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Financial Literacy and Fintech : A Double-Edged Sword for Millennial Investors Behavioral Biases
Purpose: The current research focused on investigating the moderating effect of financial literacy and financial technology on the heuristic behavior of millennials. Research Approach: The research was based on the primary data; a survey method questionnaire was prepared to collect the data needed for the present research. With the purposive sampling method, 526 responses were collected from millennial investors. The partial least square-structural equation modeling (PLS-SEM) method was applied to infer the moderating effect of financial literacy and financial technology on millennials heuristic behavior. Findings: The results showed that financial literacy significantly moderated the relationship between millennials heuristics and behavioral biases, whereas financial technology had no moderating effect. Research Implications: Millennial investors were slammed or benefited by the stock market performance. The research aimed to help them understand their behavioral changes during market anomalies. Financial advisors and regulatory bodies should consider the studys outcome as it contributes to mitigating the misconception of behavioral bias. Originality: There are numerous articles describing individual investors behavioral biases, but the current researchs uniqueness was to measure the moderating effect of financial literacy and financial technology on millennials heuristics and behavioral biases and a significant contribution to the world of research in behavioral finance. 2025, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Financial Literacy and Fintech Exposure As Determinants of Investment Decisions: The Mediating Role of Investment Interests A Study of Individual Investors in Hyderabad, India
The evolution of the financial sector, particularly the rise of financial technologies (Fintech), has reshaped how individual investors make investment decisions. This study investigates the influence of financial literacy and fintech exposure on individual investment decisions in the underexplored emerging markets like Hyderabad, emphasising the mediating role of investment interest. Drawing on behavioural finance theory and empirical studies, the research explores how informed financial understanding and engagement with digital financial platforms shape investment behaviour. The data is collected using a structured survey method from 311 individual investors in Hyderabad, India. For the study, Structural Equation Modelling (SEM) was employed to test relationships among the constructs. Unlike prior studies that have often examined financial literacy or fintech exposure in isolation, this paper uniquely integrates these two determinants with the mediating mechanism of investment interest, providing a comprehensive model of investment decision-making in the Indian context. The study contributes to the understanding of investment psychology within the Indian context and offers insights for policy-makers and financial institutions aiming to foster inclusive and informed investment ecosystems. It can be concluded that financial literacy positively influences investment decisions by providing investors with the necessary knowledge and skills to evaluate options critically and confidently. Dr. Syed Jaffer et al. -
Financial Literacy, Inclusion, and Empowerment of Rural Women Entrepreneurs: A Bibliometric Review on the Role of Incubation Centers
In the last twenty years, efforts have been made to address how financial literacy and inclusion can empower rural women entrepreneurs. However, one essential factor tends to be left behindthe contribution of incubation centers to enabling these women to succeed. This research examines the academic landscape in closer detail through a bibliometric analysis of 2,012 peer-reviewed articles between 2005 and mid-2025 based on the Scopus database. Using tools such as Biblioshiny and VOSviewer, we delve into how the discourse on financial capability, women entrepreneurship, and economic empowerment has progressed throughout time. The research indicates a meteoric increase in interest following 2020, fueled primarily by vulnerabilities uncovered with the COVID-19 pandemic. Despite expansion, however, something is certain: there remains relatively little research linking incubation assistance to rural women directly or financial literacy programs. Our analyses of keywords and co-authorships indicate a splintered discipline with ample space for richer, more holistic research. This article not only charts what is known but also reveals what is lacking, presenting new directions for researchers and policymakers dedicated to building stronger safety nets for rural women entrepreneurs. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Financial management analysis of dividend policy pursued by selected Indian manufacturing companies /
Journal of Financial Management and Analysis, Vol.27, Issue 1, pp.223-229 -
Financial market data establishment for effective finance data system /
Patent Number: 202111056642, Applicant: Nitin Kulshrestha.
The present invention relates to a financial market data establishment for effective finance data system. Herein matching engine message stream generator of an electronic exchange platform generates protocol-specific market data messages use and includes a first interface created on a reconfigurable logic device that receives matching engine message(s) with a source specific format from a matching engine. -
Financial market data establishment for effective finance data system /
Patent Number: 202111056642, Applicant: Nitin Kulshrestha.
The present invention relates to a financial market data establishment for effective finance data system. Herein matching engine message stream generator of an electronic exchange platform generates protocol-specific market data messages use and includes a first interface created on a reconfigurable logic device that receives matching engine message(s) with a source specific format from a matching engine. -
Financial Market Forecasting using Macro-Economic Variables and RNN
Stock market forecasting is widely recognized as one of the most important and difficult business challenges in time series forecasting. This is mainly due to its noise. The use of RNN algorithms for funding has attracted interest from traders and scientists. The best technique for learning long-term memory sequences is to use long and short networks. Based on the literature, it is acknowledged that LSTM neural networks outperform all other models. Macroeconomics is a discipline of economics that studies the behavior of the economy as a whole. Macroeconomic factors are economic, natural, geopolitical, or other variables that influence the economy of a country. This study studies and test several macroeconomic variables and their significance on stock market forecasting. In macroeconomics, we have series that are updated once a month or even once a quarter, with data that is rarely more than a few hundred characters long. The amount of data given can sometimes be insufficient for algorithms to uncover hidden patterns and generate meaningful results. Depending on the prediction needs, we proposed a feasible LSTM design and training algorithm. According to the findings of this study, the inclusion of macroeconomic variable has a significant impact on stock price prediction. 2022 IEEE. -
Financial services and green investment on ESG investing for a sustainable future
The financial services industry is transforming as investment businesses become greener. The urgency of global environmental challenges has boosted investor interest in ESG investment. Although long-s tanding, ESG investing remains specialized. ESG factors in investment portfolios may increase economic and social satisfaction, according to this paper. These factors may harm investment portfolios. A worldwide green finance legal framework aims to avoid greenwashing, establish standards, and encourage sustainable development. It examines how ESG efforts effect green money using many research approaches. Risk assessments and industry trends are examined for the company. A resilient and fair economy with ESG investments requires financial services, according to the results. This occurred because financial services are vital. 2025, IGI Global Scientific Publishing. All rights reserved. -
Financial Socialisation, Decision-Making Power and Risk-Taking Behaviour of Rural Households: Moderating Mediation Analysis
Financial socialisation (FS) plays a vital role in determining the financial decision-making power and risk-taking behaviour of rural households. The present study investigates the interplay between financial socialisation, gender, and marital status in shaping decision-making power and investment risk-taking behaviour. A quantitative approach was employed, with 312 survey responses collected via a cross-sectional survey method from rural investors in Karnataka and Tamil Nadu, India. Financial socialisation was assessed using adapted and validated items from prior studies, while trading frequency was a proxy for risk-taking behaviour. The moderated mediation framework (PROCESS Macro Model 8) was employed to investigate the interplay between the variables. Results show that FS significantly increases womens risk-taking behaviour, but this effect is partly reduced due to their lower decision-making power in rural patriarchal households. For men, the direct effect of financial socialisation on risk-taking behaviour is positive but weaker, with no mediation through decision-making power. Married individuals exhibit more conservative risk-taking behaviour than unmarried individuals due to familial responsibilities. The study also found that education and income do not significantly impact decision-making power, possibly reflecting deeper socio-cultural influences in rural settings. These findings imply that policymakers should design targeted financial literacy programmes to address gender disparities and cultural barriers to financial participation. By promoting inclusive financial socialisation, households can achieve more equitable decision-making processes and risk management, which will improve the financial well-being of rural communities. This study contributes to understanding financial socialisation within patriarchal contexts and offers insights into targeted financial empowerment initiatives. The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). -
Financial stress, financial literacy, and financial insecurity in India's informal sector during COVID-19
The lockdowns and restrictions imposed to control COVID-19 have made life miserable for people, especially those involved in informal economic activities. The pandemic induced financial hardships, caused financial anxiety and financial stress among informal sector participants. This study aimed to measure and analyze the financial stress and financial insecurity of one of the important informal sector elements (street vendors) in India. Street vendors in Bangalore were interviewed in this descriptive research through personal interaction and telephonic interviews. The collected primary data were processed using SPSS statistical package. The results have indicated that the pandemic inflicted financial stress on street vendors irrespective of their gender, marital status, age, education, monthly income, and type of product dealt. Financial stress levels varied depending on the number of dependents of street vendors and their business nature. Financial literacy differed according to street vendors' marital status. A person becomes extremely sensitive and cautious in personal finance matters on getting married. Financial stress and financial literacy correlated negatively. 89.5% of street vendors perceived that they had financial insecurity in the future due to this pandemic. The results indicated that financial stress and financial literacy did not affect financial insecurity perceptions of street vendors. The predictors of financial insecurity have been marital status and the number of dependents of the street vendors (r2: 16.6%). However, marital status alone impacted the 6% variance in financial insecurity. This study concluded that the pandemic caused financial stress and financial insecurity among street vendors, but not financial stress and financial literacy. Thangaraj Ravikumar, Mali Sriram, S Girish, R Anuradha, M Gnanendra, 2022. -
Financial Vulnerability in Households: Dissecting the Roots of Financial Instability
The phenomenon of household financial vulnerability, defined by unexpected shocksin income and expenditures, carries major implications for both individual households and the overall economy of a nation. For a considerable time, household debt has been widely acknowledged as the primary determinant of household financial vulnerability. This study aims to extend the analysis beyond the scope of household debt. Middle-income households may experience financial difficulties when faced with unexpected changes in income and expenses. These challenges can arise from several circumstances, including the inability to engage in discretionary activities such as dining out or vacations. For a very long time, it has been posited that low-income households exclusively experience financial vulnerability. Hence, it is imperative to thoroughly examine the concept of household financial vulnerability and its underlying factors to enhance households' ability to withstand adversities and better clarify the matter. In light of the prevailing economic recession triggered by the global pandemic and the ongoing confrontation between Russia and Ukraine, the significance of the matter is further underscored. This study aims to comprehensively define household financial vulnerability and examine its relationship with financial capability, digitalized payments, financial stress, and financial socialization. The current study anticipates establishing a foundational framework for future research endeavors in this specific field. Moreover, this paper also explores potential avenues for future research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Financial Vulnerability in Households: Dissecting the Roots of Financial Instability
The phenomenon of household financial vulnerability, defined by unexpected shocksin income and expenditures, carries major implications for both individual households and the overall economy of a nation. For a considerable time, household debt has been widely acknowledged as the primary determinant of household financial vulnerability. This study aims to extend the analysis beyond the scope of household debt. Middle-income households may experience financial difficulties when faced with unexpected changes in income and expenses. These challenges can arise from several circumstances, including the inability to engage in discretionary activities such as dining out or vacations. For a very long time, it has been posited that low-income households exclusively experience financial vulnerability. Hence, it is imperative to thoroughly examine the concept of household financial vulnerability and its underlying factors to enhance households' ability to withstand adversities and better clarify the matter. In light of the prevailing economic recession triggered by the global pandemic and the ongoing confrontation between Russia and Ukraine, the significance of the matter is further underscored. This study aims to comprehensively define household financial vulnerability and examine its relationship with financial capability, digitalized payments, financial stress, and financial socialization. The current study anticipates establishing a foundational framework for future research endeavors in this specific field. Moreover, this paper also explores potential avenues for future research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Financial well-being A Generation Z perspective using a Structural Equation Modeling approach
The current pandemic situation in the global economy has urged the need to revolutionize the financial services industry with a keen eye on consumers financial needs for sound financial decisions, which is necessary for financial well-being. The purpose of the study is to assess the financial well-being of Indian Gen Z students in relation to financial literacy, financial fragility, financial behavior, and financial technology. In addition, the study also tries to determine how Gen Z students financial well-being is influenced by other factors such as gender, age, parental education, employment status, and monthly income in India. The study uses the scientific data analysis approach, Partial Least Squares-SEM model to estimate, predict, and assess the hypotheses. A sample of 271 University students from India was surveyed using a self-administered structured questionnaire. Questions were incorporated to understand the effect of financial literacy, technology, fragility, behavior, demographic and parental characteristics on financial well-being. The results indicate that financial behavior is positively related to financial well-being, while financial fragility is negatively associated. However, financial literacy and financial technology do not significantly affect financial well-being. The results also show that financial well-being is significantly influenced by gender, parental education, employment status, and monthly income change. Understanding Indian Gen Z student financial well-being will expand the students understanding of the importance of financial literacy for well-planned financial behavior and informed decisions, hence high levels of financial well-being. Government and financial institutions can more effectively identify gaps and deficiencies in student financial well-being. 2022 LLC CPC Business Perspectives. All rights reserved. -
Financing for SDGs in India in Post Pandemic era - Challenges & Way forward
In 2015, a resolution known as Agenda 2030 was passed by United Nations General Assembly in which seventeen goals for Sustainable Development were laid down for global dignity, peace and prosperity. The post- pandemic era became full of uncertainties in pursuing those Sustainable Development Goals (SDGs) and its implementation became a challenge especially for the developing economies like India. The country is facing a tremendous gap in arranging for resources to meet the climatic changes and attaining the SDGs. India requires 170 billion dollars per year from 2015-2030 to fulfill the Sustainable Development Goals as per the estimation done by National Determined Contribution, a body setup after Paris agreement 2015 to monitor the efforts of the country towards reducing national emissions and adapting to climate change. There is a huge concern amongst the various agencies on exploring the ways to fill this financing gap especially after the economic slowdown seen in the post pandemic era. This research paper analyses the challenges imposed by the COVID 19 pandemic on financing for SDGs and also explores the options to mitigate them. The articles and research papers related to SDG financing are reviewed by the researchers to arrive at the above mentioned statements. This paper is an attempt to draw the attention of worldwide authorities towards this grim situation as sustainable finance is far from reality in India and requires immediate up scaling. The Electrochemical Society -
Financing Green Startups: A Blockchain-Powered Approach
Green startups routinely encounter difficulty in obtaining financing owing to the high funding needs to launch their business, and the imprecise market acceptance and future returns of those businesses, rendering them unacceptable to traditional latter-day funding methods. The funding modality available today fails to provide the needed transparency, flexibility and accessibility to encourage ventures based on green projects. This paper develops a funding model based in blockchain for green startups, that employs tokenization, decentralised finance (DeFi) and smart contracts with automaticity, as an efficient way of funding to provide secure, traceable funding structures that make funds available related to the performance of the venture. We present a conceptual model showing the responsibilities of startups, funders and smart contracts within a de-centralised funding ecosystem. Various case studies such as Power Ledger and WePower are investigated in order to validate the practical relevance of the model. Our research indicates how blockchain mechanisms can heighten trust, enhance liquidity, and automate funding that is linked to impact. This paper contributes to future work on scalable platforms that are both regulation compliant and also provide a fit between Blockchain infrastructure and the unique requirements of sustainable innovation. 2025 IEEE. -
Finding a New Life Through Adaptive Reuse for the Old Railway Terminus Complex, Kochi, Kerala
The research article, titled Finding a New Life through adaptive reuse for the Old Railway Terminus Complex, Kochi, Kerala, examines the historical and cultural importance of the original and still existing railway station complex in Ernakulam. This station, which symbolized the arrival of the initial train to Cochin, was constructed during the zenith of the Kochi kingdom in partnership with the British, making a substantial contribution to the regions progress. Over time, the stations original role steadily diminished, leading to its abandonment and subsequent deterioration. The aim of the study is to assess the effectiveness of adaptive reuse as a strategy for conserving this valuable urban asset. The objective of the research is to reuse these neglected structures with the goal of reintegrating them into the vibrant urban landscape of Kochi, thus ensuring a sustainable and environmentally conscious future for the city. The approach involves a thorough analysis of the historical context, current condition, and potential utilization of the precinct. The main findings emphasize that adaptive reuse is an effective method for optimizing space to meet modern requirements while maintaining the historical essence of the built environment. The study highlights the significance of preserving cultural assets by creatively repurposing decommissioned railway historical structures, demonstrating their potential to contribute to sustainable urban development. The research highlights the importance of finding a balance between preserving historical elements and incorporating modern practicality. It provides a framework that can be used by other communities dealing with similar challenges. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Finding balance in a digital world: Equanimity as a predictor of nomophobia
The present study examined the relationship between equanimity and nomophobia. The study also examined the differences in experience of nomophobia considering gender, education and employment status. The sample included 216 emerging adults (M = 64, F = 152) from across India. The Equanimity Scale 16 and the Nomophobia Questionnaire were used to measure equanimity and nomophobia, respectively. Mann-Whitney-U test and Rank-Biserial coefficient indicated that gender differences significantly affected the losing connectedness factor of nomophobia. Correlation analysis showed that equanimity had a significant negative relationship with nomophobia and its factors- not being able to access information, giving up convenience and losing connectedness. Regression analysis showed equanimity as a significant predictor of nomophobia. The studys findings hold potential implications for equanimity-based interventions for nomophobia and individual well-being, technological design improvements in the digital age and unfolds areas for future research. 2024 Taylor & Francis Group, LLC. -
Finding balance in a digital world: Equanimity as a predictor of nomophobia
The present study examined the relationship between equanimity and nomophobia. The study also examined the differences in experience of nomophobia considering gender, education and employment status. The sample included 216 emerging adults (M = 64, F = 152) from across India. The Equanimity Scale 16 and the Nomophobia Questionnaire were used to measure equanimity and nomophobia, respectively. Mann-Whitney-U test and Rank-Biserial coefficient indicated that gender differences significantly affected the losing connectedness factor of nomophobia. Correlation analysis showed that equanimity had a significant negative relationship with nomophobia and its factors- not being able to access information, giving up convenience and losing connectedness. Regression analysis showed equanimity as a significant predictor of nomophobia. The studys findings hold potential implications for equanimity-based interventions for nomophobia and individual well-being, technological design improvements in the digital age and unfolds areas for future research. 2024 Taylor & Francis Group, LLC. -
Finding Real-Time Crime Detections during Video Surveillance by Live CCTV Streaming Using the Deep Learning Models
Nowadays, securing people in public places is an emerging social issue in the research of real-Time crime detection (RCD) by video surveillance, in which initial automatic recognition of suspicious objects is considered a prime problem in RCD. Dynamic live CCTV monitoring and finding real-Time crime activities by detecting suspicious objects is required to prevent unusual activities in public places. Continuous live CCTV video surveillance of objects and classification of suspicious activities are essential for real-Time crime detection. Deep training models have greatly succeeded in image and video classifications. Thus, this paper focuses on the use of trustworthy deep learning models to intelligently classify suspicious objects to detect real-Time crimes during live video surveillance by CCTV. In the experimental study, various convolutional neural network (CNN) models are trained using real-Time crime and non-crime videos. Three performance parameters, accuracy, loss, and computational time, are estimated for three variants of CNN models for the real-Time crime classifications. Three categories of videos, i.e., crime video (CV), non-crime video (NCV), and weapon-crime video (WCV), are used in the training of three deep models, CNN, 3D CNN, and Convolutional Long short-Term memory (ConvLSTM). The ConvLSTM scored higher accuracy, lower loss values, and runtime efficiency than CNN and 3D CNN when detecting real-Time crimes. 2024 ACM. -
Fine-Tuned Deep Contextual BERT for Enhanced Aspect-based Sentiment Analysis: A Comparative Study on Laptop Reviews
Sentiment analysis entails the care full analysis, conduction of interpretation and conclusion of subjective texts even as an evaluation. In the business context, the companies' strategies towards growth makes use of both level of experience of consumers, market reach, social media, opinion and reputation of the brand. The different levels of performing the analysis includes the analysis at the document, phrase, and aspect levels. The sentiment which targets the polarity on some components of texts is often recognized by various Natural language processing (NLP) tasks for example aspect level sentiment analysis. This study presents the fine-tuned deep contextual BERT (FTDC BERT) aiming at improving the accuracy of sentiment polarization prediction. We look at different types of models including the LSTM based and the attention based and the BERT based models and where they performed on the laptop dataset. The fine-tuned and pre-trained BERT model exceeded all benchmarks and gave the most accurate work at 84.48%. This remarkable achievement testifies to the capability of the model in adapting its structure to varying degrees of sentiment contained in laptop reviews. Based on the comparative analysis, different models have different degree of success which indicates that sentiment has to be modelled separately for every set of data. This paper describes interesting areas of the future inline sentiment analysis for researchers and practitioners. 2025 IEEE.