AI powered risk assessment company
Anomaly detection in financial data
Problem
The client aimed to enhance their internal audit software by improving its anomaly detection capabilities for financial transactions recorded in the general ledger and accounts payable data.
Solution
An ensemble of AI models was developed, combining various supervised and unsupervised learning techniques to effectively identify anomalies within complex financial datasets.
Outcome
The AI-powered solution significantly improved the accuracy of anomaly detection, enabling the client to identify irregularities with greater precision and efficiency.
Leveraging Advanced Machine Learning to enhance anomaly detection
The client, a provider of AI-powered internal audit software, sought to enhance its anomaly detection capabilities for financial transactions recorded in general ledger and accounts payable data. To achieve this, an ensemble of machine learning models was developed using a combination of unsupervised and supervised techniques. These models were integrated into the software and deployed.
The enhanced models delivered a significant improvement in anomaly detection, achieving an accuracy of over 93% within eight months of deployment.
Accuracy amplified
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