Statistical Data Analytics

Our team of Data Analytics specialists capture, consolidate and interrogate massive volumes of structured and unstructured data. We provide cutting edge, data-driven expertise in support of complex business issues, allowing our clients to make informed, strategic decisions.

Our Data Analytics specialists focus upon the application of analytical techniques to detect and prevent fraud and abuse. The team engages in unlocking actionable insights from large volumes of complex transactional data. We apply data management and data mining methodologies and software to solve complex business challenges for our clients.

Detecting and preventing fraud is difficult, because there is no simple, precise, and fast algorithm that correctly identifies all cases of fraud. Fraud is an adaptive crime, so it needs special methods of data analysis to detect and prevent it.

To uncover fraudulent and abusive behavior, investigators must sort through millions of records to find suspicious behavior. Our advanced statistical analysis capabilities greatly improve your ability to proactively detect and prevent fraud:

  • Spatial Analysis for Fraud Detection: provides a new dimension for applying outlier analysis to detect fraudulent behavior. By linking records with geographic measures and demographics, investigators can quickly identify outliers based upon population demographics.

  • Abnormal and Outlier Analysis: Identification of abnormal behavior typically requires investigators to undergo painstaking evaluation of comparative measures.

  • Predictive Modeling for Fraud: Automating the identification trends that signify fraud allows payers to not only find existing fraud schemes, but also provides a new tool to evaluate the likelihood of fraud. As opposed to business-rule type evaluations, predictive analytics can identify new trends that are characteristic of fraud.