By Sirikulvadhana S.
The target of this thesis is to figure out if info mining instruments can directlyimprove audit functionality. the chosen attempt quarter used to be the pattern choice step of thetest of keep an eye on method. The study info was once according to accounting transactionsprovided via AVH PricewaterhouseCoopers Oy. a variety of samples have been extracted fromthe attempt information set utilizing info mining software program and generalized audit software program and theresults evaluated. IBM's DB2 clever Miner for facts model 6 was once chosen torepresent the information mining software program and ACL for home windows Workbook model five waschosen for generalized audit software.Based at the result of the try and the critiques solicited from experiencedauditors, the belief is that, in the scope of this study, the result of datamining software program are extra attention-grabbing than the result of generalized audit software.However, there isn't any proof that the knowledge mining process brings out materialmatters or current major enhancement over the generalized audit software program. Furtherstudy in a special audit quarter or with a extra entire information set may perhaps yield a differentconclusion.
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Extra resources for Data Mining As A Financial Auditing Tool
If not, at least transaction date has to be identified. - Document Number -- refers to source or supporting documents. - Description -- or explanation of each journal. - Account Number - Amount -- normally the debit amount has positive value while credit amount has negative value. - Responsible Person -- or person who prepares or keys in the transaction. - Authorized Person -- some transactions with certain characteristics may require approval. - Other Additional Information -- such as profit center, customer group, currency and spot exchange rate.
Scalability of the model is the major concern in this phase. 3: A decision tree classifying transactions into five groups The fundamental algorithms can be different in each model. Probably the most popular ones are Classification and Regression Trees (CART) and Chi-Square Automatic Interaction Detector (CHAID). For the sake of simplicity, I will not go into the details of these algorithms and only perspectives of them are provided. CART is an algorithm developed by Leo Breiman, Jerome Friedman, Richard Olshen and Charles Stone.
1. Among all underlying algorithms of these methods, Apriori algorithms, decision trees and neural networks are the most familiar ones. 1: Summarization of appropriate data mining techniques of each data mining method (Continued) Data mining already has its market in customer relationship management as well as fraud detection and is expected to penetrate new areas in the near future. However, data mining software packages that are currently available have been criticized for not automated enough and not user-friendly enough.