Data of problems in real world, fuzziness/impreciseness/absence appears due to various reasons very often. In such cases, difficulty in model building can be overcome by using fuzzy set theory and concepts. In this study, only situation of data lacking will be considered, Data envelopment analysis cannotbe used in the absence of one or more data in: model. If those absent datum or data can be supplied with possibilistic membership function, the problem is solved. In this study, a suggestion will be given about how to apply data envelopment analysis with the assistance of possibilistic membership function in real world problem with lacking data. Model problem has been chosen in the banking sector, which is a very popular area.