S. Abdullahi, Nazir Yusuf, M. A. Zayyad, Lawal Idris Bagiwa, A. Zakari, Alhassan Adamu, Amina Nura, Saadana Shehu
{"title":"The Big Data Technology: Assessing the Impact in the Banking Industry","authors":"S. Abdullahi, Nazir Yusuf, M. A. Zayyad, Lawal Idris Bagiwa, A. Zakari, Alhassan Adamu, Amina Nura, Saadana Shehu","doi":"10.31580/OJST.V3I2.1464","DOIUrl":null,"url":null,"abstract":"Big data is a form of data with increased volume, difficult to analyze, process, and store using traditional database technologies. It has long been adopted in business and finance where a large number of bank transaction are executed daily. The emergence of big data in banking industry results to large proportion of technical improvements in the industry. However, its processing causes disruption in the banking industry. Big data analytics is the process that involves using algorithms and software tools to extract useful business information from the dataset. This study adopts big data analytics process to investigates the disruption due to big data processing in the banking industry. The study identifies, acquired, and extracted dataset of the banking industry which was analyzed using MapReduce based fraud committed due to processing of large amount of data. findings show that government employee commit more crime in comparison with the private sector employees. Finally, based on customers gender, the male employees commit most of the fraud in both government and private sector.","PeriodicalId":19674,"journal":{"name":"Open Access Journal of Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Access Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31580/OJST.V3I2.1464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Big data is a form of data with increased volume, difficult to analyze, process, and store using traditional database technologies. It has long been adopted in business and finance where a large number of bank transaction are executed daily. The emergence of big data in banking industry results to large proportion of technical improvements in the industry. However, its processing causes disruption in the banking industry. Big data analytics is the process that involves using algorithms and software tools to extract useful business information from the dataset. This study adopts big data analytics process to investigates the disruption due to big data processing in the banking industry. The study identifies, acquired, and extracted dataset of the banking industry which was analyzed using MapReduce based fraud committed due to processing of large amount of data. findings show that government employee commit more crime in comparison with the private sector employees. Finally, based on customers gender, the male employees commit most of the fraud in both government and private sector.