The global insurance industry has had $4.1 trillion of premium written in 2015. It’s an industry on the cusp of change with investments totaling $1.4 billion on InsurTech firms in just the first three-quarters of 2016. However, it has become clear that the breadth and scale of the opportunity are not evident to many of them. The mental model of ‘InsurTech’ seems to be limited to the claims part of the value chain only. This article outlines a 5 C framework to help startups navigate the insurance opportunity landscape.
The 5Cs of opportunity in life insurance are – communication, customization, connection, cognition, and consensus. Let’s look at each in turn:
Communication
At its core, insurance is a promise. Now, there isn’t much value in a promise if you can’t communicate it! So the opportunity here is for startups creating exciting means of communication – think chatbots (SPIXII is a good example) and robo-advisors (Pi-sight) and those enabling the insurer to use social media effectively.
There is also an opportunity for those creating content – how can we better educate our customers about the benefits of my product? How can we become a source of valued and used content for our customers? Finally, the largest near-term opportunity is creating communication tools for the insurer’s intermediaries (agents and brokers). Most insurance business (especially in Asia) is still written through intermediaries, and improving their ability to communicate with customers is high on the insurer’s agenda. Think Salesforce applied to the insurance workflow. How can you simplify the tool so that an agent uses it?
Customization
I’m sure my Amazon and Netflix recommendations are very different from yours. Yet, in all probability, our insurance dashboards look remarkably similar, if not the same. And, when it comes to renewal, our prices will be roughly the same (assuming we are the same age for life insurance or live in the same postcode for home insurance). This is because insurance has still not boarded the personalization bus.
We see two different opportunities in this pool: 1. Startups building recommendation engines to customize risk coverage (like Knip or Clark); and 2. Startups generating data sets that can be used to change the basis of underwriting. The potential for 2 is that large companies using connected devices, genomics, and even social media analytics generate enormous data sets. How can these be used to supplant traditional underwriting tables and bring about true customization in insurance? In addition, tomorrow’s leading carriers will embrace real-time underwriting as customers produce more capture-able data. Digital Fineprint has made excellent progress in this regard.
Connection
The critical challenge for companies today lies in getting noticed. To get noticed, you have to be part of your customers’ conversation. You have to engage without interrupting. It’s a tall order, and insurance companies are particularly bad at it – we average only 1.44 customer interactions per year. So it is hardly surprising that most customers feel no sense of connection or loyalty to their insurer and that insurance ranks near the bottom for customer satisfaction scores.
The opportunity here lies in ancillary services. Potentially, digital solutions that increase the number of connections we can have with a customer along with the following aspects:
- Health, emotional health, affinity group, or financial goal setting
- Social media analytics and other heuristics to identify key moments
- Ideas that drive connectedness, helping us establish a deeper relationship with our policyholders
The top digital companies like Tencent and Facebook have shown that their chief assets are connections and community. So increasing customer interactions and loyalty is genuinely a billion-dollar-plus opportunity. Sureify is building an excellent tool-set to increase connections.
Cognition
We use cognition as shorthand for the broader Artificial Intelligence and Machine Learning opportunity. Strictly speaking, cognition runs across the earlier Cs (communication, customization, and connection), but due to its impact, we feel it deserves its own section.
We are in the early stages of the artificial intelligence (AI) revolution. Learning algorithms, whose results improve with experience, will enable us to find patterns in large data sets and make predictions more effectively — about people, processes, and entire systems. Ultimately, these technologies will completely transform the entire insurance organization.
In insurance, we see AI/ML tools being used for:
- Fraud detection and monitoring
- Claims automation
- Marketing with customization
- Behavioral analysis for improved pricing
- Preventive insurance using Genomic data sets
Insurance is one of the largest industries that you can target with your AI tool.
Consensus
By consensus, we mean blockchain(s) (consensus refers to the underlying algorithm that underpins their structure). For instance, a life insurer is the epitome of the trusted intermediary – you expect it to honor its promises after your death! Needless to say, when you can encode this trust onto a blockchain in a DAO (decentralized autonomous organization), then the whole industry will look very different.
However, blockchains can significantly impact administrative costs in the near term by making processes such as KYC (know your customer), fraud, and other verification services (policy issue, claim filing, etc.) cheaper.
Ideally, the entire industry would collaborate on a blockchain solution. However, that is challenging. So, can you find an attractive use case that a single insurer can use?
Collaborating with Insurers
Insurance is a heavily regulated industry, and insider knowledge is a prerequisite for success. This makes it hard for entrepreneurs from outside the industry to enhance the capabilities of the industry. The smart bet is to partner with an insurer. In addition, it is a good idea to connect with the innovation lab – usually the easiest way into the organization.
Insurance is a large and exciting space. It can be a great vehicle for growth if you have a use case that fits one or more of the Cs.
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