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Data Quality Assessment in Credit Risk Management in Banks: Design, Application and Evaluation - Tapa blanda

Güneş, Muhammed İlyas

 
9783659822049: Data Quality Assessment in Credit Risk Management in Banks: Design, Application and Evaluation
Tapa blanda
ISBN 10: 3659822043 ISBN 13: 9783659822049
Editorial: LAP LAMBERT Academic Publishing, 2017

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

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.

Biografía del autor

The 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 specialist in Banking Regulation and Supervision Agency in Turkey. His study subjects are risk management, finance and information systems.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2017
Idioma
Inglés
ISBN 10 
3659822043
ISBN 13 
9783659822049
Encuadernación
Tapa blanda
Número de páginas
152
Contacto del fabricante
no disponible
Persona responsable
no disponible