Artificial Intelligence Driven Fraud Detection Analytics | Python |
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Overview

The client’s data was not labelled as fraudulent or not. Proposed a solution that would take up information that were filed during the claiming process and then predict whether the claim was fraudulent or not.

Solution

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Initially the currently available mechanism, policies and regulations were studied.

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Data is analyzed to examine and check for abnormal data points and comprehend variables that may cause anomalies.

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Initially the duration between accident to the date of the report was analyzed.

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Driver specific analysis was performed where in the license class, the experience and vehicle restriction and then visualized

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The isolation Forest and SVM (Support Vector Machine) model was constructed to identify claims that stood apart as anomalous

Impact

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Ability to identify claims that stood out as an anomaly.

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Ability to identify the variables that cause abnormality

Technology

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