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This study examines the importance of financial inclusion and financial literacy in achieving Sustainable Development Goal 1 (SDG 01) of reducing poverty within Asia. It highlights the significance of fostering financial inclusion and spreading financial literacy for economic prosperity in the region. Despite the progress made in combating poverty and enhancing financial commodities, challenges persist, particularly regarding insufficient accessibility to basic financial amenities and a lack of knowledge in handling finances. However, a substantial portion of the Asian population lacks access to the financial literacy skills necessary for utilizing financial facilities and achieving financial inclusion. It reviews the current situation of financial inclusion and financial literacy in the region, explores the factors influencing these concepts, and highlights government initiatives aimed at fostering financial inclusion and literacy. Asia, with its diverse cultural and socioeconomic contexts, presents unique challenges and opportunities for promoting financial literacy and inclusion. The region’s growing population, emerging economies, and increasing middle-class underscore the importance of these factors. Ensuring that individuals have access to financial services and the knowledge and skills to manage their finances effectively can support economic development and poverty reduction, and create an inclusive and equitable society. By addressing the challenges of limited access to financial amenities and promoting financial literacy among the population, it is possible to foster economic growth, reduce poverty, and create more inclusive societies.

Introduction: Artificial intelligence (AI), the engineering of brilliant machinery, performs intelligent human intelligence tasks, such as learning and problem-solving. Insurance is a financial protection policy either for individuals or entities to reimburse losses from the insured company. The role of AI in insurance always helps enhance customer services and understand their behaviour.

Purpose: This chapter aims to determine the role of AI in the insurance industry in India. The insurance industry is expanding very fast, and to further increase its horizons, the part of the technology of AI is essential. However, this sector has initiated using AI technology and is expanding its scope to benefit the customers.

Methodology: The authors selected research papers of the last five years to review and determine how the technology changed during the period and how an increase in AI benefits the industry and facilitates delivering the best services, and understanding the customer’s needs and behaviour.

Findings: It has been found that the industry is moving very fast and adopting the AI technology methods to enhance customer services, betterment for growing India, and serve insurance services to the nation efficiently.

Purpose – The purpose of this paper to immobilization provides biosorbent particle with density and mechanichal strength, immobilization can save the cost of separating from biomass, can be regeneration and to increase adsorption capacity for metal ions.

Design/Methodology/Approach – The parameters affecting the adsorption, such as initial metal ion concentration, pH, contact time, and temperature, were studied. The analysis of biosorbent functional group was carried out by Fourier Transform Infrared Spectroscopy, SEM-EDX, for elemental analysis.

Findings – Optimum pH condition for biosorption Cd(II) was pH 5, contact time was 45 min, and initial concentration was 250 mg/L. Biosorbent analysis was characterized using SEM-EDX and FTIR analysis. Kinetics adsorption was studied and analyzed in terms of the pseudo-first-order, pseudo-second-order, and intraparticle diffusion kinetics models. The result showed that the biosorption for Cd(II) ion followed the pseudo-second-order kinetic model. Biosorption data of Cd(II) ion at 300°K, 308°K, and 318°K was analyzed with Temkin, Langmuir, and Freundlich isotherms. Biosorption of Cd(II) by durian seed immobilization in alginate according to the Langmuir isotherm equation provided a coefficient correlation of r² = 0.939 and maximum capacity biosorption of 25.05 mg/g.

Before the September–October 2008 Financial Crisis, investment banks were hooked on debt. In 2007, a year before its failure, Lehman Brothers held equity just 3.3% of its balance sheet (that is, its debt/equity ratio well exceeded 29); virtually all the rest was financed by borrowing. Leverage is an elixir that makes profits soar when times are good but magnifies losses when the economy sours. Currently in India, several companies have seen their balance sheet out of shape because of overleverage, but banks continue to be benevolent, often forced by political interventions (see Cases 6.1 and 6.2). Most of these business groups are nearly dead, with their equity almost wiped out. There is little chance they will survive but for their banker’s largesse. Ever-greening of loans is keeping them alive, but what could be the end game? For instance, just a year before economic liberalization in India, few enterprising men invested in the steel business. They borrowed monies from the banks and banks continued to finance their operations, and now they are realizing that the promoters cannot meet with their debt obligations. The banks, however, did not want to accept financial loss and hence commonly agreed to ease the payment obligations so that the loans remained good and not degenerate to NPAs. This is tantamount to refinancing to service your loans. But now the banks overwhelmed with accumulated NPAs are trying to sell debt. How do you legally, ethically, morally, and spiritually (LEMS) justify share-market concentration in the hands of very few promoter investors? What are their long-run unintended economic, legal, ethical, and moral consequences, and why? This chapter studies this market turbulence and the role of bankruptcy laws and court systems in bringing about some change in the debt-overleveraged corporations.

A major chunk of rural people live on agriculture and other allied activities viz animal husbandry, dairying and fisheries, etc. Rural development constitutes of lot of big data related to rural employment which has driven this study to address a research question that what is the application of big data in rural development with special reference to the world’s largest public works and wage employment generating poverty alleviation program – Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)? The concepts of MGNREGA are novel and innovative though the program continues to suffer from various rigidities depicted from the data. This drives us to the objectives of our research. The objective of the study is to explore literature and big data on rural development with special reference to MGNREGA, explore the upcoming challenges in rural employment with special reference to MGNREGA, identify gaps in existing literature and pave out future research direction. The present study paves various ways for future research directions for academicians, researchers and policy maker.