Megaputer Intelligence

It is a no secret that the insurance industry is data-driven. Today, the insurers are going beyond the traditional historic data and tapping into the third-party data sources. The data from sources such as social media, mobile usage, credit bureau reports and others are helping the insurance providers to manage their business, manage risk and know their customers better. Set against this backdrop is Megaputer Intelligence; an Indiana based Software Company that delivers data and text mining tools. The company facilitates fetching and extracting of large sets of data and text and transforms it into an understandable structure, helping insurers to make better-decisions.

We minimized the waste of resources and missing subrogation opportunities by a greater percentage with the subrogation prediction tool

PolyAnalyst, a flagship product of the company, performs all the operations for data analysis and retrieval of information. It provides distinctive and powerful tools for data and text mining including promotion response analysis, customer segmentation and profiling, and cross-selling analysis— that proves to be crucial for insurers. In order to prevent the complexity, the product provides a single platform with an intuitive interface for both data and text mining tools. It derives the necessary knowledge from large volumes of text and structured data, delivering this information to the decision makers – enabling insurers to understand custom reports and include the retrieved information in their business processes. This data analysis enables an insurance provider to keep a track of the changing customer preferences and behavior, thereby, enabling them to develop and optimize claims for enhanced profitability. “Intelligent decisions provide new competitive edge for insurers,” says Sergei Ananyan, CEO, Megaputer Intelligence. Through its drag and drop interface, data analysts can create multi-step data analysis scenarios and report templates for decision makers.

Sergei Ananyan, CEO, megaputer intelligence leveraging big data to bring transformational changes in insuranceSergei Ananyan, CEO
In a complete data analysis cycle, PolyAnalyst also offers a comprehensive selection on algorithms for automated analysis of text and structured data. The numerous knowledge discovery operations or algorithms are categorization, clustering, prediction, link analysis, keyword and entity extraction, pattern discovery and anomaly detection.

PolyAnalyst safeguards resources of insurance companies with its Subrogation Prediction tool. The tool is built on PolyAnalyst platform enabling insurance companies not to miss subrogation opportunities as it costs them hundreds of millions of dollars. Megaputer’s subrogation prediction tool develops a claim categorization model, a representative collection of historical claims data where subrogation/no-subrogation decision was taken, based on the analysis. It also offers powerful machine learning for developing subrogation model, on-the fly prediction of claim, a broad selection of algorithms and simple integration with case management tools. Megaputer also delivers experienced assistance and consulting by its analysts.

The challenges involved in subrogation have incurred great losses to insurance industry. The subrogation opportunities comprised a small percentage of claims and the decisions taken for those claims involved manual analysis of textual notes which proved to be lengthy and costly. The subrogation prediction tool provided to the insurance companies enabled them to determine the probability of a subrogation opportunity and also estimate the recovery amount. “We minimized the waste of resources and missing subrogation opportunities by a greater percentage with the subrogation prediction tool,” says Ananyan.

With efficient analytics tools, the company has benefited leaders in the insurance industry like Allstate, Aetna, Liberty Mutual and much more. “Megaputer has a vision to become a leader in developing data and text mining software and helping customers convert complex analytic challenges into valuable business opportunities” concludes Anayan.