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Neural Network Host Platform for Generating Automated Suspicious Activity Reports Using Machine Learning

机译:用于使用机器学习生成自动可疑活动报告的神经网络主机平台

摘要

Aspects of the disclosure relate to using machine learning techniques for generating automated suspicious activity reports (SAR). A computing platform may generate a labelled transaction history dataset by combining historical transaction data with historical report information. The computing platform may train a convolutional neural network using the labelled transaction history dataset. The computing platform may receive new transaction data and compress the new transaction data using lossy compression. The computing platform may input the compressed transaction data into the convolutional neural network, which may cause the convolutional neural network to output a suspicious event probability score based on the compressed transaction data. The computing platform may determine whether the suspicious event probability score exceeds a predetermined threshold and, if so, the computing platform may send one or more commands directing a report processing system to generate a SAR, which may cause the report processing system to generate the SAR.
机译:本公开的各方面涉及使用用于生成自动可疑活动报告(SAR)的机器学习技术。计算平台可以通过将历史事务数据与历史报告信息组合来生成标记的事务历史数据集。计算平台可以使用标记的交易历史数据集训练卷积神经网络。计算平台可以使用有损压缩接收新的交易数据并压缩新的交易数据。计算平台可以将压缩的交易数据输入到卷积神经网络中,这可能导致卷积神经网络基于压缩事务数据输出可疑事件概率分数。计算平台可以确定可疑事件概率得分是否超过预定阈值,并且如果是,计算平台可以发送指示报告处理系统生成SAR的一个或多个命令,这可能导致报告处理系统生成SAR 。

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