Insurance claims processing investigates data such as the validity of submitted claims and determines the extent of the coverage and other personal information of the claimer. Analyzing claims is integral to speeding up the process and preventing fraud. This is where insurance claims analytics outshines.
Handling claims becomes a challenge with excessive claims floating around your insurance business. Even your adjuster won’t have time to sift through all the data and evaluate each claim diligently. As an insurer, your adjuster probably becomes incapable when it comes to decision-making. They may make decisions based on their experience, intuition, and the limited information available.
Therefore, integrating data analytics into your claims process can help you improve overall work efficiency. It will be a win-win situation for both your insurance business and the policyholder.
What is Insurance Claims Data Analytics?
According to Garter, “Insurance claims analytics is using business intelligence (BI), reporting solutions, dashboards, data mining, and predictive modeling technologies to manage and analyze claims data, resulting in improved performance”.
It acts as a magnifying glass to analyze existing processes and their performance thoroughly. Insurers can identify trends and patterns for streamlining process bottlenecks and provide greater visibility.
6 Ways You Can Use Data Analytics to Streamline Insurance Claims Management
For this reason, many insurance firms are moving towards integration of data analytics. However, if you outsource claims processes, you can reap the maximum benefit of their services. As an insurer, give access to your insurance BPO services provider and let them take charge of the process. On the other hand, you focus on strategic tasks of your insurance business. Let’s see how insurance claims analytics add value to your business.
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Comprehensive Claims Data Management Workflows
As an insurer, you know that data stems from diverse sources such as onboarded policyholder details, claims applications, investigated data, and various other documents. Maybe you captured the data manually or automated the process, availing resources. Once you gather all the data, it needs to be extracted, transformed, and loaded for human validation.
Logical data structuring helps you centralize the data that works as a single source of truth and ensures data accessibility. This is where data analytics comes with robust management systems. They store, sort, and organize data in a few clicks. It can automatically capture data, measure its quality, delete duplicate or outdated information, and identify patterns around data fidelity.
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Accurate Claims Processing Without Errors
Whether your insurance claims are impeccable or automated, there’s always room for improvement. Data analytics helps you identify patterns and trends and provide deep insights into claims processing.
For example, data analytics can easily detect errors that crop up during collection, such as incomplete information or inconsistent data. After identifying the issue, you can improve data quality and attain efficiency in your claims process.
Insurance claims analytics also help you detect internal and external fraud during processing claims. It can be in the form of unusual billing or several claims. When you identify such patterns, you can take preventive measures against such frauds.
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Fast Fraud Detection and Prevention
According to report, insurance fraud revenue losses cost around $USD 308.6 billion annually. Hence, immediate resolution of such fraud can stop the havoc. That’s where data analytics can be your savior!
Data analytics can detect and prevent fraud efficiently through several strategies.
As mentioned, it identifies patterns and pinpoints red flags. Similarly, it maintains a log of claims data and spotlights any outliers to protect policyholder’s interests. In this way, your insurance business can foster a culture of trust.
With real-time fraud detection and mitigation, as an insurer, you can ensure preventive measures in the long run.
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Smooth Optimization and Settlement of Payouts
Claims processing is one of the key aspects that enhances customer experience in the insurance landscape. Seamless claims processing experience improves your reputation in the market. With this pressure, insurers often struggle to settle claims at a pace with accuracy. Another challenge that insurers face while settling claims is minimizing overhead costs.
Data analytics ensure a balance between various claims processing needs. Data analytics can also forecast claims-related costs and ensure transparency, speedy and fair claims settlements. These insights can help you handle and settle long-tail claims swiftly. It is a way to pave the way for automation in your insurance claims management services process to attain:
- Improved customer experience
- Estimate and cap payout limits
- Maintain cash reserves for future claims
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Enhanced Compliance and Litigation Avoidance
Claims are the major contributor to legal disputes between insurers and customers. When it comes to insurance products, claims dispute lodgment rations reached approx. 80% to 90% within life insurance. The increasing lodgment is a sign more than a problem for claims processing. It further leaves room for compliance failure and litigations.
Therefore, insurers are more focused on improving their claims process and ensuring everything conforms to the terms and conditions of the policy. Leveraging insurance claims analytics can help you maintain an auditable and traceable record for all business decisions.
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Better Product Efficiency
By integrating data analytics into your claims process, you can identify trends and patterns to develop high-quality products for customers. These valuable insights can help you evaluate the insurance market and understand customers’ changing preferences. As an insurance business owner, you can tailor your products as needed.
Why should you make Data Analytics a Part of your Insurance Business?
Insurance is a commodity. It becomes crucial for carriers like you to outshine in the market. With insurance claims analytics, you can deliver measurable ROI with cost savings. Just a 1% improvement in the loss ratio for a $1b billion insurer is worth more than $7 million on the bottom line.
