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METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR APPLYING DEEP LEARNING ANALYSIS TO FINANCIAL DEVICE USAGE

机译:将深度学习分析应用于金融设备使用的方法,系统和计算机程序产品

摘要

Described are a system, method, and computer program product for applying deep learning analysis to predict and automatically respond to predicted changes in financial device primacy for a financial device holder. The method includes receiving transaction data representative of a plurality of transactions between the financial device holder and a merchant. The method also includes generating time series data based on the transaction data and generating a predictive model configured to: (i) receive an input of time-interval-based transaction data; and (ii) output a probability of primary financial device primacy change, the predictive model trained based on historic transaction data. The method further includes determining a probability of primary financial device primacy change for the financial device holder by applying the predictive model to the time series data. The method further includes, generating at least one communication to at least one issuer and/or the financial device holder.
机译:描述了一种系统,方法和计算机程序产品,用于应用深度学习分析来预测并自动响应金融设备持有者的金融设备优先级的预测变化。该方法包括接收代表金融设备持有人和商人之间的多个交易的交易数据。该方法还包括:基于交易数据生成时间序列数据;以及生成配置为:(i)接收基于时间间隔的交易数据的输入的预测模型;以及(ii)输出主要金融设备优先权发生变化的概率,该预测模型基于历史交易数据进行了训练。该方法还包括通过将预测模型应用于时间序列数据来确定金融设备持有者的主要金融设备优先权改变的概率。该方法还包括:生成与至少一个发行者和/或金融设备持有者的至少一种通信。

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