5 Ways Data Science & Intelligence Can Help Insurance Companies
From underwriting to calculate mortality and premiums, the insurance industry has always been data-dependent. And therefore has always been at the forefront of embracing new data technologies. The availability or mainstreaming of deep data science technologies like Artificial Intelligence, Machine Learning, Predictive Analytics, etc., provides another opportunity for insurance companies to build next-gen data intelligence capabilities for its processes, products, and people.
Data Science has disruptive powers for the industry. It can help them go beyond data crunching to build data-models that can analyze patterns and predict outcomes with greater accuracy. And a lot more!
Here are 5 ways Data Science & Data Intelligence will be a game-changer for insurance providers
Premium Pricing– There’s a price war out there in the industry. The digitalization of the industry has further intensified it. However, insurance companies don’t have to hurt their bottom lines to win more business. Data Science technologies can help you build predictive models that can help you process historical data on costs, claims, and profits, etc., to deliver incisive intelligence on the pricing strategy. It can also help you adopt a pricing strategy based on customer’s past claims history, lifestyle and medical history, etc.
Insurance Fraud– Insurance frauds are real. And it results in huge financial losses. As per insurancefraud.org, Fraud accounts for 5 to 10% of claims costs for insurance companies in the US and Canada. Around 32% of insurers say fraud was as high as 20 percent of claims costs. Data Science can help insurance companies in effectively combating fraud. It can help build advanced software powered by predictive analytics models that can process huge amounts of data & transactions to detect patterns of suspicious activities to frauds. This can help insurance companies in identifying and investigating suspicious cases and catching fraud.
Understanding Customers– We’re living in the age of customer-centricity. Customers today want hyper-personalized products & services well-tailored to their needs. And insurance companies are no exception. But how to deeply understand customers’ needs & wants? Data Science offers solutions. You can leverage Natural Language Processing (also referred to as text analytics) to build data engines that scrape through social media channels, review websites and your own digital touchpoints to analyze and understand what your customers are talking about to deliver actionable intelligence on customers concerns, needs and wants. If properly done, these can give provide you with loads of insights to improve your products and services.
Claims Prediction– Predicting claims is an important process for an insurance company. Claims prediction helps them in building pricing models. The industry has been using a range of statistical tools and models to predict claims. Data Science can help them go beyond by helping them in processing the voluminous amount of data emanating from a variety of sources to build predictive models that can predict claims with higher accuracy.
Sales & Marketing– Data Science can take insurance sales and marketing to the next level. An insurance company can today granularly segment its customer base on the basis of age, income, lifestyle, and behavior and then devise targeted campaigns for them. Data-driven marketing automation can help you reach your customers at the right time. Recommendation engines can influence and help your customers in selecting the right insurance policies based on their past data. Insights into customer churn and Customer lifetime value (CLV) can help you build proactive strategies to ensure their loyalty.
There are many other ways data science & intelligence can help insurance companies by helping them harness each byte of data and delivering incisive insights on it.
Are you an insurance provider looking to build next-gen data intelligence capabilities? Qualetics, our on-demand platform, helps you get it without the challenges of time, investments, and resources. It helps you fully dedicate your focus on your core business operations as it takes care of your data intelligence needs. To know more click here.