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AI-Powered Solutions

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Pattern & Anomaly Detection

Machine learning and other cognitive approaches are used to identify patterns in the data and learn higher order connections between information that can provide insight into whether a given piece of data fits an existing pattern or is an outlier.

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Fraud Detection

Anomaly detection, a technology based on artificial intelligence, can detect unusual activity or anomalies in a data set captured. In most cases, these anomalies or irregularities can be turned into problems like fraud, errors, and design flaws. Anomaly detection will aid in the efficient detection of fraud and the discovery of suspicious behavior in large and complex Big Data sets. For example, by creating detailed risk profiles on clients and scoring them based on granular data, AI-Based Fraud Detection can assist banks and other financial institutions in preventing fraud and money laundering.


Risk Analysis

Anomaly details must be identified quickly to take effective steps for both risks and rewards in a timely and accurate manner. In AI-based risk analysis, anomaly detection entails identifying interest trends (deviations, idiosyncrasies, outliers, and so on) that differ from expected activity within a dataset. Decision makers who use these cognitive technologies to foresee and proactively manage risk can gain a competitive edge and use risk to propel their companies forward.


Intelligent Monitoring

End-to-end disparity-free tracking is used in anomaly detection systems to scrutinize data and find the tiniest anomalies that humans would miss. It is commonly referred to as intelligent monitoring. Intelligent Monitoring enables businesses to analyze raw data in order to improve decision-making, collaboration, and overall performance.

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