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題名：視覺化虛設行號逃漏稅預警機制建置之探討
作者：許志誠
作者(外文)：Chih-Cheng Hsu
校院名稱：元智大學
系所名稱：管理學院博士班
指導教授：鄭雅穗
學位類別：博士
出版日期：2014
主題關鍵詞：虛設行號；逃漏稅；商業智慧；資料探勘；知識管理；Tax Evasion；Bogus Business Entities；Visualized Data Mining；Business Intelligence；Knowledge Management
原始連結：連回原系統網址new window
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虛設行號之困擾存在已久，這類型不法企業之營業人開立發票供他人作為進貨或費用憑證，此行為與發票憑證影響我國正常稅務課徵之機制與公平性。政府稅務相關單位為此投入人力與資源，目的在於能夠早期發現虛設行號進而有效抑止。然而稅務人員面對數量繁多的申報資料，以及稅務任務多元化的實際狀況下，經驗傳承與選案效率都是查核困難原因。
本研究之目的在於協助稅務單位有效管理與分享查核虛設行號之知識，進而能夠給予有效的預警資訊。我們運用資訊科技與資料科學分析技術，建置視覺化虛設行號預警機制，運用DMAIC方法論建構整體知識發掘流程，依據知識管理與分享本體論定義，以KNIME作為視覺化預警機制建置之呈現。
在執行虛設行號資料來源之資料蒐集與轉置後，我們進行三個研究主題，包括虛設行號負責人特徵、虛設行號申報營業稅特徵、虛設行號與正常企業申報資料之比較。研究過程中我們歸納出虛設行號可能存在的兩個面項特徵，亦即企業在申報營業稅時基於進銷平衡與營運槓桿等。在各流程中我們均依據知識管理與分享本體論建置，並進行視覺化呈現與操作，可快速有效產出相關報告，協助相關單位進行虛設行號逃漏稅主動稽查之決策依據。
我們所建立之虛設行號逃漏稅預警機制之資料庫與分析模式庫具有無限擴充特性，可依使用者經驗、新開發資料探勘技術與分析改善後之結果回饋執行，持續強化決策正確性。除營業稅與虛設行號資料外，仍可套用於其他財稅相關資料、專家經驗與必要之外部資料等，建置符合該類型逃漏稅預警機制。
We aimed to apply visualized data mining technique to establish a mechanism for bogus entity detection. In the past research, we collected datasets related to a large bogus entities group and their tax records, analyzing and extracting characteristics of crime. In this project, relevant datasets from large databases of 8 different systems at the Fiscal Information Agency will be integrated, examined, and extracted for tax evasion pattern recognition and for prior/ex crime behavior analysis.
Based on DMAIC (Define, Measure, Analyze, Improve, and Control), we expect to build up a detection mechanism, to define its ontology, including data, models, parameters and results, with visualized data mining technique. We also expect to discuss open data issues, such as its possible applications, legal and safety, data management, planning for data mining and data analysis, as well as the possible social impact.
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