The advancement in FinTech especially artificial intelligence (AI) and machine learning (ML), has significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation are getting more complex in the field of finance. ML is used in many financial companies which are making a significant impact on financial services. With the increasing complexity of financial transaction processes, ML can reduce operational costs through process automation which can automate repetitive tasks and increase productivity. Among others, ML can analyze large volumes of historical data and make better trading decisions to increase revenue. This book provides an exhaustive overview of the roles of AI and ML algorithms in financial sectors with special reference to complex financial applications such as financial risk management in a big data environment. In addition, it provides a collection of high-quality research works that address broad challenges in both theoretical and application aspects of AI in the field of finance.

The advancements in artificial intelligence and machine learning have significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation are becoming more complex within the field of finance. Artificial intelligence and machine learning, with their spectacular success accompanied by unprecedented accuracies, have become increasingly important in the finance world. Advanced Machine Learning Algorithms for Complex Financial Applications provides innovative research on the roles of artificial intelligence and machine learning algorithms in financial sectors with special reference to complex financial applications such as financial risk management in big data environments. In addition, the book addresses broad challenges in both theoretical and application aspects of artificial intelligence in the field of finance. Covering essential topics such as secure transactions, financial monitoring, and data modeling, this reference work is crucial for financial specialists, researchers, academicians, scholars, practitioners, instructors, and students.

The Asian Regional Team for Employment Promotion (ARTEP) is responsible for implementing the ILO's World Employment Programme in the Asian region. Its main objectives are to identify the factors which prevent a substantial expansion of employment opportunities in countries of the region, to identify measures which can overcome these factors and to assist governments in the implementation of such measures. The ARTEP is based in New Delhi, India. The present volume is an edited version of the synthesis report on employment and human resource development strategies in Pakistan carried out under the UNDP-ILO project, "Employment and Manpower Strategies and Policies." The broader issues related to employment and human resource development of Pakistan have been presented in this study in the hope that they will be of interest to a wider audience both inside and outside Pakistan. This volume has been prepared by Mr. John Cameron of the School of Development Studies, University of East Anglia and Mr. Mohammad Irfan of the Pakistan Institute of Development Economics, Islamabad while they were respectively the Chief Technical Advisor and the National Technical Consultant to the above UNDP-ILO project.