Computational intelligence is driving significant change across various fields. In management, the diligent research by computational intelligence experts has gained significant attention, especially in finance where there is a wide scope to analyze financial data. As a result, computational finance has emerged as a field that is growing rapidly. With the combination of management and computational intelligence, recent efforts have been made to address a wide range of real-world challenges. The CFBA conference provides a platform for researchers to share their latest practical developments in management. The conference is focused on systems and applications papers in management, with an emphasis on practical application papers, as well as more traditional algorithms papers. This will enable researchers working on practical applications to share their latest developments and exchange knowledge with their peers. The main objective of CFBA-2024 is to create a premier forum for interactions among eminent and budding researchers, academicians, experts, and practical innovators from around the world. Through this forum, they can interact and discuss the latest developments and practical applications in the field of management. By bringing together researchers from different backgrounds, the conference will promote collaboration and enable the exchange of knowledge and ideas, with the aim of advancing the field of management.
CFBA-2024 seeks to establish a leading platform for researchers to interact and share the latest practical applications and developments in management. The conference aims to bring together renowned and upcoming researchers, academicians, experts, and practical innovators from around the world to exchange knowledge and ideas on the latest developments in the field of management. The objective is to foster collaboration and promote the advancement of the field through the exchange of practical applications and developments. We are inviting original (un-published research contributions for the conference on the following key themes, but not limited to:

• Financial Analytics: Computational Intelligence for Financial Modeling, Machine Learning in Finance, Big Data Finance and Economics, Neural Networks Modeling for Financial Application, Deep Learning Models in Finance, Probabilistic Modeling/Inference, Fuzzy Sets, Rough Sets, & Granular Computing for Financial Application, Intelligent Trading Agents, Trading systems & Trading Room Simulation, Time Series Analysis, Non-linear Dynamics, Financial Data Mining, Evolutionary Computation for Financial Application, Digital Financial Reporting, Semantic Web and Linked Data, Asset allocation strategies, Algorithmic Trading, Trade execution systems, Financial Risk management, Pricing of structured Securities, Behavioral finance, Evolutionary finance, Portfolio Optimization, Arbitrage, Crypto currencies, Block chain and applications, Financial Prediction and Forecasting, Behavioral Competencies, Diversity, Equity and Inclusion, Revenue Management, Risk and Credit Analytics, Robust Decision Making, Scenario and Sensitivity Analysis


• Human Resource Analytics: Employee Relation, Global HR, HR Analytics, Talent Acquisition Analytics, Workload Analytics, Talent Development Analytics, Succession Planning, Employee Engagement Analytics, Compensation Analytics, Performance Measurement


• Marketing Analytics: Marketing Automation, Customer Retention, Digital Marketing, Demand Generation, Social Media Marketing, Conversion Rate Optimization, Inbound and Outbound Marketing, Influencer Marketing, Marketing Analytics, Marketing Strategies and Innovations, Decision Making in Social Setting, Decision Making under Uncertainty, Decision Making with Multimedia, Decision Theory and Decision Sciences, Digital Market Design and Operation, Dimensionality Reduction, Electronic Commerce, Ethical Decision Making, Customer Relationship Management, Pricing Analytics, Retail Sales Analytics


• Business Analytics: Fraud Analytics, Group Decision Making and Software, Healthcare Analytics, Informatics Theories and Applications, Intelligent Agents Technologies, Intelligent Organizations, Machine Learning, Management Science and Operations Research, Mathematical Optimization, Multiple Criteria Decision Making, Network and Social-Graph Analysis, Optimization, Political Decision Making, Predictive Modeling, Prescriptive Methods, Public Decision Making, Security and Privacy, Sequential Decision Making, Simulation Methods and Applications, Statistical Decision making, Supply Chain Analytics, Transportation Analytics, Web-Based Decision Making