December 6, 2019
3 Big Challenges on the Way to Nirvana
To fulfill insurtech's promise, insurers must get their heads around cognitive computing, big data and data exchange standards.
We hear almost daily how insurtech is disrupting the once-staid insurance industry. The main ingredients are big data, artificial intelligence, social media, chatbots, the Internet of Things and wearables. The industry is responding to changing markets, technology, legislation and new insurance regulation.
I believe insurtech is more collaborative than disruptive. There are many ways insurance technology can streamline and improve current processes with digital transformation. Cognitive computing, a technology that is designed to mimic human intelligence, will have an immense impact. The 2016 IBM Institute for Business Value survey revealed that 90% of outperforming insurers say they believe cognitive technologies will have a big effect on their revenue models.
The ability of cognitive technologies, including artificial intelligence, to handle structured and unstructured data in meaningful ways will create entirely new business processes and operations. Already, chatbots like Alegeus’s “Emma,” a virtual assistant that can answer questions about FSAs, HSAs and HRAs, and USAA’s “Nina” are at work helping policyholders. These technologies aim to promote not hamper progress, but strategies for assimilating these new “employees” into operations will be essential to their success.
Managing the flood of data is another major challenge. Using all sorts of data in new, creative ways underlies insurtech. Big data is enormous and growing in bulk every day. Wearables, for instance, are providing health insurers with valuable data. Insurers will need to adopt best practices to use data for quoting individual and group policies, setting premiums, reducing fraud and targeting key markets.
See also: Has a New Insurtech Theme Emerged?
Innovative ways to use data are already transforming the way carriers are doing business. One example is how blocks of group insurance business are rated. Normally, census data for each employee group must be imported by the insurer to rate and quote, but that’s changing. Now, groups of clients can be blocked together based on shared business factors and then rated and quoted by the experience of the group for more accurate and flexible rating.
Cognitive computing can also make big data manageable. Ensuring IT goals link back to business strategy will help keep projects focused. But simply getting started is probably the most important thing.
With cognitive computing, systems require time to build their capacity to handle scenarios and situations. In essence, systems will have to evolve through learning to a level of intelligence that will support more complex business functions.
Establishing effective data exchange standards also remains a big challenge. Data exchange standards should encompass data aggregation, format and translation and frequency of delivery.
Without standards, chaos can develop, and costs can ratchet up. Although there has been traction in the property and casualty industry with ACORD standards, data-exchange standards for group insurance have not become universal.
See also: Insurtech’s Approach to the Gig Economy
The future is bright for insurers that place value on innovating with digital technologies and define best practices around their use. It’s no longer a matter of when insurance carriers will begin to use cognitive computing, big data and data standards, but how.