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Foundations of Artificial Intelligence in Finance.epub
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Foundations of Artificial Intelligence in FinanceInsights for Practitioners with Applications and Case Studies
rtificial intelligence (AI) is transforming the global financial services industry by increasing the efficacy, accuracy, and customisation of financial goods and services. Organisations can make better use of large datasets, identify trends, automate decision-making, and streamline operational procedures by leveraging AI tools, particularly machine learning (ML), deep learning (DL), and natural language processing (NLP) [1–4]. As a result, significant advancements have been made in areas such as fraud detection, asset management, credit rating, and client contact. AI-driven systems have been used more and more by FinTech companies and financial institutions in recent years to provide specialised services, lower transaction costs, and better manage risks.
For example, the AI-based lending platform Upstart stated that, at the same default rate, its models approve 27% more loans than conventional credit assessment systems [5]. Similar to this, robo-advisory services like Wealthfront and Betterment use AI-powered algorithms to provide individualised, reasonably priced investing advice with little assistance from humans [6]. The use of AI in financial decision-making presents serious ethical, legal, and technological issues in spite of its advantages. Regulators and scholars have focused on issues such as algorithmic opacity, possible bias in training data, lack of interpretability, and data privacy concerns [7–10]. As an example, the European Union, in its General Data Protection Regulation (GDPR), implements the principles of algorithmic transparency and non-discrimination [11]. This chapter makes a systematic and critical exploration of the backgrounds, applications, and the future of AI in Finance. It combines results from academic research and industrial practice to analyse the application of AI for solving real-life specific financial challenges like risk assessment, fraud detection and prevention, and regulatory compliance. We focus on new developments, such as new explainable AI (XAI) innovations, adversarial ML, and multimodal data analysis that are rising stars in the domains of financial technology [12, 13]. Moreover, the chapter beholds a systematic review of 162 peer-reviewed papers, to chart existing areas of research while 2. highlighting major areas that deserve attention. This chapter provides a bibliometric and thematic analysis that reveals the applied use of AI in various financial contexts and identifies areas for future investigation. Bridging theory and practice, it aims to provide researchers with a detailed manifesto for future research and practitioners with a practical guide to the process of adopting AI.
Chapter 1Introduction to AI in Finance: Foundational Concepts and Emerging ChallengesAfzalur Rahman, Sruthi Sivakumar, Uvesh Husain, and Sujit Singh
Chapter 2Framework for Responsible AI Adoption in FintechSyed Hasan Jafar
Chapter 3Exploring Explainable AI (XAI): Implications for Transparency in Financial Decision-MakingHemachandran K
Chapter 4Implementing Robotic Process Automation (RPA) for Financial OperationsSolomon Jeresa
Chapter 5Leveraging Natural Language Processing (NLP) in Financial Customer Service: Enhancing User ExperienceRajan Gupta and Sudeshna Sani
Chapter 6Advanced NLP for Financial Document Analysis: Tools and TechniquesPrince Yeboah Asare
Chapter 7Predictive Analytics and AI in Credit Scoring: Transforming Lending PracticesSamba Shiva Rao, Dharmavarapu Naveen Kumar, and Marella Anvitha
Chapter 8AI-Driven Fraud Detection and Prevention StrategiesDzisenu Dziedzorm and Kotagiri Sai Deepak
vi. Chapter 9AI in Sustainable Finance and ESG Analysis: A Practical GuideMichael Ayikwei Quarshie, Cornelius Adorm-Takyi, Reginald Djimatey, and Dominic Achari
Chapter 10An African Perspective on Artificial Intelligence and Climate FinanceWilson E. Herbert and Maureen N. Nwala
Chapter 11AI in Sustainable Risk Management and ComplianceMichael Ayikwei Quarshie, and Reginald Djimatey
Chapter 12Exploring the Influence of Gold Prices on Forex Rates, Equity Index, and Crude Oil Amid Disruptions: A Comparative Analysis of Machine Learning and Deep Learning ApproachesMulukalapally Susruth, Mahesh Admankar, and Ch. Purnachander
Chapter 13Intelligent Robo-advisors and Personalized Financial PlanningCornelius Adorm-Takyi and Fredrick Appiah Asare
Chapter 14AI in Algorithmic Trading and Investment StrategiesJoseph Tufuor Kwarteng
Chapter 15Deep Learning in Stock Forecasting and Market PredictionsKotagiri Sai Deepak
Chapter 16AI Applications for Anti-Money Laundering and Compliance in Financial InstitutionsDonkor Nawaah and Rockson Mintah
Chapter 17Ethical Considerations for AI in Financial ServicesPrashant Subhash Chougule and Siddharth Nanda
Chapter 18Artificial Intelligence in Healthcare Finance: Developing Sustainable Financial ModelsEmmanuel Asare Tettey
vii. Chapter 19Blockchain and AI in Finance: Synergies for a Digital EconomyMuneer Shaik and Mukundamgari Rishik Reddy
Chapter 20AI-Driven Socially Responsible Investing: Tools for Impact MeasurementLeticia Bosu
Chapter 21Financial Management and AI: A New Dawn for CompaniesMurage Jane Karuana and R. V. Palanivel
Chapter 22Case Studies and Future Directions for AI in FinanceDonkor Nawaah
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