In the digital age, bank lending no longer relies solely on human intuition or traditional statistical methods. Faced with rising risks, increasingly complex financial behavior and an explosion of data, banks are entering a new era: that of artificial intelligence. Artificial Intelligence and Bank Credit Risk: Methods, Models and Applications explores in depth the transformation of banking decision-making systems thanks to Machine Learning. The book shows how financial institutions can use algorithms to better assess borrowers, reduce defaults and grant credit faster, more accurately and more fairly.The book begins by explaining the fundamentals of bank credit: why some applications are accepted, why others are rejected, and how notions of creditworthiness, risk and profitability structure financial decisions. It also highlights the real cost of bad credit: bank losses, bad debts, business failures and economic slowdown.
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MBENZA MAKIADI è un professionista congolese dell'IT specializzato in progettazione di sistemi informativi, amministrazione di rete, sviluppo di software e business intelligence. Con un profilo versatile, unisce solide competenze tecniche, una significativa esperienza accademica e un forte senso di responsabilità.
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Paperback. Zustand: new. Paperback. In the digital age, bank lending no longer relies solely on human intuition or traditional statistical methods. Faced with rising risks, increasingly complex financial behavior and an explosion of data, banks are entering a new era: that of artificial intelligence. Artificial Intelligence and Bank Credit Risk: Methods, Models and Applications explores in depth the transformation of banking decision-making systems thanks to Machine Learning. The book shows how financial institutions can use algorithms to better assess borrowers, reduce defaults and grant credit faster, more accurately and more fairly.The book begins by explaining the fundamentals of bank credit: why some applications are accepted, why others are rejected, and how notions of creditworthiness, risk and profitability structure financial decisions. It also highlights the real cost of bad credit: bank losses, bad debts, business failures and economic slowdown. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786630061451
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Taschenbuch. Zustand: Neu. Artificial Intelligence and Bank Credit Risk | Understanding, predicting and optimizing credit decisions in the age of Machine Learning | Oumar Armel Mbenza Makiadi | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786630061451 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 135407617
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Paperback. Zustand: new. Paperback. In the digital age, bank lending no longer relies solely on human intuition or traditional statistical methods. Faced with rising risks, increasingly complex financial behavior and an explosion of data, banks are entering a new era: that of artificial intelligence. Artificial Intelligence and Bank Credit Risk: Methods, Models and Applications explores in depth the transformation of banking decision-making systems thanks to Machine Learning. The book shows how financial institutions can use algorithms to better assess borrowers, reduce defaults and grant credit faster, more accurately and more fairly.The book begins by explaining the fundamentals of bank credit: why some applications are accepted, why others are rejected, and how notions of creditworthiness, risk and profitability structure financial decisions. It also highlights the real cost of bad credit: bank losses, bad debts, business failures and economic slowdown. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786630061451
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