March 28, 2017
10 Trends at Heart of Insurtech Revolution
by Sam Evans
For one, external data and contextual information will become more important than historical internal data for predicting risk and for pricing.
As the insurance industry enters a period of profound change, we at Eos use a concept called the 20/20 dynamic to illustrate the point:
On a conservative basis, we believe most insurers risk losing at least 20% of their business to disruption. On the flip side, for those that embrace innovation there is an opportunity to grow their business by 20%.
Our goal is to ensure our strategic investors are on the right side of this equation.
Insurtech represents a unique opportunity for insurers to evolve their business model. Insurtech is not necessarily about disruption, but more an opportunity to take advantage of technology and data to create innovative solutions, reduce costs and capture greater value for customers, brokers and intermediaries, underwriters and service providers.
At one level, active participation is required just to meet the basic requirements of playing in the new market. For those committed to a strategic approach, insurtech can help drive true competitive differentiation, while enabling measured bets for the future.
See also: Insurtech: Unstoppable Momentum
Underpinning this transformation are 10 key trends that we have identified and believe will be at the heart of the insurtech evolution:
- Insurance, as we have it known it historically, will be bought, sold, underwritten and serviced in a fundamentally different way within the next three years
- External data and contextual information will become increasingly more important than historical internal data for predicting risk and pricing
- A majority of the simple covers will be bought in standard units through a marketplace/ exchange, permitting just-in-time, need and exposure based protection through mobile access
- Solutions will continue to evolve from protection to behavioral change then to prevention — even across complex commercial insurance
- Although proliferation of data and increasing transparency on the buyer and seller will cause disintermediation for simple covers, it will also create opportunities for brokers and intermediaries to innovate solutions and channels for their B2C (non-standard risk pools, retirees/older generation, healthcare gaps) and B2B (emerging and unknown risks, cyber, global supply chains, cross-border liability, terrorism) customers
- The ability to dynamically innovate (new risk pools, new segments, new channels) and deliver on the customer promise will become the most important competitive advantage (as known risks continue to get commoditized and move to the direct channels)
- Internal innovation, incubation and maturing of capabilities will no longer be the optimal option; dynamic innovation will require aggressive external partnerships and acquisitions
- Simple “Grow or Go” decisions of the last decade will be sub-optimal, as the dust settles in insurtech; building in future optionality and degrees of freedom will be the key
- Consolidation just for economies of scale will provide increasingly less marginal value in non-life as well as life insurance; real value creation will come from “economies of skill” and digital capabilities
- Deep learning (next generation of AI), blockchain and genomics technologies will improve financial inclusion and better meet the needs of the under-insured and uninsured
We have linked the above trends to analysis of how profit pools will change over time to build an investment strategy that also focuses on platforms or clusters that allow us to build more compelling propositions by connecting related players in adjacent parts of the value chain.
Three areas of initial focus are:
1. A digital front office solution that leverages an open architecture platform developed by Convista (OneDigitalOffice), augmented by relevant startups including, for example, on-demand insurance by Oula.la and social media adoption by Digital Fineprint.
The ability to drive dynamic innovation is driven by technology stack/system flexibility to respond quickly to customer needs. New risk pools, new products and new ways to reach customers will place massive pressure on traditional systems, making a dynamic digital front office key to execution.
- 360-degree multi-channel (direct, field sales force, internal sales force, independent agents/brokers) connectivity
- Augmented functionality across the value chain from sales/distribution through underwriting, binding and servicing
- Sales funnel optimizer (sales force effectiveness) — inquiry/quote, quote-to-submission, submission-to-bind ratio
- Sales force/intermediary (broker/agent) segmentation and performance management
As an example, the impact of the sharing economy and need for on-demand insurance will require instant pricing and cover that switches on and off at point of sale to meet the needs of the customer.
2. An end-to-end claims solution developed by RightIndem and supported by additional capability from other technology providers
The claims space is an interesting one; it represents the largest individual expense on any P&C insurer’s P&L but conversely has seen very little innovation. This is now starting to change. RightIndem has developed a platform that achieves significant improvements in customer satisfaction while significantly reducing the cost of managing the claim. This is a win/win for the customer and the insurer and in our view a classic enabler technology that takes an existing function within the insurance value chain but does it much more effectively and with the interests of the customer at its core.
See also: Insurtech Checklist: 10 Differentiators
3. Artificial intelligence (AI) with an initial focus on life and health insurance developed by Gen.Life
We are particularly excited about the combination of AI and the latest health technology to transform insurance. Examples include Livingo Health, which combines a blood glucose monitor support and intervention to help coach people through diabetes, and Cycardia Health, which employs machine learning predictive analytics software to categorize abnormal circadian patterns in otherwise healthy breast tissue to provide early detection of breast cancer. These types of technology will allow the early detection of potential diseases so that preventative treatment can be started much earlier, dramatically improving chances of success. Rather than life and health insurance being about prospective payments after an event, they can become the key mechanism for deploying technology to allow people to enjoy healthy lives.
The insurance industry will look very different in five years, but more importantly there is an opportunity to drive huge benefits to society through reducing under-insurance and supporting the transition from protection to prevention.