The world is one big ball of unrefined data and big data is the name of the game. Raw data doesn’t do much, but with the help of data analysis, it becomes invaluable. It provides valuable insights into all facets of company operations and performance – from consumer behaviour to underwriting practices to the ROI of marketing campaigns. Using some of the health insurance data analytics trends, we can see new strategies for insurance big data analytics that will help companies do even more with their information.
Nowadays, customer expects total transparency and an exceptional experience at every stage of the member lifecycle. Based on this shift in the market, health insurers need provide more insightful recommendations to members based on their personal data so they can make better decisions regarding their coverage and overall health.
Trends in Health Insurance Analytics
Health insurers need to stay on top of the latest data analytics trends in the insurance industry to be on the edge of competition. Following is some of the latest trends in health insurance.
- Member-centric : Today the health plan members are treated as individuals instead of a collective group. The reason being members are given importance and well understood by their health plan providers.
- Predictive modeling: Health insurance companies are using predictive models to forecast future healthcare costs and identify high-risk individuals. This allows them to proactively manage their risk and improve their financial performance.
- Personalized pricing: Health insurance companies are using big data analytics to offer personalized pricing based on an individual’s health history, lifestyle, and other factors. This allows them to better target their products to specific segments of the market.
- Fraud detection: Big Data analytics is being used to identify and prevent fraudulent activity in the health insurance industry. By analyzing patterns in claims data, insurance companies can identify unusual activity that may indicate fraud.
- Population health management: Health insurance companies are using big data analytics to improve population health management by identifying trends and patterns in population health data. This allows them to develop targeted interventions to improve the overall health of their insured population.
- Improving the customer experience: Health insurance companies are using big data analytics to improve the customer experience by identifying areas where they can streamline processes, reduce costs, and improve service. This can include everything from automating routine tasks to improving communication with customers.
- Wearable technology: Wearables have a big advantage as they can tap data for both the health care provider and health insurer. It can leverage the Internet of Things (IoT) to collect data about the wearer’s behavioural patterns and to promote healthier habits.
- Telematics: The use of sensor technology to collect and transmit real-time data over long distances – is the latest trend in data collection and the insurance space. People have begun to opt in to plans that analyse data from their wearables and automobiles to better inform their insurance policies, in hopes of earning cheaper premiums.
- Internet of Things (IoT): The need for more data security and regulation is largely due to the vast amounts of data we now have access to. With the creation of the Internet of Things (IoT), we have created virtually incomprehensible amounts of data. It gives insurers access and insights unlike anything they had before, and can impact all areas of business specifically towards:
1. Risk assessment
2. Marketing campaigns
3. Claims processing
4. Claims leakage
5. Product pricing
Conclusion
Having good data is not enough, maximizing its usefulness is the most important aspect. There are various platforms, tools, and strategies that health insurance companies can make the most of their data, but no matter the approach, carriers must be able to gather, analyze and report on this data quickly and accurately. Given the unpredictability of the marketplace insurers operate in, an accelerated analytics journey definitely helps them drive strategic decision-making at scale across underwriting, claims management, customer satisfaction as well as policy administration functions.
