Tech Corner

Fraud Detection in Online Banking Data

Digital banking fraud resulted in a total financial loss of R284.2m in 2019, an 8% increase from 2018 [1]. The ability to detect fraud rapidly helps to prevent financial losses from occurring and maintain customer relationships between the banking institutions and their respective clients. In this article we are going to share our insights from an investigation where we used a Hidden Markov Model to classify whether an online banking session is fraudulent based on the posterior probability.

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Smart Mining & Manufacturing: Anomaly Detection and localisation using Variational Autoencoder (VAE)

In this post we will show how you can detect as well as localise the defect using a Deep Neural Network (DNN), specifically a Variational Autoencoder (VAE). This workflow can be useful in instances where the process of correction is dependent on the type of defect identified.

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