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Fraud Detection and Prevention by using Big Data Analytics

机译:使用大数据分析进行欺诈检测和预防

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A retail sector is a group of organization or people who sell goods or services for gaining income. Fraud is wrongful or criminal activities for the economic and personal benefits. Fraud detection is finding actual or expected fraud which takes place in an organization and in the retail market is one of the challenging aspects. Fraud is mischievous activities occur in retail sector includes shoplifting, skimming, replicating cards from skimmed data, counterfeiting, bar code or POS(Point-of-Sale) manipulation, contamination, mislabeling, substitute cheaper ingredients instead of high-quality ingredients. Fraudulent activities occur in the retail sector by both consumer and supplier. Analyzing financial crimes related to fraudulent activities is difficult where traditional data mining techniques fail to address all of them. Big data analytics is used to identify an unusual pattern to detect and prevent fraud in the retail sector. Various predictive analytics tools are used to handle massive data and their pattern.
机译:零售部门是为了获得收入而出售商品或服务的一组组织或人员。欺诈是为了经济和个人利益而进行的不法或犯罪活动。欺诈检测发现组织或零售市场中发生的实际或预期的欺诈是具有挑战性的方面之一。欺诈是在零售部门中进行的恶作剧活动,包括入店行窃,盗录,从盗录数据中复制卡,伪造,条形码或POS(销售点)操纵,污染,贴错标签,用便宜的原料代替高质量的原料。消费者和供应商在零售部门进行欺诈活动。传统的数据挖掘技术无法解决所有与欺诈活动有关的金融犯罪,因此很难进行分析。大数据分析可用于识别异常模式,以检测和防止零售行业中的欺诈行为。各种预测分析工具用于处理海量数据及其模式。

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