The Challenge (and Opportunity) of Speeding Up Digital For Life Insurers
August 30, 2016 by Anne-Frances Hutchinson
You are not alone in your data challenges. One out of every two companies confess to incredible difficulty gaining actionable intelligence from their data.
In Insurance 2020: forcing the pace – the fast way to becoming a digital front-runner, PwC UK analysts suggest using a combination of legacy processes with market-ready solutions “to compete on equal terms with the mobile companies, Internet providers and other new entrants looking to make inroads into the market. In parallel, they can integrate new operations with existing business platforms and make sure that overall capabilities are steadily updated.”
The authors stress that the workforce must be capable of taking advantage of social media and big data decision-making to become more agile and customer-centric. “In turn, long and sweeping business planning cycles would give way to a faster changing and data-led iterative approach to meeting customer demand.”
To speed up digitalization, PwC recommends moving from developing products through “the separate siloes of design, marketing and distribution (looking inside-out) to discerning the needs and expectations of customers and working back to create the right solutions (looking outside-in).”
With fierce startup competition coming from the tech, mobile and Internet sectors, life insurers must match the scale, data access and high-speed analytics of these fast movers. “Some life insurance companies now use more than 50 data sources to create a truly insightful ‘360-degree’ profile of their customers. This kind of analysis allows them to create products and customer experiences around their needs and preferences,” they write.
Here comes the caution flag: “(A) key challenge is how to deal with such a proliferation of data, the bulk of which is irrelevant ‘noise’. Most organisations are looking at how to increase their capacity to mine and analyse, but this can leave them drowning in data and make it difficult to extract genuine insights.”
A recent PwC Digital IQ survey shows that “while nearly 70% of companies are using analytics in strategy, product development and marketing, more than half believe that moving from data to insight is proving to be a major challenge.”
Swiss Re further supports the need for quality data in their report, Data Analytics in life insurance: lessons from predictive underwriting. “There are many outcomes life insurers may be seeking to achieve with their data. These include: reducing the underwriting process for healthy customers; improving retentions; increasing responses to marketing activities; or differentiating on price between customer groups…
“There have been some far-fetched promises about what big data can achieve; but the effectiveness of data is frequently constrained. Swiss Re has invariably found that the strongest health predictor models are those that are built from scratch on a bespoke basis. By definition this means that past data is needed of sufficient quantity and quality – and this is not always available.”
The report’s authors add, “(S)trikingly, we have observed vast differences in the quantity and the quality of data held by our clients, even by banks.”
The opportunity then, is masterfully leveraging the competitive advantage of your proprietary legacy data.
Knowing what’s coming is great, but for life insurers, it’s time to start speeding up. Especially when it comes to making sure legacy data is in the right format; and it is clean, de-duped, normalized and actionable.
Captricity’s pioneering data solutions lead the field in accuracy, convenience and turn-around times. That’s why 50 percent of the top insurers in the U.S. trust us for unparalleled data capture, transformation, and advice.
To dive deeper and see how some of the best in the industry utilize Captricity, head on over to our life insurance offerings page.