AI – Machine Learning. AI and machine learning make it possible for insurance companies to mine both structured and unstructured data. The use cases range from underwriting, claims management and personalised offerings through behavioural data and sentiment analysis. There are examples of early adopters in the auto industry – but again there are obvious and wider use cases, that can benefit risk modelling, pricing, customer acquisition, and agent and channel efficiency.
AI – Virtual assistants/Chatbots. This falls right in with managing customer experiences. As customers expect more self-service (yes, the future will see less agents!) several insurance providers are using chatbots at several customer touchpoints, covering departments such as Sales and Claims. This will increasingly be the norm as smart phone (and app) penetration increases and the target base becomes younger. There are online-only insuranceproviders where clients interact with chatbots services and they are able to cater to a larger, untapped, mass market. There are more advanced adoption examples such as USAA’s use of intelligent personal assistant equipped with an NLP engine that have been trained with a deeper knowledge of policies. Virtual insurance agents will become more of a norm in the near future.
Which brings us to the important question on how insurance companies are planning to leverage InsureTech. Multiple stakeholders could benefit from InsureTech adoption. The Claims department appears to be a key stakeholder, focused both on fraud prevention and automation when it comes to transaction and processing. Sales and Customer Service appear to be next in line, where personalisation of product offerings would equip the teams better for a competitive market.
Challenges of AI Adoption in Insurance
It is obvious that the insurance companies are still at a nascent stage of adoption of AI and InsureTech. While cybersecurity is a recurrent concern (as it should be), it is a common concern across any technology area. The biggest challenge that the insurance industry faces in adoption of AI and other data-driven technologies is the actual data management – from access to integration. The industry may be data-intensive, but the data exists in silos. In the end an InsureTech implementation should benefit multiple departments – Underwriting, Claims, Sales and so on.
Several insurance companies will look to consulting firms and systems integrators to create a roadmap to their transformation journey and enable the data integration – especially as technologies evolve and when internal IT lack the right skills to manage these projects.
The technology that will be the key component of InsureTech and transform the insurance industry is AI. In spite of the challenges of adoption, the industry will be forced to transform to survive in the highly competitive market. Companies in emerging economies will especially benefit from investing in AI – in fact, India and especially China will see a surge in InsureTech investments.