The next phase of insurtech deployment is expected to be focused on improving efficiencies in insurers' core functions. Opportunities present themselves in many areas and each requires skills to be harnessed in-house, but they will also rely upon strong partnerships with third parties.
One of those key areas is in the application - and mastery - of artificial intelligence (AI) and machine learning.
The rise of the machines
AI has a wide range of uses that can greatly simplify onboarding and customer service, in particular the claims settlement experience. Though the experience to date of claims estimation for auto damage has been mixed, it is an example of how, in the future, a claim will likely be simpler and cheaper to process and therefore settled more quickly, to the benefit of both insurer and customer.
AI is expected to revolutionize more specialized functions such as fraud prevention, anti-money laundering through to underwriting and pricing.
The human touch in a digital glove
As mentioned previously, customer engagement is important, but AI will extend far beyond marketing.
Mental health is a major cause of lost productivity, because it can take months for an employee to be diagnosed and to start treatment. The sooner this process begins, the better, but typically, once an employee is absent due to mental health matters, all contact is lost, making future contact very hard to initiate.
Platforms are already being developed to bridge the pastoral and clinical environments to assist those with mental health - or musculoskeletal problems - to stay in touch with the employer through a virtual consultant or counsellor. This will maintain contact and keep channels of communication open, helping them back into the workplace more quickly. It will also offer ongoing support to keep them there with monitoring and through support networks.
AI generates data, the lifeblood of the insurtech and insurers that lack data or the partners and models that generate it, will find their business models severely challenged.
AI and machine learning is a transversal tech with applications across the value chain and it may prove to be the biggest driver of efficiency.
Players in this space:
Carpe Data - gathers and refines a range of emerging and alternative data sources enhancing all facets of the insurance life cycle.
Lemonade - property and casualty insurer that returns a portion of premium in a no-claim period
Policybazaar - online insurance market aggregator
Shift Technology - AI-based anti-claims fraud
- Insurtech 10: Trends for 2019
- Trend 1: Digitize or die
- Trend 2: Ecosystems rock
- Trend 3: It's a new game - press reset
- Trend 4: Digital risk reduction
- Trend 5: Focus on the digital customer
- Trend 6: Data is the new oil - and the price is going up
- Trend 8: Auto insurance - disruption coming but direction not clear
- Trend 9: New role for the oldest skills
- Trend 10: Skill up and reorganize urgently for a digital world