Given our country has one of the lowest insurance penetrations in the world, insurers find it difficult to reach out to prospective customers at the right time, provide the right set of solutions/products to suit customer requirements and facilitate speedy claims support. When customers interact with an insurance agent, the benchmark is not one carrier vs another anymore but is the expectation of a much faster, more transparent and intuitive experience than one they have had before. Not only is this a tremendous shift in customer mindset, but with artificial intelligence, it has also presented the industry with an opportunity – and the challenge of – an elevated level of engagement.
Can artificial intelligence and cognitive technologies live up to the hopes and respond to changing times? I believe the following core technology trends, tightly combined with AI, will reshape the insurance industry over the next decade.
Data explosion and the situation of the next-billion Indians
India’s low insurance penetration, especially in the general insurance industry is not a new story. In close to two decades, India’s insurance market has grown about 3%. To try and solve this issue, several distribution channel-level propositions such as insurtech sandbox are being brought into the fray by IRDAI to help the industry reach a larger population. The unprecedented rise of the internet and smart-phone penetration in India over the last five years present both a challenge and an opportunity.
On one hand, the resulting avalanche of new data created, allows underwriters to understand their customers more deeply – leading to new product categories, tailored pricing packages and real-time service delivery. For example, small-ticket or bite-sized insurance products have shown improvements in speeding operations after the success of sachet products in the FMCG sector. On the other hand, ethical considerations for data privacy, misappropriation of data, and fraud detection of each customer and extending simple yet valuable experiences continue to be a hot agenda.
Distribution & AI-based risk profiling
User experience in the insurance industry is key at the front end. Technologies such as NLP (Natural Language Processing) and intent-driven chatbots have revealed real progress in this regard. RGI, for example, uses RIVA (Reliance Interactive Virtual Assistant), an AI-enabled chatbot on Whatsapp and Facebook messenger to facilitate effortless claim experience, easy access and transparent grievance redressal process.
Additionally, to address the concern of accuracy in risk profiling, AI and machine learning technologies are providing in-depth risk, fraud and customer models. This is done by finding hidden risk spots and decreasing the individual’s or business’ cost of recovery after a tragic impact. One such case is the recent launch of an AI-enabled car inspection feature on an insurance app by a leading General Insurance player towards speeding up renewal and claims processing in motor insurance.
That said, we are still at the nascent stages of hyper personalised products coming in to address grievances or provide a risk profile and quotes in real-time, akin to checking your phone balance.
Open source & data ecosystems for faster and accurate claims processing
Over the past few years, embedding AI in processes, services and products has become almost mainstream to deliver an intelligent and customised package, one which attracts a lot of attention and will continue to do so. In insurance, automated claims processing is playing that role to reduce operational cost and provide speedy solutions to customers.
This is the model in the open source and data ecosystems that aims for a paperless, error-less and instant claims processes. Simple claims will get approved and paid out in seconds, while the complicated ones get reviewed by the human team.
The future is customer centricity, yet challenges remain
AI is here to stay. Underwriting talent is set to work with Robo-partners and adoption of AI to boost performance, and insights are steadily reaching a tipping point.
A majority of clients are also comfortable with AI using personal data to improve customer experience, that it is well protected. Then there is AI-bias – a challenge that is created from prejudiced data inputs. A sexism bias, for example, can conduct a varying risk profile for men vs women for motor insurance.
The new-age customer of the future demands simpler terms, transparent underwriting and easily comprehensible benefit structures in one simple risk cover – from which they can choose discrete individualized need-based covers. Product innovation in this regard will require unified efforts towards simplifying and connecting to the customer in a hyper-personalized manner like never before.