Organizations have been reactive in using analytics to detect exceptions / fraudulent transactions after the occurrence of events, resulting in huge cost and effort towards recovery and remediation measures.
Social Analytics proactively assists knowledge workers / users in forming realistic opinion about the case-under-evaluation by detecting all the anomalies, by considering all the available cues and by recommending the next best possible course of action to achieve the desired result. It seamlessly aggregates all the relevant case-related information from multiple disparate sources, thus supporting user decisions. Information accumulation & enrichment, Flags, comprehensive risk scores and proactive alerts are some of the features that make Social Analytics, the most pragmatic decision-support design.
- Instantly detect anomalies
- Built-in decision analysis to identify most effective actions to reach desired result
- Intelligent risk score giving a comprehensive picture about the party / case under evaluation
- Models that predict possibilities for anomalies / exceptions at a case-level
- Next-gen dashboard offering highest level of customization at user and case level, aiding in quick research
Applications / Use Cases
- Healthcare Proactive claims analysis to detect frauds and overpayments resulting in minimization of recovery costs
- Financial Services Effective early warning towards managing of Non-performing assets (NPAs) and minimize fraudulent financial transactions
- Insurance Analysis of huge data, helps agencies measure and monitor their performance, improve policy making and service delivery
- Government Claims analytics platform to help property and casualty insurers optimize fraud detection and help improve ROI in fighting fraud