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Fingerprint based authentication model to protect the sim card of the mobile /
Patent Number: 201941048500, Applicant: Dr. Gobi R.
Nowadays, Mobile becomes an essential part of our life, and it is also an inevitable medium for communication in the present era. It keeps us connected from mail access, travel booking, etc. The amount of personal information and sensitive information like username, password, and transaction details are routinely stored in the device. There is a possibility of information access when the thief steals the Mobile. It is a massive data loss for the mobile owner, especially private information. -
Fine-tuning Language Models for Predicting the Impact of Events Associated to Financial News Articles
Investors and other stakeholders like consumers and employees, increasingly consider ESG factors when making decisions about investments or engaging with companies. Taking into account the importance of ESG today, FinNLP-KDF introduced the ML-ESG-3 shared task, which seeks to determine the duration of the impact of financial news articles in four languages - English, French, Korean, and Japanese. This paper describes our team, LIPIs approach towards solving the above-mentioned task. Our final systems consist of translation, paraphrasing and fine-tuning language models like BERT, Fin-BERT and RoBERTa for classification. We ranked first in the impact duration prediction subtask for French language. 2024 ELRA Language Resource Association. -
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. -
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. -
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 -
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. -
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 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 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 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 management analysis of dividend policy pursued by selected Indian manufacturing companies /
Journal of Financial Management and Analysis, Vol.27, Issue 1, pp.223-229 -
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Financial Literacy and Financial Capability among the Urban Street Vendors
Employment in the informal sector has grown rapidly over the years as it requires a limited skill set, limited educational background, and least initial investment. One such vulnerable sector which forms the major portion of the informal workforce is the street vendors. They lack basic facilities to newlinehave a good standard of living. It is observed that they are usually denied newlinevarious opportunities though their contribution to the economic growth and newlinedevelopment is immense. Their unstable income has left them vulnerable to many financial situations and led them into a financial debt trap. This research is carried out entirely from the view of the street vendors. newlineFinancial literacy has gained importance over the years as it enhances and empowers one s financial ability. Financial literacy is promoted through financial inclusion where all the sections of the society come under one roof to avail finance at ease. Basic financial literacy is will aid the users to newlinemake better utilization of financial schemes under financial inclusion. This in turn leads to better financial capability for individuals. It is observed that there is a gap that needs to be bridged between the street vendors and financial accessibility as they lack basic financial knowledge as are from a low educational background in this study. Better financial knowledge will newlinelead to better usage and accessibility of financial inclusion schemes which will result in better financial capability; this concept is being examined in the current study. The identified relationship impact of financial inclusion on financial literacy and financial capability forms an integral part of the study. It is useful in bringing out the gap between the street vendors and their financial distress. The research was designed to develop an instrument. A research instrument to measure variables was built based on previous studies and the expert s newlineconsultation. -
Financial Lexicon based Sentiment Prediction for Earnings Call Transcripts for Market Intelligence
Sentiment based stock price direction detection has been an exciting study in the field of finance which is drawing a lot of attention from the investor community. Sentiments are used to detect the changes in the stock price movements for the subsequent periods. Investor community uses these sentiments derived from news, celebrity speech and events to plan trading and investment strategies. Several studies have been done in the past with sentiments, but use of Earnings Call Transcripts (ECT) has not been explored for market intelligence hitherto. Standard dictionary based lexicons like Vader, AFINN and NRC have not performed well in finance as they are domain agnostic. There is a need to develop a financial lexicon based on the ECT corpora, which may provide a better lift over the standard lexicons. This study has observed that Vader has performed poorly as opposed to the newly developed financial lexicon. Machine learning based generative lexicon engine using Bayesian approach, which is termed as FNB Lex was developed in this research study to overcome the limitations of standard domain agnostic lexicons. The lexicon development was performed on quarterly Earning Call Transcripts (ECT) of sixteen IT companies spanning over ten years. The study also investigates the detection of inverse effect in stock price movements based on the sentiments of the previous period. Machine Learning (ML) models like Naive Bayes, FNB Lex, SVM and biLSTM were developed and their discriminatory powers were assessed. NB Lex provided much better lift in detecting the inverse effect as opposed to other models. 2024 IEEE. -
Financial inclusion of rural sector: Imperative for sustainable economic growth of India
This research paper aimed to take a look on the present status of financial inclusion in the Indian economy, especially in the rural sector. It also suggested few measures to be taken by the government and banking sector to enhance the inclusion of deprived sections of our country in the financial ecosystem. The data was collected from various secondary sources to depict the present level of financial inclusion, primarily after the implementation of various government policies. The suggested measures mainly included financial literacy and awareness campaign to be implemented at the grass root level along with a robust infrastructure to increase the telephone and internet connectivity in the rural sector. The researchers also analysed that the financial inclusion of the rural sector is imperative for the sustainable economic growth of an agricultural driven economy like India. 2021 Ecological Society of India. All rights reserved. -
Financial inclusion in IndiaA progress and challenges
The term Financial Inclusion means the process of access to appropriate financial products and services needed by all sections of society including vulnerable groups such as weaker section and low-income at an affordable cost. It has been a very big challenge for the developing countries for including the people into the financial system. Financial inclusion is emerging as a new paradigm of economic growth that plays major role in driving away the poverty from the country. Financial inclusion is important priority of the country in terms of economic growth and advancement of society. Globally, the financial inclusion is on the rise and from 2014-2017, 515 million adults opened an account with bank and there has been a significant increase in the use of mobile Phones and internet to conduct financial transaction. There was a commendable increase in the financial inclusion and this is predominantly driven by India. Through government initiatives and indicatives taken by the RBI, weaker sections of society and economically poor people were able to access to financial products, services, credit etc. The basic variables for measuring the financial inclusion are bank penetration, credit penetration, number of accounts opened etc. So the present study aims to investigate the progress of financial Inclusion in India through the initiatives taken by the Government of India(GOI) and Reserve Bank of India (RBI). 2019 SERSC. -
Financial inclusion and poverty alleviation: The alternative state-led microfinance model of Kudumbashree in Kerala, India
The study examines the microfinance and microenterprise model of Kudumbashree, the state poverty eradication mission of Kerala, and its impact on poverty alleviation in the state of Kerala in India. Kudumbashree's method of identification of the poor is seen to be superior to the conventional head count ratio as it captures the multidimensional characteristics of poverty leading to lesser chances of exclusion of vulnerable families. The microenterprise-linked microfinance model of Kudumbashree has established itself as an effective model linking the state, community, and financial organizations, differentiating itself from other NABARD-led self-help group (SHG) programmes or the Grameena model of microfinance institutions in the country. The fundamental idea of local economic development on which the microenterprise business is built is, however, not free from limitations. Heavy reliance on local markets for procuring inputs and selling outputs makes the products less competitive, questioning the sustainability of a business-led model in the absence of state subsidy in the longer run. Copyright 2014 Practical Action Publishing. -
Financial Inclusion and Human Development in Indian States: Evidence from the Post-Liberalisation Periods
This article examines the existing synergy between financial inclusion and human development in Indian states during the post-liberalisation periods (19932015). Using both principal component analysis and panel data regression models, first, the impact of financial inclusion on human development is measured. Second, the reverse causality from human development to financial inclusion is estimated to know whether human development should be a pre-condition for ensuring greater financial inclusiveness in Indian states. It is found that financial inclusion has a positive and statistically significant impact on human development, along with other control variables such as social sector expenditure, per capita state gross domestic product and capital receipt. However, the lack of urbanisation (measured by the percentage of rural population) has a negative and significant impact on the process of human development in Indian states. On the other hand, since human development has also a significant reverse causal connection with financial inclusion, it is argued that ensuring financial inclusion through urbanisation measures would not only improve the level of human development in Indian states, but it would also sustain the process of inclusive development in itself due to the existing feedback loop with the later. 2022 Institute for Human Development. -
Financial Distress and Value Premium using Altman Revised Z-score Model
In the stock market, investors and value managers desire to be safe. Estimating equity returns and evaluating potential financial distress risk are essential for investment and trading decisions. The link between distress risk and stock return is controversial, and current literature yields contradicting results. A variety of models may be used to evaluate distress risk-return trade-offs. This paper employs a revised Altman Z-score to examine financial distress and value premiums. Using univariate and multivariate techniques, we examine firm- and industry-level portfolio returns, encompassing all Indian companies listed on the Bombay Stock Exchange (BSE). Results confirm the existence of the distress factor effect found in industry and firm-level portfolios. It shows that the distress risk factor significantly determines stock returns as an independent systematic risk factor. This result is consistently found in most industries. The study demonstrates the existence of a value premium in both distressed and safe zones. The study also used a multivariate GRS test and the Fama-Macbeth procedure to validate the reliability of the distress factor and pricing models. Results confirm that Altman model-based distress factor augmented models improve the performance of existing pricing models with higher reliability and accuracy. 2023 MDI.