Indian Financial Sector Research Articles

Precision forecasting in perilous times: stock market predictions leveraging google trends and momentum indicators during COVID-19

PurposeThis study explores the complex impact of COVID-19 on India's financial sector, moving beyond simplistic public health vs. economy views. We assess market vulnerabilities and analyze how public sentiment, measured through Google Trends, can predict stock market fluctuations. We propose a novel framework using Google Trends for financial sentiment analysis, aiming to improve understanding and preparedness for future crises.Design/methodology/approachHybrid approach leverages Google Trends as sentiment tool, market data, and momentum indicators like Rate of Change, Average Directional Index and Stochastic Oscillator, to deliver accurate, market insights for informed investment decisions during pandemic.FindingsOur study reveals that the pandemic significantly impacted the Indian financial sector, highlighting its vulnerabilities. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.95% maximum accuracy in forecasting stock market values during such events.Originality/valueTo the best of authors knowledge this model's originality lies in its focus on short-term impact, novel data fusion and methodology, and high accuracy.• Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of COVID-19 on market behavior.• Novel data fusion and framework: A novel framework of sentiment analysis was introduced in the form of Trend Popularity Index. Combining trend popularity index with momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods.• High predictive accuracy: Achieving the prediction accuracy (98.93%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

Optimizing Digital Financial Data: Enhancing Business Decision Making in the Indian Scenario

The study aims to explore challenges hindering inclusive access to digital financial inclusion (DFI) in the Indian financial sector, focusing on the role of automation in financial decision-making support systems. It also seeks to assess the impact of digital technologies on corporate financial performance and Environmental, Social, and Governance (ESG) considerations. Descriptive research methodology was conducted to analyse challenges affecting inclusive access to DFI, with a sample size of 388 participants from major financial institutions in Mysore city. Primary data was collected through structured questionnaires, and secondary data was obtained from relevant literature and reports. Statistical methods including ANOVA were employed for data analysis. The analysis revealed non-significant differences in digital literacy programs and technological infrastructure among banks, highlighting a uniform approach and the need for standardized development. Significant variation was observed in gender-based challenges, emphasizing the necessity for tailored initiatives. Non-significant differences in automation adoption and system usage imply a consistent approach across banks, though further investigation is warranted. Borderline significance in stakeholder perception suggests diverse opinions, requiring proactive management during digital transformation. The study underscores the importance evaluations and collective efforts to address challenges hindering inclusive access to digital financial services in India. While certain aspects exhibit consistency, targeted interventions are needed to foster inclusivity and maximize the potential of digital technologies. Future research should explore stakeholder perceptions and influencing factors behind automation adoption trends to enhance understanding of digital financial inclusion dynamics in India.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN FINANCIAL DECISION-MAKING

In the realm of finance, decision-making processes have always been pivotal in determining the success or failure of individuals, businesses, and economies at large. With the advent of Artificial Intelligence (AI), this landscape is undergoing a profound transformation. The integration of AI technologies in financial decision-making is not merely an augmentation of existing processes but a fundamental shift in how decisions are conceived, analysed, and executed. This introduction seeks to delve into the evolving role of AI in financial decision-making, particularly within the context of the Indian financial sector. The rapid pace of technological advancement has propelled AI into the forefront of various industries, and finance is no exception. AI encompasses a spectrum of technologies, including machine learning, natural language processing, deep learning, and predictive analytics, among others. These tools offer the ability to process vast amounts of data, identify patterns, and generate insights at speeds and scales that were previously unimaginable. In the context of financial decision-making, this translates into enhanced capabilities for risk assessment, portfolio optimization, fraud detection, and customer service, among others. India, with its burgeoning economy and vibrant financial markets, stands at the cusp of this AI-driven revolution. The country's financial ecosystem, characterized by a diverse array of institutions ranging from traditional banks to fintech startups, is ripe for AI-led innovation. The adoption of AI in Indian finance is driven by several factors, including the proliferation of digital technologies, the increasing availability of data, and the imperative for efficiency and competitiveness in a globalized economy. Furthermore, initiatives such as the government's Digital India campaign and regulatory efforts to promote fintech innovation have created a conducive environment for AI adoption in the financial sector.

HARNESSING THE SYNERGY OF HR AND MARKETING IN INDIA'S FINANCIAL SECTOR: STRATEGIES FOR SEIZING OPPORTUNITIES AND SURMOUNTING CHALLENGES TO BOOST PERFORMANCE

In the dynamic and competitive landscape of India’s financial sector, the integration of Human Resources (HR) and Marketing functions has emerged as a critical strategy to enhance organizational performance. This paper explores the synergy between HR and Marketing, highlighting how their collaboration can lead to a more cohesive brand identity, improved customer experiences, and a motivated workforce. The financial sector in India is undergoing rapid transformation, driven by technological advancements, regulatory changes, and evolving customer expectations. In this context, the alignment of HR and Marketing strategies becomes essential for organizations to stay competitive and responsive to market demands. The paper examines key strategies for harnessing this synergy, such as cross-functional collaboration, aligning employee engagement with brand values, and leveraging data-driven insights to foster innovation. It also addresses the challenges that organizations may face in implementing these strategies, including cultural barriers, resistance to change, and the need for continuous upskilling of employees. Through a comprehensive review of literature and case studies from leading financial institutions in India, this paper identifies best practices for creating a seamless integration of HR and Marketing functions. The findings suggest that organizations that successfully leverage this synergy are better positioned to seize market opportunities, enhance customer loyalty, and drive sustainable growth.

Role of Artificial Intelligence (Ai) and Machine Learning (Ml) in Financial Decision-Making

In the banking business, the use of artificial intelligence (AI) algorithms to detect fraud, automate trading activities, manage portfolios, and provide customer service has increased significantly in recent years. Artificial intelligence (AI) uses statistical modeling to create predictions. Managing relationships and providing investors with financial advisory services. The inherent capacity of AI to quickly analyze several data sets and create different business scenarios to aid in decision-making can enhance an organization’s financial performance without explicitly programming for predicted results. This study examines how well AI is implemented in the Indian financial sector, as well as how much progress has been made in this area Integration has produced. The study addresses some of the contemporary AI technologies used in the Indian financial sector and attempts to investigate the comfort level and expectations of these workers with regard to AI use. Additionally, it attempts to statistically examine the degree of integration and potential relationship between AI systems and the features and efficacy that they have brought to financial decision making across all industries and participants in the Indian financial sector, as well as across all job levels within various financial organizations.

A STUDY ON IMPACT OF GLOBAL ECONOMIC CRISIS ON THE INDIAN ECONOMY: CASE STUDY

This paper explores the complex relationships between international financial crises and the ensuing changes in Indias financial system. It attempts to offer thorough insights into the ways that times of worldwide economic unrest affect the Indian financial market, impacting its composition, dynamics, and general resilience. This paper examines the complex effects of global economic downturns on Indias financial ecosystem using empirical data and in-depth analysis. It looks into the relationships between these crises and changes in important metrics such as currency exchange rates, stock market indices, investment trends, and government reactions. This article also examines the adaptable strategies the Indian financial sector used to get through these trying times. Through an analysis of past examples and current situations, it provides insightful viewpoints on the tactics used by investors, market players, and policymakers to reduce risks and seize opportunities in the face of worldwide economic volatility. In the end, this article aims to advance a nuanced understanding of the complex interactions between global economic crises and Indias financial environment by illuminating the ramifications, difficulties, and possible solutions for bolstering the Indian financial systems resilience in a globally interconnected economy

Strategic Shift in Indian Financial Sector- A Lesson from Pandemic (Covid-19)

Strategic Shift in Indian Financial Sector- A Lesson from Pandemic (Covid-19)

A survey of cybersecurity threats and countermeasures in the Indian financial sector

This research paper delves into the realm of cybersecurity threats and countermeasures within the Indian financial sector, a domain increasingly susceptible to cyber attacks due to rapid digitalization. The primary objective of this study is to assess the current state of cybersecurity awareness, the effectiveness of existing countermeasures, and to identify potential gaps in the cybersecurity framework of the Indian financial sector. Employing a structured questionnaire, data was collected from 750 respondents across various demographics including financial analysts, IT professionals, and banking employees, utilizing stratified random sampling techniques. The analysis involved frequency count, percentages, and cross-tabulation to interpret the complex interplay between demographic factors and cybersecurity aspects. The study highlights the importance of continuous adaptation in cybersecurity measures and advocates for enhanced training programs and policy enforcement.

Strategic Shift in Indian Financial Sector- A Lesson from Pandemic (Covid-19)

Strategic Shift in Indian Financial Sector- A Lesson from Pandemic (Covid-19)

Navigating consolidation: Understanding objectives, legislation and phases of banking mergers in the Indian financial sector: A review

Navigating consolidation: Understanding objectives, legislation and phases of banking mergers in the Indian financial sector: A review

Review Paper on Enhancing Stock Price Prediction with Sentiment Analysis of Bank Nifty Index

Sentiment analysis has emerged as a powerful tool in financial markets, offering the ability to harness market participants' collective wisdom and emotions to make more informed investment decisions. This research paper presents a comprehensive literature review on sentiment analysis models in predicting stock prices, focusing on the Bank Nifty Index, a critical benchmark in the Indian financial sector. The review begins by elucidating the significance of sentiment analysis in stock price prediction, highlighting its pivotal role in capturing market sentiment, investor emotions, and their impact on asset valuations. A detailed overview of sentiment sources, encompassing financial news, social media, reports, and other relevant data streams, provides insight into the rich tapestry of information that sentiment analysis can leverage. The paper delves into various sentiment analysis approaches, from traditional lexicon-based and rule-based methods to cutting-edge machine learning and deep learning techniques. It elucidates the intricate process of integrating sentiment analysis with stock price prediction models, exploring feature concatenation, time series integration, and weighted data to incorporate sentiment insights effectively. Evaluation metrics crucial for assessing the performance of both sentiment analysis models and stock price prediction models are thoroughly discussed. It concludes by highlighting the substantial potential of sentiment analysis in augmenting stock price prediction, offering investors and traders valuable tools to navigate the complexities of financial markets.

A Study On Financial Performance Analysis with Reference to Real Touch Finance

The Indian financial sector boasts diversity and rapid expansion, featuring an array of financial institutions, including commercial banks, insurance companies, NBFCs, co-operatives, pension funds, and mutual funds. Among these, NBFCs play a pivotal role, contributing significantly to economic growth by offering credit and financial services to various sectors. This study undertakes a five-year analysis (2018-2022) of three selected NBFCs based on their Asset under Management (AUM), a key indicator of size and financial strength. The study evaluates short-term solvency, Leverage, profitability and earning capacity. Real Touch Finance Limited (RTFL) and Dharani Finance Limited exhibit consistent current ratios and favourable debt management. RTFL distinguishes itself with a positive trend in Return on Assets (ROA) and Return on Equity (ROE), reflecting its profit-generating ability. RTFL also excels in cost management, profitability, and interest-related earnings. All three NBFCs face challenges in profit generation. RTFL displays improved liquidity, long-term growth focus, a 6% rise in total revenue, but also a notable increase in administrative expenses. In summary, RTFL appears to be in a relatively stronger financial position compared to the others. However, its ability to manage cash effectively, make strategic investments, and address rising administrative expenses is pivotal for long-term financial stability and enhanced profitability. This study offers valuable insights for RTFL and other NBFC to identify opportunities for growth, potential threats, and areas for improvement for long-term success.

FinTech Adoption of Financial Services Industry: Exploring the Impact of Creative and Innovative Leadership

This paper examines the link between creative and innovative leadership and FinTech adoption through the transmission mechanisms of perceived ease of use (PEOU) and perceived usefulness (PU). This study used a questionnaire survey method to collect data from a sample of 721 employees working in the Indian financial services sector. The data were analyzed using structural equation modelling. The study results revealed a significant and positive influence of creative and innovative leadership, PEOU, and PU on FinTech adoption. Moreover, PEOU and PU mediated the link between creative and innovative leadership and FinTech adoption. This study proposes a new vision for managerial procedures to understand the critical aspects regarding FinTech adoption. The study advises that engineering managers should offer simple and user-friendly technology to enhance the adoption rate. Additionally, the results suggest the importance of creative and innovative leadership for competitively exploiting novel technologies. Given India’s digital revolution and huge market potential, the FinTech sector could prove a game-changer, especially in generating employment for the young and technologically qualified population. Tech-driven organizations could use the study findings strategically in this digital era.

Exploring Financial Health in India: Evaluating Risks for Sustainable Practices

Stakeholder theory is the foundation for environmental, social, and governance (ESG) factors, which are crucial for sustainable corporate operations. This study looks at the effects that various ESG risk levels have on Indian financial companies' financial performance. The Prowess IQ database provided the data for this investigation. The study found, in keeping with stakeholder theory, a substantial negative association between ESG risk and a company's return on equity and return on assets through the use of correlation analysis and linear regression. These results emphasise how crucial it is for businesses to concentrate on lowering ESG risks in order to increase profitability. This study fills a knowledge gap about the relationship between ESG characteristics and financial performance, particularly in the context of the Indian financial sector, due to the paucity of research in this field.

Lessons from outperformance in the Indian financial sector

AbstractWe examine predictions and outcomes for the Indian financial sector in the pandemic period to (i) build a case for re‐examining our understanding of the sector and (ii) improve risk perceptions and policy design. Reasons for outperformance include reforms that led to a better balance between discretion from public sector dominance and the excess volatility of market‐based systems. This diversity, as well as divergence of the Indian credit cycle from the global credit cycle, was protective given the sustained external risks. It put the sector in a position to support the domestic recovery, despite global quantitative tightening. Public sector banks contribute to diversity. Non‐bank financial companies reach the unbanked sectors and improve financial inclusion. Regulatory excesses and absence of liquidity support contributed to persistence of financial stress. Policy lessons are for countries to avoid policy over‐reaction, aim for diversity, different types of exposures, some uniformity in financial sector regulation, with the appropriate balance between discipline and support, in order to reduce risks. There are lessons from India's more broad‐based regulation for the narrow bank‐based regulation in advanced economies, which is increasing global financial fragilities and risks. The share of markets has risen so much there that diversity is falling.

Indian Post Payment Bank: Financial inclusion revolution in India

The Indian financial system has seen several significant changes since 1991. The banking industry is one of the few that has thrived sinceliberalization, and its success is unquestionably tied to the considerable financial reforms adopted by RBI and the significanttechnological improvements that have occurred over the years. In 2014, the Reserve Bank of India (RBI) broadened the variety of banksoperating inside the Indian financial sector. Payment banks and tiny banks are two names for these modern financial institutions. Themajor objective in creating these banks is to increase financial inclusion in underserved rural communities by increasing access tobanking goods and services. The unbanked and underbanked populations may be able to get access to financial services via paymentbanks, a new kind of financial institution. Expanding the availability of financial services is a top priority for them. In this paper, wediscuss the payment banking infrastructure and the benefits that are expected to accrue from it. The Post Payment Banks of Indianfinancial system will be a great first step in providing access to banking services for underserved populations, especially those who aretransient or from low-income families. Is the Indian Post Payment Bank the second phase of financial inclusion following the PradhanMantri Jan Dhan Yojana?This research aims to fill in some of the gaps in our understanding of payment banks by providing a high-leveloverview of their functioning processes and demonstrating how the idea of payment banks accomplishes two goals at once. All of theinformation in this study comes from secondary sources. As a starting step toward its financial inclusion strategy, it is increasing its digitalpayment infrastructure. The second positive effect is that it promotes a more tech-savvy mindset in the Indian banking industry. Theseresults show promise for increasing financial inclusion and access throughout India, especially in rural areas and with a focus on lowincomepeople and small businesses.Key words: Payment Banks, Financial system, Financial Inclusion, Post Payment Banks,

Self help groups, microfinance, financial inclusion and social exclusion: Insight from Assam

In order to link the unorganised with the formal financial sector in India, the National Bank for Agriculture and Rural Development (NABARD) introduced the Self-Help Group Bank Linkage Programme (SHG-BLP) as a trial initiative in 1992 and mainstreamed it in 1996. Microfinance services are available in Assam through SHG-BLPs registered with the Deendayal Antyodaya Yojana-National Rural Livelihoods Mission (DAY-NRLM). In central Assam, there are the most active SHG-BLP units. In light of this, the present study aims to explore contribution of SHG-BLP in financial along with the social inclusion of the marginalised rural people of central Assam. The impact of SHG-BLP is facilitated by the application of the propensity score matching method. The empirical results show that the SHG-BLP considerably reduces social exclusion among participants relative to their non-participant counterparts and ensures financial inclusion too. Based on this empirical finding, the study recommends that the coverage of SHG registration under DAY-NRLM be expanded. Simultaneously, efforts must be made to expand the alternative model of SHGs, the MFI-Bank Linkage Model, for expanding SHG coverage.

AN ANALYSIS OF BUSINESS RESPONSIBILITY AND SUSTAINABILITY REPORT OF SELECTED INDIAN COMPANIES

Investors and governments from all around the globe have been putting increased emphasis on the need for environmentally responsible finance. It would be useful to urge investors to study issues that go beyond risk and return since this would be beneficial. This would accomplish the goal of facilitating the growth of responsible investment, which would be beneficial. The advancement of the Indian market in the direction of a more sustainable environment would be beneficial to India's standing in the worldwide community. As a direct consequence of this, India's standing in the eyes of the rest of the world will improve. When it comes to making decisions about their finances, this would encourage customers to consider factors other than risk and reward. In the study titled "Business Responsibility and Sustainability Reporting," the authors explore five emerging organizations within the Indian financial sector and their approaches to corporate responsibility and sustainability reporting. Bajaj Finance Limited, IIFL Wealth Management Limited, Indiabulls Housing Finance Limited, Home First Finance Company India Limited, and Nahar Capital and Financial Services Limited are all represented in our investigation into the annual reports that each company prepares for this research, all of which are examined in considerable detail. The results of this study show that sustainable finance has become more prevalent throughout all India's financial sector. Additionally, the study highlights key policy changes and reforms that need to be done in the region to improve growing financial markets in the long term. This is done, in particular, to increase the area's attractiveness to potential investors. These adjustments and alterations to the system are emphasized in the study. The aforementioned changes and revisions are given great weight in the research.

An overview of anti-money laundering practice in the indian financial system

Money laundering is a menace to economies and a central concern globally. The financial system remains the primary target of money launderers. While the risk of money laundering cannot be entirely eliminated, it can be mitigated through specific preventative measures. In this regard, FATF took its initial international step by presenting its 40 recommendations to combat Money Laundering and Terrorist Financing. These recommendations have since evolved into a model for successful national and global Anti Money Laundering and Countering Financing of Terrorism (AML/CFT) controls. This paper aims to assess and describe the anti-money laundering (AML) practice and framework within the Indian financial system, as well as to examine how the Indian financial system has addressed FATF's recommendations on AML. The study utilizes secondary data obtained from books, annual reports, and selected websites to achieve its objectives. The findings of the study demonstrate that the Anti-Money Laundering (AML) regime in the Indian financial system is regulated by the Prevention of Money Laundering Act (PMLA) along with an established regulatory and supervisory framework to address FATF Recommendations. The AML framework of the Indian financial system includes FIU-India, which operates as a national agency for receiving, processing, analyzing, and disseminating information related to suspicious transactions. Additionally, the Reserve Bank of India (RBI), Securities Exchange Board of India (SEBI), and Insurance Regulatory Development Authority (IRDA) serve as the regulatory and supervisory bodies for financial institutions in India. Regulating, supervising, and developing Anti-Money Laundering (AML) policies and practices for the Indian financial sector fall under the responsibilities of these three authorities.

Machine Learning for Risk Compliance Automation in India’s Financial Sector

The automation of risk compliance through machine learning (ML) has become essential for Indian financial institutions to ensure adherence to regulatory standards. This paper explores the use of ML algorithms such as Decision Trees, Random Forest, and Support Vector Machines (SVM) to automate the process of risk compliance. The study evaluates how these algorithms can analyze large volumes of financial data to detect compliance violations, fraud, and money laundering activities. The research also examines the role of AI in enhancing transparency and reducing operational costs in the Indian financial sector.