When ‘Insurance’ and ‘Technology’ is spoken in one breath, ‘Insurtech’ is born. It is the adoption of emerging technologies to improve efficiency and add value for the end customer. InsurTech has embraced the Indian insurance industry in multiple ways. Starting with customer acquisition, underwriting, upsell & cross sale, claims adjudication & fraud, product design, it has literally touched the entire value chain of insurance.
And now we are pursuing technology to fill the penetration gap by targeting the rural areas through various platforms.
Recommendation engine for customer acquisition
An acquisition process that supports direct-to-consumer approach is the need of the hour. More you know the customer, better is the products & services you can deliver to the customer. InsurTech ecosystem allows insurance companies to partner with platforms, who are churning out enormous amount of customer level data. By using this customer level data on spending habits, preferences etc customer scoring can be done and by using a recommendation engine, customised products can be delivered. Further, third-party data and AI-based insights can be combined to ensure easy onboarding.
Machine Learning models for smart Underwriting
In a manual underwriting process, most applications would take days to weeks for issuance. Underwriting is one of the most time and resource-intensive processes in the insurance customer life cycle. AI-assisted machine learning model changes this situation help building intelligence into the system for routine tasks while keeping human attention dedicated to the most complex tasks and for the final decisioning. The key factor is learning from past data sets and experience analysis of existing cohorts. The whole model facilitates Predictive Underwriting. In conjunction with a minimally inquisitive digital application process and integrated application infrastructure, AI-driven underwriting systems are helping companies to reduce issuance time drastically.
AI driven platform for Fraud Risk management
One of the major aspects in claims management is fraud and the only way to counter fraud is Data. The insurance application process generates data at every step from lead identification to underwriting and policy issuance. With these data points, a real-time fraud framework that can predict instances of possible fraud can be built. These data points could come from structured and unstructured sources and from any section of the journey including interactions with external data points, transactions, relationships, demographics. Platform should have the capability to analyse and identify fraud before it happens and let the business user develop models in real time to counter newer types of threats that emerge.
Transforming customer experience with conversational technologies
Conversational technologies offer the potential to transform the way customer experience is designed and delivered. Implementing intelligent customer interactions through chatbots, voice assistants and other similar conversational platforms enables insurance companies to personalize, automate and improve customer experience. AI enabled human conversations have proved to be more natural and empathetic than human conversations, while at the same time being immediate, accountable and cost-efficient to deliver
Enablers of hybrid sales model
While digital is the preferred mode for millennials, agents and brokers continue to be the dominant point of sales of the remaining segments. Though the actual sale would happen on a face-to-face conversation, deploying an AI based digital sales tool will help agents find the right products to sell to the right customers. Equally significant, the move to digital sales allows agents to develop and store customer data based on their daily client interaction. Over time, this will allow agents to change their sales approach from a transaction model to a “everyday partner” model, leading to cross-selling opportunities.
Accelerating transformation with cloud
Digital transformation thrives on speed and agility. Cloud makes it possible to generate seamless data flows that alleviates cumbersome legacy systems and processes. As a result, machine learning, automation and AI can be swiftly deployed and start adding value sooner rather than later
Author: Rohit Boda, Managing Director, J.B. Boda
Disclaimer: The opinions expressed within this article are the personal opinions of the author. The facts and opinions appearing in the article do not reflect the views of IIA and IIA does not assume any responsibility or liability for the same.