The rate at which Data is generated from multiple sources in several formats in a single day is beyond imagination. Today, organisations use Data to enrich business, finding current status based on facts and stats, making a business leader take the right decision.
Without Data, it is hard for companies to acquire customers and taste victory in the business. Processing the acquired Data turns into Information that fundamentally becomes the heart and soul of the business.
In Health Insurance, Data and Information are inevitable factors that help run the business successfully. Due to rapid and abundant advancements in technology, companies use technology as a scalable platform to establish their brand and garner customers to develop and sustain the business.
Some of the prominent technology evolution we witnessed in recent years is nothing but the tremendous growth and technology adaption that results in the implementation of technologies like Artificial Intelligence (AI) and Machine Learning (ML).
These technologies minimise the complexity of Data processing and accelerate the pace of problem-solving. Health Insurance as an industry has started adopting AI-ML-driven problem-solving approaches in a big way.
It also ensures a seamless user experience for the policyholders whenever they purchase the policy online, either by using websites or mobile applications and also improves overall customer service.
Importance of Data Science in Health Insurance
With an increase in the number of digital interactions, we are now at a stage where Data diversity and Data availability are at a higher rate. However, the real challenge comes in using it efficiently and productively.
Data Science enables organisations to use and understand a huge amount of Data from multiple sources efficiently and extract valuable insights. These insights help businesses identify the shortcomings of existing implemented solutions and changes required to improve the interaction between the insurer and the insured.
It further helps visualise upcoming challenges and evaluate competition with other existing providers in the market.
Contribution of Data Science
Data science contributes by helping insurers develop effective strategies for acquiring new customers, creating personalised products, analysing risks and implementing fraud detection systems.
Efficiency Improvement
One of the advantages an organisation can have is, it helps in identifying when and where their products are getting sold the most. As a result, it will help the company to find the right customers to pitch the right product at the right time.
Financial Benefits
Right update to the Sales and Marketing team results in engaged customers and better services will help in reducing the customer churn rate, Sales Lead Generation process will help in finding new customers, which results in the benefit of the organisation for more revenue generation.
New Opportunities
Once you segment your customers into multiple divisions, you can easily understand their demands at a granular level. The hidden patterns in the Data will help an organisation customise the existing products and create new products.
Specific to the Health Insurance industry, it can also help expand the network with nearby hospitals and labs.
Some of the Important Use cases of Data Science:
Fraud Detection
Understanding the behaviour/pattern of customers, hospitals, Agents and SMs at the time of claims helps predict the genuineness of an incoming claim. AI/ML enables the system to create an alert for all the suspicious claims and helps prevent fraudsters.
Customer Segmentation
Companies use big Data to store all the customers’ interactions and design the customer usage journeys to suit their needs. This enables the right sale of Health Insurance products that are in line with the customer’s requirements.
Through Technology, Health Insurance companies can design their new products based on the customers’ demands.
Insurance companies can seamlessly target the right customers based on their financial background, paying capacity, family size, etc. In simple words, it provides a one-on-one experience between an insurer and an insured through digital technology.
Renewal Retention
Based on the renewal behaviour of the existing customers, Data science helps prioritise the customers who require a reminder to renew their policies and de-prioritise the customers who are proactive in renewing their policies.
With this targeting, the organisation can prepone the renewal collection, thereby increasing the customer retention rate. Further, proactive customers will be subjected to lesser reminders.
Reason for Investment in Technology
Health Insurance companies spend huge amounts of money to foster technology in their businesses.
Companies firmly believe that in this technology-driven world, where most of the transactions are happening through mobile and the internet, the company that captures the digital business will be able to give the best experience most efficiently.
Summing up
To become a mammoth of any business, companies have to shift and adapt the business to sustain themselves among competitors. Data Science is the most efficient way to solve complex problems and provide solutions in this digital era.
Experience and Engagement bring a sense of clarity about the product to the customers. It also incentivises the users to stay connected to the platform through a personalised experience.
The information contained in this blog is provided based on the author's views, opinion and understanding.
