Artificial Intelligence and Financial Security

This book “Artificial Intelligence and Financial Security” explores the transformative power of AI in enhancing and safeguarding financial systems. This comprehensive guide looks into AI-driven solutions for fraud detection, risk management, regulatory compliance, and market forecasting.

With detailed case studies, actionable insights, and expert analyses, the book equips the readers to tackle emerging challenges in financial security. It provides a deep dive into cutting-edge technologies like ML, blockchain, and AI-powered cybersecurity, while highlighting the critical importance of ethical considerations and compliance with financial regulations. Each chapter is thoughtfully structured to guide readers from foundational concepts to practical strategies and insights into future trends in AI-driven finance.

By the end of this book, you will be well-positioned to understand how AI is shaping the future of financial security. You will possess the knowledge to make informed financial decisions and navigate the increasingly AI-driven financial landscape with confidence.

KEY FEATURES  

• Practical case studies on AI integration for financial security.
• Strategies to optimize and protect financial systems with AI.
• Insights on emerging AI technologies and trends in finance.

WHAT YOU WILL LEARN

• Understanding the role of AI in securing and optimizing financial systems.
• Detect fraud and manage risks using AI-driven strategies.
• Apply ML for predictive analytics and anomaly detection.
• Integrate blockchain and AI for enhanced financial security.
• Navigate ethical and regulatory challenges in AI implementation.
• Forecast trends and prepare for AI-driven financial innovation.

WHO THIS BOOK IS FOR

This book is for financial professionals, AI practitioners, researchers, and policymakers seeking to understand and apply AI in financial security. A basic understanding of finance, technology, or AI concepts is helpful but not mandatory, as the book provides foundational explanations alongside advanced insights.

1. Fundamentals of AI
2. Financial Security Basics
3. AI Applications in Financial Security
4. ML in Financial Security
5. Data Privacy and Security in AI Systems
6. Cybersecurity and AI
7. Blockchain and AI in Financial Security
8. Regulatory and Compliance Challenges in AI
9. Human AI Collaboration in Financial Security
10. AI in Financial Markets
11. Challenges and Risks of AI in Finance
12. Future of AI in Financial Security
Appendix A
Appendix B

Piyush Ranjan is a seasoned technology leader and Assistant Vice President at a leading financial firm in the USA, with 18+ years of expertise in artificial intelligence, security, and financial systems. As an IEEE Vice Chair and Forbes Technology Council member, he has contributed extensively to the advancement of AI applications in finance, earning recognition for his groundbreaking innovations. Piyush is the recipient of several prestigious awards, has authored numerous scholarly articles, and holds patents in AI-driven financial innovation, demonstrating his commitment to driving transformative change in the industry.

Brij Kishore Pandey is a Principal Software Engineer at ADP in USA with 15+ years of experience specializing in designing, developing, and delivering scalable and robust applications. Proficient in Python, Go, Cloud, Databricks, and AI technologies, Brij is also a GenAI strategist, data professional, and architect. His work bridges the gap between innovation and practicality, and he is a published author with a deep passion for advancing AI-driven solutions. Brij’s expertise lies in creating sustainable and scalable systems while fostering continuous learning and growth.

Rajiv Avacharmal brings 15+ years of expertise in AI and model risk management, specializing in the validation, implementation, and monitoring of AI/ML/GenAI models. Based in the USA, Rajiv has been instrumental in devising strategies to mitigate biases, ensuring fair, transparent, and ethical AI solutions that align with industry standards. His focus on sustainability and ethical AI practices underscores his dedication to building trustworthy and effective frameworks, making him a thought leader in the field. Rajiv’s contributions have helped organizations navigate the complexities of AI with clarity and confidence.