Insurance Analytics Solution Case Study

This is a case study of an insurance industry analytics solution built with InetSoft's dashboard and reporting software - which can be used to access and report on any type of data, including insurance industry data.

Insurance Analytics Expert Integrates InetSoft's Data Intelligence Technology

Summary

This InetSoft client requested to remain confidential.

The client sought to create an end-to-end insurance BI solution which would provide insurance companies with access to and analysis of real-time data, so that insurance companies could discover trends and insights across their entire customer base.

The client wanted to build their solution from insurance industry standard data models (Acord & OMG) that include line-of-business details such as worker compensation. Incorporating these data models into the solution would allow insurance companies to do consolidated operational reporting and analytics.

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Requirements

This InetSoft client needed a flexible fully customizable business intelligence tool, from which the insurance analytics product they envisioned could be built.

Their customers had huge amounts of data that were stored in multiple systems, which limited access and meaningful use. A BI tool was needed that could join customers' legacy or competing systems data with other pertinent business information like demographics from external social data sources.
A tool was needed whose design fit with the client's vision of having the insurance data for both dashboards and reports coming through a single metadata layer, thereby ensuring a "single version of the truth" for all insurance calculations and metrics.
The tool also needed to be able to scale up with their customers changing business needs, so that the need to look for a new BI vendor didn't arise in the future.

Solution

InetSoft's flagship product, Style Intelligence, was selected as an OEM component for the client's insurance analytics solution. The area where InetSoft's solution really stood out was the level of self-service that the solution offered to non-technical end users, not just in the easy building and modification of dashboards and reports, but also in the capability to modify and mash up data using the InetSoft data worksheet. InetSoft's proprietary data worksheet puts the power of fast data integration and mashup into the hands of business users without having to wait on IT to integrate and massage new data sources.

The client was pleasantly surprised to find that if they chose InetSoft's tool for integration, their platform could give users the ability to merge and join data sources without having to create ETL processes or even write SQL in the back end. InetSoft's Style Intelligence offered these capabilities and it could also be hosted on premise, which is a preference for many insurance companies due to the sensitive nature of their data.

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Customer Value

Since integrating InetSoft to create their insurance analytics solution, the client was named as one of the "20 Most Promising Data Analytics Solution Providers" by CIOReview.
Their solution offers better data consolidation and analysis within the often complex insurance industry, with clients gaining valuable insights and visibility into the performance of their agencies, underwriters and adjusters.
When mashing up insurance, census, and social media data, power users do not need an ETL process to connect disparate sources of data. Unique calculated customer metrics like highest rate of retention and lowest loss ratio are used for targeted marketing for better customer retention.
Business users can annotate & bookmark dashboards for better communication between the underwriting and claims departments.
Using the flexibility of the InetSoft data worksheet, insurance business rules are now incorporated into the solution to check the accuracy and quality of the data.
The client's B2B insurance industry solution offers 140 pre-built, perfectly formatted yet customizable industry standard reports, making it easy for insurance companies to provide required reporting to government agencies and shareholders.
To ensure they don't miss anything important, users can set up alert capabilities. For example, the claims department gets an alert when auto customer's losses exceed a certain amount.

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How Do Insurance Carriers Use Artificial Intelligence?

Insurance carriers are increasingly leveraging artificial intelligence (AI) to enhance various aspects of their operations, from customer service and claims processing to risk assessment and fraud detection. Here's a detailed look at how AI is transforming the insurance industry:

1. Claims Processing and Management

AI streamlines claims processing by automating many of the routine tasks involved, such as data entry and verification. Machine learning algorithms can quickly analyze claims data to identify patterns and anomalies, speeding up the approval process and reducing the potential for human error.

Automated Claim Verification: AI systems can automatically verify the authenticity of claims by cross-referencing data from multiple sources, such as photos, videos, and sensor data.
Fraud Detection: AI can identify suspicious claims through pattern recognition and anomaly detection, flagging them for further investigation. This reduces the occurrence of fraudulent claims, saving insurance companies significant amounts of money.

2. Customer Service

AI-powered chatbots and virtual assistants provide 24/7 customer service, handling inquiries and assisting with routine tasks such as policy information updates and claim status checks. These tools enhance customer experience by providing quick and accurate responses.

Chatbots: AI chatbots can answer common questions, guide customers through processes, and even help them file claims.
Virtual Assistants: Advanced virtual assistants can handle more complex inquiries, offer personalized recommendations, and escalate issues to human agents when necessary.

3. Underwriting and Risk Assessment

AI improves the accuracy and efficiency of underwriting by analyzing vast amounts of data to assess risk more accurately. Machine learning models can evaluate factors that traditional underwriting methods might overlook, leading to more precise pricing of policies.

Data Analysis: AI algorithms analyze data from various sources, including social media, credit scores, and even wearable devices, to build a comprehensive risk profile for each applicant.
Predictive Analytics: AI uses predictive analytics to forecast potential risks and losses, enabling insurers to adjust premiums accordingly and improve their risk management strategies.

4. Personalized Insurance Products

AI enables the creation of personalized insurance products tailored to individual customer needs and behaviors. This personalization enhances customer satisfaction and loyalty.

Usage-Based Insurance: AI can track and analyze driving behavior through telematics, offering customized auto insurance policies based on individual driving habits.
Health and Life Insurance: Wearable devices and health apps provide data that AI can use to tailor health and life insurance policies to an individual's lifestyle and health status.

5. Fraud Detection and Prevention

AI significantly enhances fraud detection capabilities by identifying patterns and anomalies that humans might miss. Machine learning models continuously learn from new data, improving their accuracy over time.

Behavioral Analysis: AI analyzes customer behavior to detect deviations that might indicate fraudulent activity.
Anomaly Detection: AI systems can compare claims against vast datasets to identify outliers that warrant further investigation.

6. Operational Efficiency

AI helps insurers streamline their operations, reduce costs, and improve productivity by automating routine tasks and optimizing workflows.

Document Processing: Natural language processing (NLP) algorithms extract and process information from documents, reducing the need for manual data entry.
Robotic Process Automation (RPA): RPA automates repetitive tasks such as policy renewals and claims processing, freeing up human employees to focus on more complex activities.

7. Regulatory Compliance

AI assists insurance carriers in maintaining compliance with regulatory requirements by automating compliance checks and reporting.

Compliance Monitoring: AI systems continuously monitor transactions and communications for compliance with industry regulations.
Audit Trail Creation: AI can create detailed audit trails for all automated processes, ensuring transparency and accountability.

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