The insurance sector is witnessing several use cases for advanced data and analytics capabilities and predictive modeling-based applications
FinTech BizNews Service
Mumbai, January 12, 2024: How many times have you watched a movie that popped up on your OTT platform as a recommendation? Have you ever considered the technology that powers your viewing experience and how it predicts your interest based on your previous selections?
Like many people, I grew up watching movies in theatres. But today, I can select a movie from any country, in any genre or language, and consume it anytime I want. Technology has delivered both convenience and changed the movie-going experience, asAI and machine learning (ML) algorithms canmake predictive suggestions based on deep learning and data analytics.
Now, what if I use the same technology to reimagine the insurance experience for my stakeholders? As a digital-native company, that’s the envelope that we are pushing – using tech tocreate ahyperpersonalised experience that intimately connects company and client.
Deep learning and analytics
The insurance sector is witnessing several use cases for advanced data and analytics capabilities and predictive modeling-based applications. The tech allows us to reimagine the way we service customers, recruit and train employees, market and distribute products, evaluate risks, detect frauds, and even underwrite and issue policies.
Predictive models are the neural networks that drive these applications. And the propellant powering analytics is rich data from multiple sources –historic industry pool and own data, third-party data such as location and credit scores, government and demographic data as well as learned data generated through AI.
The data insights help insurance providers to understand unmet needs and service customers through the life stages. AI/ML-based predictive analytics applications are transforming the insurance business and enabling us to put our customers first.
In tune with the customer
Life insurance companies arein the business of helping customers during their life and after life.During life, it is all about savings and pensions, and afterwards, it is about how can a customer ensure that his family continues to live respectably. Now, to attract customers and achieve high persistency levels, insurance companies need to sell themthe right productbased on their profile and need.That’s where AI-based predictive models come into play.
Insurance providerscan usepredictive models across the customer lifecycle, right from assessing a customer’s propensity to buy to hyperpersonalising marketing collateral to matching products to the customer’s needs to issuing policies instantly.
For instance, ifa customer is an agriculturist from Punjab, themarketing brochure will talk about an agriculturist’s investment and protection needs. A productsuitability model can check if there’s a mismatch between the customer’s requirements and the policy sold.
Auto issuance, an industry first
Earlier, policy issuance was a pain point for customers because of cumbersome data inputs andprocessing time. Digitalisation is enabling thereinvention of the entire insurance experience by automating underwriting and issuance of participating and non-participating savings and unit-linked products. Today, eligible policiescan be instantly issued.Even as the customer is talking to the sales agent, the policy copy will arrive in their inbox.
Hiring right
Technology is throwing up exciting possibilities to change the employee experience, too. For any sales-driven organisation, it’s imperative to attract the right talent and hire right. Now, imagine if a predictive model could look at a potential hire’s selfie or interview video and conduct a behavioural assessment to check the job fit.A predictive model could alsoanalyse body language to createinputs aroundbehavioral aspects. As of today, technology can nowsupport the hirer to assess an interviewee’s responses and determine the job fit.
Nudged to perform
Another advantage of tech adoption is that it eliminates mundane tasks, thus providing the sales force with more time to service customers. For instance, a GPS-based app that automatically clocks the kilometers an agent traverses each daycan calculate the conveyance reimbursement. It evensends a geospatial data-based nudge if, for instance,a renewal premium has to be collected en route.Forward-thinking insurers are introducing a predictive model to monitor sales performance.
Predicting the future
Data is the new gold today. And predictive analytics that enable organisations to make informed decisions and gain a competitive edge are bound to mature. In the insurance sector, being technology-forward enables the company to reimagine and deliver an entirely new and exciting insurance experience.
