At the heart of the volume lies a simple but consequential observation: rapid advances in artificial intelligence, blockchain, cloud computing, the Internet of Things and data analytics are reshaping the way financial institutions operate and deliver services. These technologies are not incremental improvements to legacy systems. They represent a structural shift in how value is stored, transferred, priced and protected. The book argues that alongside opportunities for greater efficiency, transparency and innovation, the same technologies are creating new challenges related to cybersecurity, regulation, ethics and digital trust, and that understanding both sides of the ledger is essential for anyone working in or studying modern finance.

Artificial intelligence and machine learning receive particular attention throughout the volume. In banking, these techniques now underpin credit scoring, algorithmic trading, customer service automation and, increasingly, the detection of financial fraud. Machine learning models can identify anomalous patterns across millions of transactions in real time, flagging suspicious behavior that would be invisible to manual review. Yet the contributors also confront the harder questions that come with algorithmic decision-making: how to ensure that automated credit decisions are fair, how to explain model outputs to regulators and customers, and how to maintain accountability when machines make choices that were once the preserve of human judgment. Ethical decision-making in AI-driven finance is treated as a first-order concern rather than an afterthought.

Blockchain and distributed ledger technologies form another pillar of the analysis. By allowing transactions to be recorded on tamper-evident, shared ledgers, blockchain promises reductions in settlement times, reconciliation costs and counterparty risk. The book situates these capabilities within the wider movement toward digital payments and tokenized assets, exploring how distributed architectures could reshape everything from cross-border remittances to trade finance. At the same time, the contributors acknowledge the regulatory ambiguity that still surrounds crypto-assets and smart contracts, and the technical hurdles, including scalability and interoperability, that stand between pilot projects and production-scale deployment.

Cloud computing and the Internet of Things extend the transformation beyond software into infrastructure. Cloud platforms give banks elastic computing power and enable the rapid deployment of new services, while connected devices generate streams of data that can inform insurance pricing, asset monitoring and hyper-personalized financial products. The volume’s treatment of hyper-personalized banking is especially timely: financial institutions can now tailor offers, advice and risk assessments to individual customers with a granularity that was unimaginable a decade ago. But personalization at this scale depends on vast data collection, which in turn raises questions about privacy, consent and the security of the cyber-physical systems that link physical devices to financial networks.

Cybersecurity and digital trust emerge as connecting threads across the entire book. As financial services migrate to digital channels, the attack surface for fraud and cybercrime expands in parallel. The contributors examine financial fraud detection as both a technical and an institutional problem, one that requires not only sophisticated analytics but also investor confidence, robust governance and coordinated regulatory oversight. The book’s chapters on risk management consider how institutions can build resilience into systems that are increasingly interconnected, automated and dependent on third-party cloud providers, and how regulators can keep pace with technologies that evolve faster than the rulebooks written for earlier eras.

Regulation itself is a major focus. The volume devotes sustained attention to fintech regulation, exploring the tension between fostering innovation and protecting consumers, markets and financial stability. Regulatory sandboxes, licensing regimes for digital-only banks and evolving standards for data protection all feature in the discussion. The contributors argue that the jurisdictions that strike the right balance between experimentation and oversight are likely to become hubs for financial innovation, while overly rigid frameworks risk pushing activity into less transparent channels. The book also connects regulation to ethics, emphasizing that trust is the fundamental asset of any financial system and that digital transformation succeeds only when customers believe their money and their data are safe.

Sustainability adds a further dimension to the analysis. Chapters on green banking examine how technology can support the transition to a lower-carbon economy, from digital processes that reduce paper and energy consumption to analytics that measure the environmental exposure of loan portfolios. The book positions green banking not as a niche marketing exercise but as a strategic imperative, driven by investor demand, regulatory pressure and the growing recognition that climate risk is financial risk. This perspective links the technological themes of the volume to the broader societal questions that will define the next decade of finance.

For portfolio management and investment services, the book surveys how data analytics and AI are changing the way assets are selected, allocated and monitored. Algorithmic strategies, alternative data sources and automated advisory platforms are democratizing tools that were once available only to large institutions, while also concentrating new forms of systemic risk when many market participants rely on similar models. The contributors consider what these developments mean for investor confidence, market efficiency and the responsibilities of asset managers in an era when machines execute a growing share of trading volume.

By bringing together conceptual analysis, contemporary research and practical perspectives, Reshaping Banking and Financial Services with Disruptive Technologies offers a comprehensive understanding of the digital transformation now underway in finance. The editors, Monica Gupta, Priya Jindal and Piyush Gupta, have assembled contributions spanning fintech, financial technology, digital transformation and the evolving banking landscape, making the volume relevant to researchers, financial-sector practitioners, policymakers and postgraduate students alike. The book is published by Bentham Science Publishers and carries the DOI 10.2174/97988988175341260101. As financial institutions worldwide grapple with the pace of technological change, the volume arrives as a timely map of both the promise and the peril of disruptive innovation in banking, a field in which the next disruption is always closer than it appears.

Subject of Research: The impact of disruptive technologies such as AI, blockchain and cloud computing on banking and financial services

Article Title: Reshaping banking and financial services with disruptive technologies

Article References: Reshaping banking and financial services with disruptive technologies. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: banking, fintech, artificial intelligence, blockchain, cloud computing, Internet of Things, data analytics, cybersecurity, financial regulation, digital payments, green banking, risk management

The research, published in Discover Psychology, was led by Riketa Parmar and Vipul Patel of Ganpat University’s V. M. Patel College of Management Studies, together with Mruga H. Mehta and Jigneshkumar P. Desai of Parul University. The team set out to build and test what they call the Green Banking Consumer Adoption Model for India, or GB-CAM-India. Rather than relying on a single behavioural theory, the model deliberately stitches together three of the most widely used frameworks in consumer and environmental psychology: the Technology Acceptance Model, the Theory of Planned Behaviour, and the Value-Belief-Norm theory. To these it adds constructs tailored to the Indian market, including perceived trust, perceived risk and customer satisfaction.

The logic behind the integration is worth unpacking. The Technology Acceptance Model, developed originally to explain how people come to use new technologies, focuses on two perceptions: that a system is useful and that it is easy to use. The Theory of Planned Behaviour adds the role of attitudes, subjective norms, meaning the social pressure we feel from people around us, and perceived behavioural control, our sense that we are capable of performing the behaviour. The Value-Belief-Norm theory, rooted in environmental sociology, traces pro-environmental action back through a chain of personal values, ecological beliefs and the activation of moral norms. Green banking sits at the intersection of all three: it is a technology, a planned consumer behaviour and an environmentally significant act at once, which is precisely why the authors argued that no single theory could capture the whole picture.

To test the model empirically, the researchers collected primary survey data from 760 respondents spread across five regions of Gujarat, a western Indian state with a large and diverse banking population. For each theoretical construct, they computed composite, or summed, scale scores and then subjected the data to a battery of statistical checks. Exploratory factor analysis was used to confirm that the survey items clustered into the intended dimensions, and reliability analysis confirmed internal consistency. The psychometric credentials of the measures were strong: the Kaiser-Meyer-Olkin measure of sampling adequacy reached 0.906, a value well above the conventional 0.6 threshold, every composite reliability value was at least 0.829, and all average variance extracted values were at least 0.545, calculated from the standardised loadings produced by the factor analysis. In plain terms, the survey instruments measured what they claimed to measure, and they did so consistently.

With the constructs validated, the team turned to multiple regression to test eight hypotheses linking the predictors to green banking adoption behaviour. The model performed respectably, explaining 46.8 percent of the variance in adoption behaviour, with an F-statistic of 82.51 on 8 and 751 degrees of freedom and a p-value below 0.001. Customer satisfaction dominated the results, with a standardised beta of 0.464, far ahead of any other predictor. Perceived ease of use came second at 0.193, followed by social influence at 0.083, both also significant at the 0.001 level. Perceived risk worked in the opposite direction, exerting a significant negative effect with a beta of minus 0.085 and a p-value of 0.002. The message for banks is that making green services feel safe, simple and satisfying matters more than preaching their environmental virtues.

One of the most technically interesting parts of the study concerns how satisfaction connects upstream perceptions to downstream behaviour. Using bootstrapped indirect-effect tests with 5,000 resamples and bias-corrected 95 percent confidence intervals, the researchers found that customer satisfaction carries significant indirect effects from perceived usefulness, perceived trust and environmental attitude through to adoption behaviour. Crucially, the corresponding direct paths from those three constructs to adoption were statistically nonsignificant. That pattern means satisfaction does not merely supplement these influences; it is the channel through which they operate. The authors are careful with terminology here, characterising these as indirect-only effects rather than partial mediation, a distinction that matters for how future researchers model the pathway.

The study also probed how the satisfaction-adoption relationship varies across the population. Income level emerged as a significant moderator of that path: higher-income consumers showed reduced sensitivity to satisfaction signals when deciding whether to adopt green banking. In other words, for wealthier customers, a pleasant service experience moves the adoption needle less than it does for lower-income consumers, a finding with clear implications for how banks segment their green marketing. The researchers additionally observed that mean adoption scores differed significantly across Gujarat’s five regions, with an F-statistic of 9.88 on 4 and 755 degrees of freedom and a p-value below 0.001. They are careful to note, however, that this is a group-difference finding rather than a formally tested regional moderation effect, an honest caveat that reflects the exploratory, composite-score design of the analysis.

The practical implications ripple outward from these statistics. For banks, the results suggest that investments in service quality, complaint resolution and overall customer experience may do more to accelerate green banking uptake than awareness campaigns alone, because satisfaction is the conduit through which usefulness, trust and environmental attitudes are converted into action. Reducing perceived risk, whether fear of fraud in digital channels or uncertainty about green products, should also pay dividends, given its significant negative coefficient. For policymakers working under the Reserve Bank of India’s Green Finance Framework, the regional differences in adoption scores across Gujarat hint that a one-size-fits-all national rollout may underperform, and that income-sensitive design could matter, since wealthier consumers respond differently to satisfaction cues than lower-income ones.

The authors are equally candid about the limits of their approach. Because the analysis relied on composite scores, exploratory factor analysis and multiple regression rather than a full structural equation model, the causal architecture of GB-CAM-India remains a proposal awaiting confirmatory testing. They explicitly flag directions for future SEM-based research that could estimate the full path model with latent variables, test the regional moderation hypothesis formally, and extend the sample beyond Gujarat to other Indian states. The survey design is also cross-sectional, so the direction of influence, while theoretically motivated, is inferred rather than observed over time.

Even with those caveats, the study lands at a propitious moment. As India’s financial sector aligns itself with sustainable development goals, understanding the psychology of the consumer becomes as important as the engineering of the green products themselves. What this research demonstrates is that the road to sustainable finance in India runs through the everyday experience of the bank customer: a useful app that is trusted, a service that satisfies, and a social environment that quietly nudges people toward greener choices. If satisfaction is the engine of green banking adoption, then the banks that win India’s sustainable finance transition may be those that treat environmental ambition and customer experience as a single, inseparable project.

Subject of Research: Consumer adoption of green banking services in India, modelled through an integrated TAM-TPB-VBN framework

Article Title: An integrated TAM–TPB–VBN framework with empirical validation from Gujarat for green banking consumer adoption in the Indian market

Article References: Parmar, R., Patel, V., Mehta, M. H., & Desai, J. P. (2026). An integrated TAM–TPB–VBN framework with empirical validation from Gujarat for green banking consumer adoption in the Indian market. Discover Psychology. https://doi.org/10.1007/s44202-026-00883-5

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00883-5

Keywords: green banking, consumer adoption, Technology Acceptance Model, Theory of Planned Behaviour, Value-Belief-Norm theory, India, Gujarat, customer satisfaction, sustainable finance, perceived risk, social influence, survey research