to harness its value and create increasingly bespoke products and services. This has meant greater collaboration between claims, marketing, research and insight and underwriting, all generating large amounts of useful data.
The shift in data use that we’re seeing also means supplementing the traditional focus on loss cost modelling with increased focus on predictive analytics to solve different business problems: understanding emerging risks in order to revise insurance coverage and alerting customers to other types of cover they may not know about. Having better data can also feed into a more customised claims experience and in better supporting niche segments and vulnerable customers.
In many ways, we are taking a lead from the analytics work being done in other industries where there has been huge investment in developing expertise and knowledge to understand what customers really want. In our industry though, the data-driven insights mean nothing without experienced professionals to analyse, test and validate the findings.
Being determined to gather a wealth of data – via both risk and non-risk analytics – doesn’t undermine Zurich’s principal purpose to serve customers and pay legitimate claims. In fact, having better data reinforces that purpose through having a better-informed grasp of customer risk that enables us to offer a more accurate and fairer price.
The customer culture and expectation around big data
In the past we have relied on the knowledge, experience and ‘gut feel’ of our brokers, underwriters, claims and risk professionals to drive success. As new data-driven insight approaches emerge we’re sometimes met with resistance to these ‘new ways’ of working as they can be perceived as a threat, but for me – nothing could be further from the truth.