國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Transforming financial services with...

Godavarthi, Srinath.

Transforming financial services with Generative AIfrom strategy and design to practical applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Transforming financial services with Generative AIby Srinath Godavarthi, Ravi Nagvekar.
其他題名:	from strategy and design to practical applications /
作者:	Godavarthi, Srinath.
其他作者:	Nagvekar, Ravi.
出版者:	Berkeley, CA :Apress :2025.
面頁冊數:	xxv, 325 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligenceFinancial applications.
電子資源:	https://doi.org/10.1007/979-8-8688-2053-3
ISBN:	9798868820533$q(electronic bk.)

Transforming financial services with Generative AIfrom strategy and design to practical applications /
Godavarthi, Srinath.

Transforming financial services with Generative AIfrom strategy and design to practical applications /[electronic resource] :by Srinath Godavarthi, Ravi Nagvekar. - Berkeley, CA :Apress :2025. - xxv, 325 p. :ill., digital ;24 cm.

Chapter 1: Introduction to Generative AI -- Chapter 2: GenAI and the Financial Services Sector -- Chapter 3: GenAI Strategy: A Blueprint for Successful Adoption -- Chapter 4: Architecting and Building a GenAI Application -- Chapter 5: Risk and Compliance Managment with GenAI -- Chapter 6: Retail Banking with GenAI -- Chapter 7: Investment Banking with GenAI -- Chapter 8: Wealth and Asset Management wth GenAI -- Chapter 9: Implementation, Operations, and Maintenance of GenAI Applications -- Chapter 10: Summary, Emerging Trends, Summary, and Next Steps.

Generative AI (GenAI) is revolutionizing the financial services sector (FSS), offering new ways to enhance efficiency, improve customer experiences, and streamline operations. This book is your comprehensive guide to understanding and implementing GenAI within FSS. Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You'll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You'll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture-through the lens of executives tasked with delivering measurable value responsibly. From there, you'll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You'll see how these capabilities power mission-critical functions across the enterprise: Finally, you'll operationalize all of it with modern FMOps/LLMOps practices-security, privacy, performance, cost management, monitoring, and continuous improvement-so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment. Whether you're a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade. What You Will Learn Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment.

ISBN: 9798868820533$q(electronic bk.)

Standard No.: 10.1007/979-8-8688-2053-3doiSubjects--Topical Terms:

890884
Artificial intelligence
--Financial applications.

LC Class. No.: HG4515.5

Dewey Class. No.: 332.640285

Transforming financial services with Generative AIfrom strategy and design to practical applications /
LDR:04044nmm a2200325 a 4500 001 692042
003 DE-He213
005 20260102122852.0
006 m d
007 cr nn 008maaau
008 260527s2025 cau s 0 eng d
020 $a 9798868820533$q(electronic bk.)
020 $a 9798868820526$q(paper)
024 7 $a 10.1007/979-8-8688-2053-3 $2 doi
035 $a 979-8-8688-2053-3
040 $a GP $c GP
041 0 $a eng
050 4 $a HG4515.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 332.640285 $2 23
090 $a HG4515.5 $b .G577 2025
100 1 $a Godavarthi, Srinath. $3 980190
245 1 0 $a Transforming financial services with Generative AI $h [electronic resource] : $b from strategy and design to practical applications / $c by Srinath Godavarthi, Ravi Nagvekar.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2025.
300 $a xxv, 325 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction to Generative AI -- Chapter 2: GenAI and the Financial Services Sector -- Chapter 3: GenAI Strategy: A Blueprint for Successful Adoption -- Chapter 4: Architecting and Building a GenAI Application -- Chapter 5: Risk and Compliance Managment with GenAI -- Chapter 6: Retail Banking with GenAI -- Chapter 7: Investment Banking with GenAI -- Chapter 8: Wealth and Asset Management wth GenAI -- Chapter 9: Implementation, Operations, and Maintenance of GenAI Applications -- Chapter 10: Summary, Emerging Trends, Summary, and Next Steps.
520 $a Generative AI (GenAI) is revolutionizing the financial services sector (FSS), offering new ways to enhance efficiency, improve customer experiences, and streamline operations. This book is your comprehensive guide to understanding and implementing GenAI within FSS. Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You'll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You'll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture-through the lens of executives tasked with delivering measurable value responsibly. From there, you'll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You'll see how these capabilities power mission-critical functions across the enterprise: Finally, you'll operationalize all of it with modern FMOps/LLMOps practices-security, privacy, performance, cost management, monitoring, and continuous improvement-so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment. Whether you're a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade. What You Will Learn Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment.
650 0 $a Artificial intelligence $x Financial applications. $3 890884
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Business and Management. $2 eflch $3 639169
700 1 $a Nagvekar, Ravi. $3 1008652
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/979-8-8688-2053-3
950 $a Professional and Applied Computing (SpringerNature-12059)