BOOKS - Artificial Intelligence for Risk Mitigation in the Financial Industry
Artificial Intelligence for Risk Mitigation in the Financial Industry - Ambrish Kumar Mishra, Shweta Anand, Narayan C. Debnath 2024 EPUB Wiley-Scrivener BOOKS
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Artificial Intelligence for Risk Mitigation in the Financial Industry
Author: Ambrish Kumar Mishra, Shweta Anand, Narayan C. Debnath
Year: 2024
Pages: 384
Format: EPUB
File size: 10.8 MB
Language: ENG



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The book "Artificial Intelligence for Risk Mitigation in the Financial Industry" discusses how artificial intelligence (AI) can be used to identify and mitigate risks in the financial industry. It covers topics such as machine learning, natural language processing, and computer vision, and their applications in finance. The book also explores the challenges and limitations of AI in risk management and provides case studies of successful AI implementation in the financial sector. The book begins by explaining the concept of risk and its importance in the financial industry. It then delves into the history of AI and its development over time, highlighting key milestones and breakthroughs that have led to the current state of the technology. This section sets the stage for understanding the potential of AI in risk mitigation. Next, the book examines the various types of risks faced by financial institutions, including credit risk, market risk, operational risk, and compliance risk. It explains how AI can help identify and manage these risks through predictive modeling, anomaly detection, and other techniques. The book then delves into the technical aspects of AI, including machine learning algorithms, neural networks, and deep learning.
В книге «Искусственный интеллект для снижения рисков в финансовой отрасли» обсуждается, как искусственный интеллект (ИИ) может использоваться для выявления и снижения рисков в финансовой отрасли. Он охватывает такие темы, как машинное обучение, обработка естественного языка и компьютерное зрение, а также их применение в финансах. В книге также рассматриваются проблемы и ограничения ИИ в управлении рисками и приводятся тематические исследования успешного внедрения ИИ в финансовом секторе. Книга начинается с объяснения понятия риска и его важности в финансовой отрасли. Затем он углубляется в историю ИИ и его развития с течением времени, выделяя ключевые вехи и прорывы, которые привели к нынешнему состоянию технологии. Этот раздел закладывает основу для понимания потенциала ИИ в снижении рисков. Далее в книге рассматриваются различные типы рисков, с которыми сталкиваются финансовые учреждения, включая кредитный риск, рыночный риск, операционный риск и риск соответствия. В нем объясняется, как ИИ может помочь выявить и управлять этими рисками с помощью прогностического моделирования, обнаружения аномалий и других методов. Затем книга углубляется в технические аспекты ИИ, включая алгоритмы машинного обучения, нейронные сети и глубокое обучение.
livre « L'intelligence artificielle pour réduire les risques dans le secteur financier » explique comment l'intelligence artificielle (IA) peut être utilisée pour identifier et atténuer les risques dans le secteur financier. Il couvre des sujets tels que l'apprentissage automatique, le traitement du langage naturel et la vision par ordinateur, ainsi que leur application dans la finance. livre examine également les défis et les limites de l'IA dans la gestion des risques et présente des études de cas sur la mise en œuvre réussie de l'IA dans le secteur financier. livre commence par expliquer la notion de risque et son importance dans l'industrie financière. Il se penche ensuite sur l'histoire de l'IA et de son développement au fil du temps, mettant en évidence les étapes clés et les percées qui ont conduit à l'état actuel de la technologie. Cette section jette les bases de la compréhension de la capacité de l'IA à réduire les risques. livre examine ensuite les différents types de risques auxquels sont exposées les institutions financières, notamment le risque de crédit, le risque de marché, le risque opérationnel et le risque de conformité. Il explique comment l'IA peut aider à identifier et gérer ces risques par la modélisation prédictive, la détection des anomalies et d'autres méthodes. livre explore ensuite les aspects techniques de l'IA, y compris les algorithmes d'apprentissage automatique, les réseaux neuronaux et l'apprentissage profond.
libro «Inteligencia Artificial para Reducir los Riesgos en la Industria Financiera» discute cómo la inteligencia artificial (IA) puede ser utilizada para identificar y reducir los riesgos en la industria financiera. Abarca temas como el aprendizaje automático, el procesamiento del lenguaje natural y la visión por computadora, así como su aplicación en las finanzas. libro también aborda los desafíos y limitaciones de la IA en la gestión de riesgos y proporciona estudios de casos sobre la implementación exitosa de la IA en el sector financiero. libro comienza explicando el concepto de riesgo y su importancia en la industria financiera. A continuación, profundiza en la historia de la IA y su desarrollo a lo largo del tiempo, destacando los hitos y avances clave que han llevado al estado actual de la tecnología. Esta sección sienta las bases para comprender el potencial de la IA para reducir los riesgos. A continuación, el libro examina los diferentes tipos de riesgos a los que se enfrentan las entidades financieras, incluidos el riesgo de crédito, el riesgo de mercado, el riesgo operativo y el riesgo de conformidad. Explica cómo la IA puede ayudar a identificar y gestionar estos riesgos a través de simulaciones predictivas, detección de anomalías y otros métodos. Luego, el libro profundiza en los aspectos técnicos de la IA, incluyendo algoritmos de aprendizaje automático, redes neuronales y aprendizaje profundo.
Nel libro «Intelligenza artificiale per la riduzione dei rischi nel settore finanziario» si discute come l'intelligenza artificiale (IA) possa essere utilizzata per identificare e ridurre i rischi nel settore finanziario. occupa di argomenti quali l'apprendimento automatico, l'elaborazione del linguaggio naturale e la visione informatica e la loro applicazione nella finanza. Il libro descrive anche i problemi e le limitazioni dell'IA nella gestione dei rischi e fornisce studi di caso sul successo dell'implementazione dell'IA nel settore finanziario. Il libro inizia spiegando il concetto di rischio e la sua importanza nel settore finanziario. Poi si approfondisce nella storia dell'IA e del suo sviluppo nel tempo, evidenziando le fasi cardine e le innovazioni che hanno portato allo stato attuale della tecnologia. Questa sezione fornisce le basi per comprendere il potenziale dell'IA nella riduzione dei rischi. Il libro descrive i diversi tipi di rischi che le istituzioni finanziarie devono affrontare, tra cui il rischio di credito, il rischio di mercato, il rischio operativo e il rischio di conformità. Spiega come l'IA può aiutare a identificare e gestire questi rischi attraverso simulazioni predittive, rilevamento di anomalie e altri metodi. Poi il libro approfondisce gli aspetti tecnici dell'IA, inclusi gli algoritmi di apprendimento automatico, le reti neurali e l'apprendimento approfondito.
Das Buch „Künstliche Intelligenz zur Risikominderung in der Finanzindustrie“ diskutiert, wie Künstliche Intelligenz (KI) eingesetzt werden kann, um Risiken in der Finanzindustrie zu erkennen und zu reduzieren. Es umfasst Themen wie maschinelles rnen, natürliche Sprachverarbeitung und Computer Vision sowie deren Anwendung im Finanzwesen. Das Buch befasst sich auch mit den Herausforderungen und Grenzen von KI im Risikomanagement und liefert Fallstudien zur erfolgreichen Umsetzung von KI im Finanzsektor. Das Buch beginnt mit einer Erläuterung des Risikobegriffs und seiner Bedeutung in der Finanzbranche. Es geht dann tiefer in die Geschichte der KI und ihrer Entwicklung im Laufe der Zeit und hebt die wichtigsten Meilensteine und Durchbrüche hervor, die zum aktuellen Stand der Technologie geführt haben. Dieser Abschnitt legt den Grundstein für das Verständnis des Potenzials von KI bei der Risikominderung. Das Buch befasst sich weiter mit den verschiedenen Arten von Risiken, denen Finanzinstitute ausgesetzt sind, einschließlich Kreditrisiko, Marktrisiko, Betriebsrisiko und Compliance-Risiko. Es erklärt, wie KI helfen kann, diese Risiken durch prädiktive Modellierung, Anomalieerkennung und andere Techniken zu identifizieren und zu verwalten. Das Buch befasst sich dann mit technischen Aspekten der KI, einschließlich Algorithmen für maschinelles rnen, neuronale Netze und Deep arning.
הספר ”בינה מלאכותית למיתון סיכונים בתעשייה הפיננסית” (Artificial Intelligence to Metheate Schances in the Financial Industry) דן בשאלה כיצד ניתן להשתמש בבינה מלאכותית כדי לזהות ולמתן סיכונים בתעשייה הפיננסית. הוא מכסה נושאים כמו לימוד מכונה, עיבוד שפה טבעית וראייה ממוחשבת, ויישומם למימון. הספר בוחן גם את האתגרים והמגבלות של בינה מלאכותית בניהול סיכונים ומספק מחקר מקרה של אימוץ בינה מלאכותית מוצלח במגזר הפיננסי. הספר מתחיל בהסברת רעיון הסיכון וחשיבותו בתעשייה הפיננסית. לאחר מכן הוא מתעמק בהיסטוריה של הבינה המלאכותית והתפתחותה לאורך זמן, מדגיש אבני דרך ופריצות דרך שהובילו למצב הנוכחי של הטכנולוגיה. סעיף זה מניח את היסודות להבנת הפוטנציאל של בינה מלאכותית בהפחתת סיכונים. הספר ממשיך ומתייחס לסוגי הסיכונים השונים שעומדים בפני מוסדות פיננסיים, לרבות סיכון אשראי, סיכון שוק, סיכון תפעולי וסיכון ציות. הוא מסביר כיצד בינה מלאכותית יכולה לסייע בזיהוי וניהול סיכונים אלה באמצעות דוגמנות חיזוי, גילוי אנומליה ושיטות אחרות. הספר מתעמק בהיבטים הטכניים של בינה מלאכותית, כולל אלגוריתמים ללימוד מכונה, רשתות עצביות ולמידה עמוקה.''
"Finansal Sektördeki Riskleri Azaltmak için Yapay Zeka" kitabı, finansal sektördeki riskleri tanımlamak ve azaltmak için yapay zekanın (AI) nasıl kullanılabileceğini tartışıyor. Makine öğrenimi, doğal dil işleme ve bilgisayar görüşü gibi konuları ve bunların finansmana uygulanmasını kapsar. Kitap ayrıca risk yönetiminde AI'nın zorluklarını ve sınırlamalarını incelemekte ve finansal sektörde başarılı AI'nın benimsenmesine ilişkin vaka çalışmaları sunmaktadır. Kitap, risk kavramını ve finansal sektördeki önemini açıklayarak başlıyor. Daha sonra, AI'nın tarihini ve zaman içindeki gelişimini inceleyerek, teknolojinin mevcut durumuna yol açan önemli kilometre taşlarını ve atılımlarını vurgular. Bu bölüm, AI'nın risk azaltma potansiyelini anlamak için temel oluşturmaktadır. Kitap, finansal kurumların kredi riski, piyasa riski, operasyonel risk ve uyum riski de dahil olmak üzere karşılaştıkları farklı risk türlerini ele almaya devam ediyor. AI'nın bu riskleri öngörücü modelleme, anomali tespiti ve diğer yöntemlerle tanımlamaya ve yönetmeye nasıl yardımcı olabileceğini açıklar. Kitap daha sonra makine öğrenme algoritmaları, sinir ağları ve derin öğrenme dahil olmak üzere AI'nın teknik yönlerini inceliyor.
يناقش كتاب «الذكاء الاصطناعي للتخفيف من المخاطر في الصناعة المالية» كيفية استخدام الذكاء الاصطناعي (AI) لتحديد المخاطر في الصناعة المالية والتخفيف منها. يغطي موضوعات مثل التعلم الآلي ومعالجة اللغة الطبيعية ورؤية الكمبيوتر، بالإضافة إلى تطبيقها على التمويل. يبحث الكتاب أيضًا في تحديات وقيود الذكاء الاصطناعي في إدارة المخاطر ويقدم دراسات حالة عن نجاح اعتماد الذكاء الاصطناعي في القطاع المالي. يبدأ الكتاب بشرح مفهوم المخاطر وأهميتها في الصناعة المالية. ثم يتعمق في تاريخ الذكاء الاصطناعي وتطوره بمرور الوقت، ويسلط الضوء على المعالم الرئيسية والاختراقات التي أدت إلى الوضع الحالي للتكنولوجيا. يضع هذا القسم الأساس لفهم إمكانات الذكاء الاصطناعي في التخفيف من المخاطر. يستمر الكتاب في معالجة الأنواع المختلفة من المخاطر التي تواجهها المؤسسات المالية، بما في ذلك مخاطر الائتمان ومخاطر السوق والمخاطر التشغيلية ومخاطر الامتثال. يشرح كيف يمكن للذكاء الاصطناعي المساعدة في تحديد وإدارة هذه المخاطر من خلال النمذجة التنبؤية واكتشاف الشذوذ وطرق أخرى. ثم يتعمق الكتاب في الجوانب التقنية للذكاء الاصطناعي، بما في ذلك خوارزميات التعلم الآلي والشبكات العصبية والتعلم العميق.
「人工智能降低金融業風險」一書討論了如何利用人工智能(AI)來識別和減輕金融業的風險。它涵蓋了機器學習,自然語言處理和計算機視覺及其在金融中的應用等主題。該書還探討了AI在風險管理中的挑戰和局限性,並提供了成功在金融部門實施AI的案例研究。這本書首先解釋了風險的概念及其在金融業中的重要性。然後,他深入研究了AI的歷史及其隨著時間的推移的發展,突出了導致該技術當前狀態的關鍵裏程碑和突破。本節為了解人工智能在降低風險方面的潛力奠定了基礎。該書進一步探討了金融機構面臨的不同類型的風險,包括信用風險,市場風險,運營風險和合規風險。它解釋了AI如何通過預測建模,異常檢測和其他方法幫助識別和管理這些風險。然後,該書深入研究AI的技術方面,包括機器學習算法,神經網絡和深度學習。

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