Insurance Analytics Software

Blog article
by Bob Thomas

Insurance Analytics Software: What is It and How Can It Help?


Data analysis and statistical techniques have long been used in the insurance industry to gain valuable insights and improve decision-making. Generally referred to as “insurance analytics,” this practice involves analyzing large volumes of data related to insurance policies, claims, and customer behavior to extract meaningful information and detect trends. The goal for insurers is often to lower costs and minimize their financial risk. 

With recent advances in information technology, the accuracy and efficiency of this type of data analysis have improved significantly, spurring the development of insurance analytics software as a category unto itself. While insurance companies use this software to analyze various aspects of their operations, claims management has the lion’s share of its application. 


Common Uses for Insurance Analytics Tools

Insurers use analytics solutions to analyze claims in a number of ways. Some examples are:

  • Claim Severity Analysis. The severity of claims is often evaluated by using this software to analyze historical data and compare it to current claims. This helps insurers understand the potential costs and risks associated with claims, allowing them to make informed decisions on coverage and pricing.
  • Fraud Detection. By analyzing patterns and anomalies in claim data and identifying connections between seemingly unrelated entities, the software can identify claims that are potentially fraudulent. It looks for suspicious behavior, unusual patterns, and inconsistencies to flag claims that may require further investigation. It also can assist insurers in identifying commonalities among otherwise unrelated claims, policyholders, healthcare providers, and other entities.
  • Claims Investigation. To assist them in investigating claims, insurers often use analytics tools to map connections between claimants, witnesses, vehicles, and other relevant entities in accident-related cases.
  • Risk Assessment. By analyzing relationships between policyholders, assets, locations, and other factors, with insurance analytics software, you can build predictive models to estimate the likelihood of future claims. This provides insurers with a comprehensive view of risk, helping them to make more accurate decisions in underwriting.
  • Customer Insights. Insurers often use the software to analyze customer feedback, interaction data, and claim history in an effort to identify areas for improvement in the customer experience. By revealing connections and interactions among customers, the software helps insurers understand customer behavior and preferences. Insurers then use these insights to streamline processes, personalize services, and enhance overall customer satisfaction.
  • Claims Processing Efficiency. By automating and streamlining claims processes, the software can help reduce the administrative burdens on insurers, improve their efficiency, and accelerate their claim settlements. It can also identify bottlenecks or areas of improvement in the claims workflow.
  • Regulatory Compliance. Analytics tools can assist in tracking relationships and transactions to ensure compliance with changing regulations, anti-money laundering efforts, and other legal requirements.
  • Market Analysis. The tools can provide insurers with insights into market dynamics, competitors, and emerging trends by analyzing relationships between insurance companies, brokers, agents, and other stakeholders.


How Graph Technology Benefits Insurance Analytics Software

Going beyond the typical insurance analytics capabilities normally required for these use cases, graph analytics tools in particular enable insurers to identify, visually represent, and explore complex relationships and connections within and across large data sets. This type of software allows for advanced querying, pattern recognition, and rapid analysis of interconnected data points. These graph-specific capabilities help to accelerate decision-making, improve fraud detection and investigation, optimize processes, and enhance risk management, ultimately empowering claims teams and Special Investigation Units (SIUs) to stop more fraudsters faster.

As a comprehensive insurance analytics platform developed with advanced graph and database technologies, DataWalk offers unique capabilities to detect and investigate fraud more accurately and efficiently. These capabilities enable you as an insurer to:

  • Streamline Data Preparation. DataWalk accepts your data as it is, and enables you to transform or massage the data as needed on your own, without requiring additional work from IT or data owners.
  • Integrate & Analyze Internal/External Data. Easily connect all your desired internal data sources (databases, data warehouses, Excel files, images, etc.), and connect them with key external sources such as public records, subscription services, and social media*.
  • Easily Create or Tune Rules & Scores. DataWalk provides a library of rules that can easily be adopted and customized. In addition, you can easily generate and optimize your own rules and scores. Unlike “black box” solutions, since they’re all transparent, you can see which rules drove a score, test your hypotheses, and tune any of them yourself.
  • Reduce False Positives & Spot More Suspicious Claims. By tuning rules and scores, you can continually improve your ability to identify suspicious claims and reduce your rate of false positives to as low as 10%.
  • Dramatically Accelerate Triage. With DataWalk you can see instantly which components have the greatest influence on a high-risk score, and then automatically assign that claim for further analysis or investigation, accelerating claims triage. With an accuracy rate as high as 90%, some companies eliminate triage altogether.


insurance analytics software

DataWalk automatically identifies organized crime groups and detects suspicious claims with up to 90% accuracy, enabling insurers to dramatically reduce false positives and accelerate claims triage.


  • Analyze Networks. In the case of health insurance, the software can analyze networks of healthcare providers and their affiliations to ensure accurate billing, detect potential fraud, and optimize provider networks.
  • Expedite Fraud Investigations. DataWalk integrates capabilities for both detection and investigation of suspicious claims, providing you with a single interface for an aggregated view and analysis of all your data. You can create reports, and share data, analyses, and investigation files with authorized colleagues. The software also scans your data and identifies clusters to reveal organized crime groups and other patterns of interest. 
  • Automate & Operationalize Results. Designed to be part of an enterprise workflow, DataWalk offers open APIs to import/export data from/to other systems, and to enable other systems to initiate analyses or extract data or results from DataWalk. Suspicious claims can automatically be forwarded to SIUs, without the need for manual intervention.


With these capabilities, insurance analytics software like DataWalk can optimize and accelerate many of the processes underpinning insurance fraud detection and investigation. Doing so empowers insurers to analyze and understand their claims data more effectively, uncover hidden patterns and trends, and better serve their customers, all while mitigating their exposure to fraud risk.

*Accessing social media data requires an additional third-party software product purchased separately.
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