Introduction
The term “predictive modeling” has special relevance in the context of the insurance industry. The existence of big and bulky data has resulted in the extended use of predictive models in insurance markets. However, predictive models have been adopted by traditional insurance players too but its recent application is more inclined towards combating the cutting edge competition.
What is Predictive Modeling in Health Insurance?
It refers to the set of models that are used to estimate the probability of the outcome such as severity and frequency of loss, premium amount, etc. Predictive Modeling is based on the concept of Machine Learning and Artificial Intelligence which provides reliable and accurate future-oriented reports to aid policymaking and underwriting. In the insurance industry, it is majorly used for claim management, identifying potential customers, and predicting losses and claims.
Use Cases of Predictive Modeling in Health Insurance
Predictive Modeling has become the substance of great value for the Health Insurance and Healthcare industry. As a result, handling big and scattered data has become an easy sail with the statistical and AI tools of Predictive Modeling. Let’s understand where these tools are implemented in delivering a better Health Insurance experience.
| Use Cases | Description |
| Pricing Structure | Machine Learning has revolutionized the way traditional pricing structures in the industry work. The pricing today is more precise and accurate as they are based on detailed trend analysis and prediction. It takes more variables into consideration that helps to provide an accurate price assessment. |
| Risk Assessment | Using the vast data set and advanced statistical tools the Predictive Models can provide precise insight into the risk culture. The assessment of the present risk with respect to the past and the expected future risk helps to give a detailed picture of the health risks based on which Insurance policies are formulated. |
| Claim Management | Managing the claim effectively is the core job of every insurance company, and so does Health Insurance. Using its AI technology and Machine Learning Algorithm the Health Insurers identify the frequency and amount of the claim. This helps to plan the budget allocation effectively to meet the needs of the consumers. |
| Identifying Potential Customers | The Predictive Models help to identify the potential health insurance customers and then they are approached accordingly. The identification of such potent customers accurately helps to create a good market share for the company and accelerate the turnover. |
| Anti-fraud Activities | The advanced systems inbuilt with AI technologies make it possible to detect fraudulent activities such as fraud claim applications. To prevent such fraud the companies use several internal and external sources to analyze the viability of the case so presented. This process is often termed “claim verification”. Without the existence of predictive models, this process might become time-consuming and uselessly extensive as collecting data from various sources without the inclusion of technology becomes troublesome. |
Benefits of Predictive Models in Health Insurance
The tools and technologies of Predictive Models have a positive impact on the Health Insurance industries which are listed below.
- Better customer engagement and turnover.
- Quick Claim settlement
- Increased number of satisfied and happy customers
- Elimination of repetitive tasks.
- Combat the potential losses and risk effectively.
- Customize health insurance plans, prices, and premiums to attract customer loyalty and longevity.
Predictive Modeling Tools for Health Insurance
The predictive modeling tools used by Health Insurance companies are based on “what-if” models and are designed to serve distinct purposes in the industry.
| Tools | Description |
| Alteryx | This tool is useful in combining clinical operations and business data models to streamline insurance processes. Furthermore, it focuses on monitoring costs and acting as the customer support center. |
| Guidewire Live | The Guidewire data model is designed for specific insurance needs where the claim managers can predict the health catastrophe and visualize the arising claims. |
| Tractable | Using this AI-based system the Health Insurers can assess the damages like car accidents that impact the health of an insured. Here, the visual images, videos, etc are collected and used based on which data uncertainty is avoided. |
| Slice | In the Health Insurance sector, this tool is used to identify fraud with its advanced mechanism. With almost 10% of claims being fraud this becomes important to address and prevent the misuse of amount. |
| Genesis Engage | This is the customer service-oriented software that helps to automate dialogues with its predictive routing application. The product helps to channel the customer interaction with clients in real-time and improve the customer experience. |
Final Words
Predictive Modeling in the Health Insurance industry has significant use cases which have helped to create a healthy ecosystem for both insurers and the insured. As a result, the industry has seen widespread adoption of Predictive model tools to ease out the insurance operations indicating its growing scope in the future.
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