As the size and complexity of banks grow, the amount of data that their information systems need to handle also increases. This leads to the emergence of a variety of data quality (DQ) problems. Due to the possible economic losses due to such DQ issues, banks need to assure quality of their data via data quality assessment (DQA) techniques. This study presents a distinctive approach for data quality assessment in credit risk management. This approach grounds the selection of DQ dimensions on identification of data taxonomies for credit risk. Identification of data taxonomies with determination of data entities and attributes, followed by the development of DQ metrics based on the DQ dimension. DQ metrics are transformed into quality performance indicators in order to assess quality of credit risk data by means of DQA methods. Analysis of the results of DQA reveals the underlying causes of poor DQ performance. Identification of DQ problems and their major causes is followed by suggestion of appropriate improvement techniques based on the size, complexity and criticality of the problems in the context of credit risk management.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As the size and complexity of banks grow, the amount of data that their information systems need to handle also increases. This leads to the emergence of a variety of data quality (DQ) problems. Due to the possible economic losses due to such DQ issues, banks need to assure quality of their data via data quality assessment (DQA) techniques. This study presents a distinctive approach for data quality assessment in credit risk management. This approach grounds the selection of DQ dimensions on identification of data taxonomies for credit risk. Identification of data taxonomies with determination of data entities and attributes, followed by the development of DQ metrics based on the DQ dimension. DQ metrics are transformed into quality performance indicators in order to assess quality of credit risk data by means of DQA methods. Analysis of the results of DQA reveals the underlying causes of poor DQ performance. Identification of DQ problems and their major causes is followed by suggestion of appropriate improvement techniques based on the size, complexity and criticality of the problems in the context of credit risk management. 152 pp. Englisch. Codice articolo 9783659822049
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Guenes Muhammed IlyasThe writer graduated from Industrial Engineering Department in Middle East Technical University (METU). He achieved his M.Sc. Degree at Information Systems program in METU. He is currently working as a banking spe. Codice articolo 158124498
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As the size and complexity of banks grow, the amount of data that their information systems need to handle also increases. This leads to the emergence of a variety of data quality (DQ) problems. Due to the possible economic losses due to such DQ issues, banks need to assure quality of their data via data quality assessment (DQA) techniques. This study presents a distinctive approach for data quality assessment in credit risk management. This approach grounds the selection of DQ dimensions on identification of data taxonomies for credit risk. Identification of data taxonomies with determination of data entities and attributes, followed by the development of DQ metrics based on the DQ dimension. DQ metrics are transformed into quality performance indicators in order to assess quality of credit risk data by means of DQA methods. Analysis of the results of DQA reveals the underlying causes of poor DQ performance. Identification of DQ problems and their major causes is followed by suggestion of appropriate improvement techniques based on the size, complexity and criticality of the problems in the context of credit risk management. Codice articolo 9783659822049
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As the size and complexity of banks grow, the amount of data that their information systems need to handle also increases. This leads to the emergence of a variety of data quality (DQ) problems. Due to the possible economic losses due to such DQ issues, banks need to assure quality of their data via data quality assessment (DQA) techniques. This study presents a distinctive approach for data quality assessment in credit risk management. This approach grounds the selection of DQ dimensions on identification of data taxonomies for credit risk. Identification of data taxonomies with determination of data entities and attributes, followed by the development of DQ metrics based on the DQ dimension. DQ metrics are transformed into quality performance indicators in order to assess quality of credit risk data by means of DQA methods. Analysis of the results of DQA reveals the underlying causes of poor DQ performance. Identification of DQ problems and their major causes is followed by suggestion of appropriate improvement techniques based on the size, complexity and criticality of the problems in the context of credit risk management.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch. Codice articolo 9783659822049
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Data Quality Assessment in Credit Risk Management in Banks | Design, Application and Evaluation | Muhammed ¿lyas Güne¿ | Taschenbuch | 152 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783659822049 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 108496930
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Da: Mispah books, Redhill, SURRE, Regno Unito
paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA82936598220436
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