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The Power of Profiling and Analytics in Insurance Claims Processing

Updated: Jun 12

The Indian General Insurance industry is a significant contributor to the financial sector, Upto December, 2023 Non-Life Industry had a Gross Written Premium (GWP) of Rs 2,13,486 Cr with a growth rate of 14.07% as compared to Rs 1,87,147 Cr for the year prior. This growth is driven by rising demand for health and motor insurance products. However, with increasing premiums comes the challenge of managing a growing volume of claims efficiently and fairly. Advanced analytics and profiling of customers, garages, health providers, diseases etc. can streamline processing, reduce costs, and improve customer satisfaction. Collaboration and data quality are crucial for AI/ML adoption in general insurance across India.

Challenges in Claims Processing

  • Manual Workload: Traditional claim processing methods involve manual review of documents, leading to delays and potential errors.

  • Fraudulent Claims: Identifying and preventing fraudulent claims remains a significant challenge for insurers.

  • Inconsistent Decisions: Manual review can lead to inconsistencies in claim decisions, affecting customer satisfaction.

There are several key reasons why profiling claims is crucial for automating the claims process in the Indian General Insurance sector, encompassing both health and motor insurance:

1. Risk Assessment and Claim Triage:

  • Profiling allows for categorising claims based on risk factors like previous claims history, type of damage/disease, repair garage/hospital involved, and policyholder demographics.

  • This risk assessment helps identify low-risk claims that can be processed through automated workflows with minimal human intervention.

  • Faster processing of low-risk claims frees up adjusters to focus on complex cases requiring human expertise and judgement.

2. Standardisation and Consistency:

  • Profiling helps establish benchmarks for common procedures, repair costs, and treatment protocols based on historical data and pre-defined parameters.

  • This standardisation allows automated systems to assess claims against established criteria, leading to more consistent and predictable claim decisions.

  • Reduced human intervention minimises the risk of errors and inconsistencies in claim processing.

3. Fraud Detection:

  • Profiling helps identify patterns indicative of potentially fraudulent claims. This can include analysing claim frequency for specific diseases, repair costs exceeding historical benchmarks, or a sudden surge in claims for a particular type of damage in a specific location.

  • By flagging suspicious claims, automation can trigger further investigation, potentially saving insurers significant costs associated with fraudulent activity.

4. Improved Efficiency and Speed:

  • Automation powered by claim profiling streamlines the entire claims process. Low-risk claims can be settled faster, reducing processing time and administrative costs for insurers.

  • Faster claim settlements improve customer satisfaction and enhance the overall experience for policyholders.

5. Data-Driven Insights:

  • Profiling generates valuable data insights that can be used to improve future claim processing strategies. This data can help insurers identify areas for cost reduction, optimise resource allocation, and potentially develop new insurance products tailored to specific risk profiles.

Overall, profiling claims plays a vital role in enabling claims automation by providing a data-driven foundation for efficient, standardised, and potentially fraud-resistant claim processing in the Indian General Insurance sector. Drona Pay offers a comprehensive module to generate Profiles at various levels which is essential for data driven decision making and identification of anomalies. More details on how Drona Pay approaches profiling to assist in automation of claims processing is provided below :

Profiling at Garages (Motor Insurance):

  • Risk Assessment: Analysing repair history at specific garages can help insurers assess the likelihood of inflated repair costs or potential collusion with fraudulent claims. Garages with a history of consistently high repair costs might be flagged for further scrutiny.

  • Standardised Repairs: Profiling repair practices at garages allows insurers to establish benchmarks for repair times and costs based on specific vehicle models and damage types. This helps identify significant deviations that could indicate unnecessary repairs.

  • Network Garages: Insurers can build networks with reputable garages known for fair pricing and quality repairs. Claims processed through network garages can benefit from faster approvals and potentially pre-negotiated repair costs.

Profiling by Damage Type (Motor Insurance):

  • Claims History: Profiling claims based on the type of damage (e.g., collision, theft, vandalism) allows insurers to identify patterns and assess risk associated with specific vehicle types or locations. This information can be used for risk-based pricing and potentially offer discounts to low-risk drivers.

  • Repair Cost Estimation: Profiling historical repair costs for different damage types allows insurers to develop more accurate estimates for claim settlements. This reduces delays and avoids potential disputes over repair costs.

  • Fraud Detection: Analysing the frequency and nature of damage claims can help identify potential staged accidents. For example, a sudden increase in claims for a specific type of damage in a particular location might warrant further investigation.

Profiling at Hospitals (Health Insurance):

  • Treatment Protocols: Profiling hospitals based on their treatment protocols for specific diseases allows insurers to identify potential over-treatment or unnecessary procedures. This helps assess the validity of claims and prevent overpayments.

  • Cost Analysis: Analysing historical treatment costs for specific procedures at different hospitals allows insurers to establish benchmarks for reasonable charges. This helps identify potentially inflated charges on claims.

  • Cashless Network Hospitals: Similar to network garages, insurers can build networks with hospitals known for fair pricing and adherence to best practices. Cashless claims processed through these hospitals can be faster and more convenient for policyholders.

Profiling by Disease (Health Insurance):

  • Risk Management: By analysing historical claims data for specific diseases, insurers can develop risk profiles. This helps identify individuals with a higher likelihood of developing certain conditions and allows them to tailor coverage options or implement preventive healthcare measures.

  • Treatment Cost Prediction: Profiling by disease allows insurers to predict the average cost of treatment for various conditions. This facilitates efficient resource allocation for claims processing and potentially faster settlements.

  • Fraud Detection: Analysing claim patterns for specific diseases can help identify suspicious trends, such as frequent claims for the same condition within a short period. This can be a red flag for potential fraudulent activity.

Benefits of Profiling:

  • Faster Claim Processing: Profiling helps streamline claims processing by identifying low-risk claims that can be settled quickly with minimal manual intervention.

  • Reduced Costs: Profiling can help prevent fraudulent claims and overpayments, ultimately leading to lower insurance premiums for policyholders.

  • Improved Customer Experience: Faster claim settlements, reduced paperwork, and potentially personalised coverage options enhance customer satisfaction.

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