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This chapter explores the intersection of cutting-edge algorithms in the financial technology (FinTech) sector, with a particular focus on the application of machine learning (ML) and artificial intelligence (AI) to enhance sustainability and ethical finance practices. The transformative capabilities of ML and AI are examined through their roles in revolutionising financial services by increasing operational efficiency, improving decision-making processes and enhancing risk management strategies. Specific applications discussed include fraud detection, anomaly detection in financial statements, robo-advisory services, prediction of customer deposits, combating money laundering, sentiment analysis, loan eligibility prediction, stock price prediction and the automation of routine tasks through chatbots. Additionally, the chapter addresses the crucial role of AI and ML in supporting green finance initiatives, reducing carbon footprints and promoting financial inclusion, thereby contributing to sustainable economic development. The detailed exploration provides insights into how these advanced technologies are key in shaping the future of the financial industry towards more sustainable outcomes.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.