01537nas a2200145   4500008004100000245007400041210006900115260002000184300001200204490000700216520107800223100002201301700002101323856004701344       2020                        eng d00aData Mining Applications for Banks’ Business Intelligence Maturity-0 aData Mining Applications for Banks Business Intelligence Maturit  c10/2020,12/2020  a153-1720 v183 a<p><span style="color: rgb(51, 51, 51); font-family: Arial, Helvetica, sans-serif;">There are many researches that applied data mining in banking. However, one may be countered the lack of suitable data as a serious obstacle to employ data mining techniques for the banks. This paper examines previous data mining researches carried out for banking, integrates them, extracts all served entities and attributes which are needed for analytical purposes, categorizes them and ultimately presents a suitable data model for analytical purpose. After analysis of a wide range of data mining application in banking, 28 entities with 423 attributes were identified in conclusion and the final proposed entity-relationship diagram was created. Also a checklist was provided based on the model for auditing data gap in banks and applied in a real case. The results of this paper can be regarded as a supportive tool for increasing banksâ€™ business intelligence maturity from the data perspective and enable managers in requirement analysis of information systems.</span></p>
1 aRanjbarfard, Mina1 aAhmadi, Shahideh  uhttp://www.dline.info/download.php?sn=3103