A Study on Blockchain Technology as a Dominant Feature to Mitigate Reputational Risk for Indian Academic Institutions and Universities

The paper-based certification is prone to manipulation and vulnerable to fraud. Instances of fraudulent degrees, manipulation of academic records, or compromised academic programs adversely impact and damage an academic institution's credibility. It also affects the Indian universities’ mission and prospects of the students graduating from such a university. What makes reputational risk a unique risk is that it may arise both from the university or institution's failure or the action outside the university. It is, therefore, essential to take an enterprise risk management approach to mitigate reputational risk. Robust credential verification and validation protocols are the most important protections against fake certifications. The legacy certificate verification solutions are highly centralized, i.e., utterly dependent on the issuing authority for certificates. Despite the University Grants Commission (UGC) taking strict measures against individuals, Indian universities, colleges, and associations, we do come across several acts of torts. Some of the technology-savvy institutions have moved to digital certificates and digital signatures. However, this has an inherent weakness, i.e., they still need to rely on a trusted third party. Blockchain technology has three foundational components, data structures based on cryptography that make it secure and tamperproof, consensus protocols that allow it to function truthfully and without any central authority or a third party smart contracts, which provide efficiency and business value transactions. These key features of blockchain, if implemented appropriately, effectively has the potential to mitigate the inherent reputational risk arising from fraudulent academic certificate matters. Niti Ayog is currently developing a blockchain-based proof of concepts to solve traditional educational qualifications related to identity misrepresentation and document forgery. The immutability attribute of the blockchain ensures that tampering and manipulation of the record are not attainable. This paper focuses on the reputational risk Indian universities and institution may face when its certifications are not easily verifiable. Therefore, it becomes easy targets for bad actors to exploit vulnerabilities by issuing counterfeit certificates. Secondary published data, including various scholarly journals, reports, industry publications, and website sources, are utilized to develop this case study. The paper also explores how blockchain technology with specific reference to the proof of concept SuperCert proposed by Niti Ayog for Indian academic institutions may provide effective preventive control to overcome such reputational risk using the ABCD analysis framework as a research case study

Academic Institutions Risk Decisions using Six Thinking Hats based Analysis

Today, almost everyone faces extraordinary health, social, and economic risk due to the COVID-19 pandemic. As for all industries, academic institutions face unprecedented challenges and are witnessing the change in short-and long-term risk profile due to COVID-19, e.g., enhanced information and cybersecurity risk due to the adoption of new collaboration tools, deterioration in the effectiveness of traditional fraud risk mitigants as enrollment and document verifications over email, and increased risk of financial viability. In addition to having a robust risk management framework, it is critical for the institutions to carefully recognize and mitigate these emerging risks, which may have long-term implications on the institution's academic performance and perpetuity. Educational institutions, therefore, must adopt a broad spectrum of thinking methods that allow a practical framework for risk decisions and provide a strong foundation for academic institutions to function and enforce strategies both throughout and after the COVID-19 period. With the help of an example, this paper explores how "Six Thinking Hats" may serve as a decision aid and facilitate the risk decisions in an academic institution around risk appetite, risk identification, risk assessment, control design, and risk monitoring. The "Six Thinking Hats" or colors are all about gaining direction, i.e., what can happen (threat and opportunities; effect and probability) and not merely about explaining the event, what is or what has happened. Risk management being forward-looking, this is a significant risk decision consideration. The paper also analyzes the "Six Thinking Hats" method using the ABCD analysis framework as a research case study

A Study on Blockchain Technology as a Dominant Feature to Mitigate Reputational Risk for Indian Academic Institutions and Universities

The paper-based certification is prone to manipulation and vulnerable to fraud. Instances of fraudulent degrees, manipulation of academic records, or compromised academic programs adversely impact and damage an academic institution's credibility. It also affects the Indian universities’ mission and prospects of the students graduating from such a university. What makes reputational risk a unique risk is that it may arise both from the university or institution's failure or the action outside the university. It is, therefore, essential to take an enterprise risk management approach to mitigate reputational risk. Robust credential verification and validation protocols are the most important protections against fake certifications. The legacy certificate verification solutions are highly centralized, i.e., utterly dependent on the issuing authority for certificates. Despite the University Grants Commission (UGC) taking strict measures against individuals, Indian universities, colleges, and associations, we do come across several acts of torts. Some of the technology-savvy institutions have moved to digital certificates and digital signatures. However, this has an inherent weakness, i.e., they still need to rely on a trusted third party. Blockchain technology has three foundational components, data structures based on cryptography that make it secure and tamperproof, consensus protocols that allow it to function truthfully and without any central authority or a third party smart contracts, which provide efficiency and business value transactions. These key features of blockchain, if implemented appropriately, effectively has the potential to mitigate the inherent reputational risk arising from fraudulent academic certificate matters. Niti Ayog is currently developing a blockchain-based proof of concepts to solve traditional educational qualifications related to identity misrepresentation and document forgery. The immutability attribute of the blockchain ensures that tampering and manipulation of the record are not attainable. This paper focuses on the reputational risk Indian universities and institution may face when its certifications are not easily verifiable. Therefore, it becomes easy targets for bad actors to exploit vulnerabilities by issuing counterfeit certificates. Secondary published data, including various scholarly journals, reports, industry publications, and website sources, are utilized to develop this case study. The paper also explores how blockchain technology with specific reference to the proof of concept SuperCert proposed by Niti Ayog for Indian academic institutions may provide effective preventive control to overcome such reputational risk using the ABCD analysis framework as a research case study

Academic Institutions Risk Decisions using Six Thinking Hats based Analysis

Today, almost everyone faces extraordinary health, social, and economic risk due to the COVID-19 pandemic. As for all industries, academic institutions face unprecedented challenges and are witnessing the change in short-and long-term risk profile due to COVID-19, e.g., enhanced information and cybersecurity risk due to the adoption of new collaboration tools, deterioration in the effectiveness of traditional fraud risk mitigants as enrollment and document verifications over email, and increased risk of financial viability. In addition to having a robust risk management framework, it is critical for the institutions to carefully recognize and mitigate these emerging risks, which may have long-term implications on the institution's academic performance and perpetuity. Educational institutions, therefore, must adopt a broad spectrum of thinking methods that allow a practical framework for risk decisions and provide a strong foundation for academic institutions to function and enforce strategies both throughout and after the COVID-19 period. With the help of an example, this paper explores how "Six Thinking Hats" may serve as a decision aid and facilitate the risk decisions in an academic institution around risk appetite, risk identification, risk assessment, control design, and risk monitoring. The "Six Thinking Hats" or colors are all about gaining direction, i.e., what can happen (threat and opportunities; effect and probability) and not merely about explaining the event, what is or what has happened. Risk management being forward-looking, this is a significant risk decision consideration. The paper also analyzes the "Six Thinking Hats" method using the ABCD analysis framework as a research case study

Academic Institutions Risk Decisions using Six Thinking Hats Based Analysis

Today, almost everyone faces extraordinary health, social, and economic risk due to the COVID-19 pandemic. As for all industries, academic institutions face unprecedented challenges and are witnessing the change in short-and long-term risk profile due to COVID19, e.g., enhanced information and cybersecurity risk due to the adoption of new collaboration tools, deterioration in the effectiveness of traditional fraud risk mitigants as enrollment and document verifications over email, and increased risk of financial viability. In addition to having a robust risk management framework, it is critical for the institutions to carefully recognize and mitigate these emerging risks, which may have long-term implications on the institution's academic performance and perpetuity. Educational institutions, therefore, must adopt a broad spectrum of thinking methods that allow a practical framework for risk decisions and provide a strong foundation for academic institutions to function and enforce strategies both throughout and after the COVID-19 period. With the help of an example, this paper explores how "Six Thinking Hats" may serve as a decision aid and facilitate the risk decisions in an academic institution around risk appetite, risk identification, risk assessment, control design, and risk monitoring. The "Six Thinking Hats" or colors are all about gaining direction, i.e., what can happen (threat and opportunities; effect and probability) and not merely about explaining the event, what is or what has happened. Risk management being forward-looking, this is a significant risk decision consideration. The paper also analyzes the "Six Thinking Hats" method using the ABCD analysis framework as a research case study

Literature Survey and Research Agenda of Risk Determinants in Indian Equities and Machine Learning

Notwithstanding the financial slowdown and severity of the Coronavirus pandemic during 2020, several retail investors ventures directly to the secondary equities market, setting off gigantic purchasing. A review of SEBI data indicates that over 6 million new dematerialization accounts between April and September 2020 are about 125 percent growth on year on year basis. At the same time, data reported by AMFI shows net outflows from equity funds by retail investors. These data points indicate that retail investors may have opted to invest using direct stock investments instead of relying on the equity mutual fund manager. Equity Investment is a dynamic process requiring and require considering different variables in selecting and, more importantly, avoiding stocks. The cornerstone of wealth creation is to invest in stores at a price considerably smaller than their intrinsic value. The very foundation of creating long-term wealth using equities is deeply embedded. One is buying businesses at a price substantially below its intrinsic value (intrinsic value indicates the entity's future cash flows after estimating the number of accounting risk, macro-economic, managerial, and behavioral risk determinants). This Literature review, therefore, is organized to cover Behavioral, Accounting, Macro-economic, Volatility, and Management theories and Forecasting and ML techniques for clustering, predictions, and classification to support risk decisions using different models, e.g., ARIMA, LSTM, VAR, Facebook Prophet, ARCH and GARCH family models, etc. The literature review also establishes that the concept of risk is highly subjective and is perceived by different investors differently; it is not always entirely objective and outside the beliefs, cognitive and socio-cultural considerations requiring careful assessment before making investment decisions. However, examining the critical risk indicators would allow investors to make a more informed decision. The research gap and identified agenda for further review were defined and assessed using valuable ABCD and SWOT management frameworks. Consequently, the literature investigation findings are analyzed by offering recommendations for creating a comprehensive research agenda pertinent to long-term equity investors in the Indian Equity market

A Study on Blockchain Technology as a Dominant Feature to Mitigate Reputational Risk for Indian Academic Institutions and Universities

The paper-based certification is prone to manipulation and vulnerable to fraud. Instances of fraudulent degrees, manipulation of academic records, or compromised academic programs adversely impact and damage an academic institution's credibility. It also affects the Indian universities’ mission and prospects of the students graduating from such a university. What makes reputational risk a unique risk is that it may arise both from the university or institution's failure or the action outside the university. It is, therefore, essential to take an enterprise risk management approach to mitigate reputational risk. Robust credential verification and validation protocols are the most important protections against fake certifications. The legacy certificate verification solutions are highly centralized, i.e., utterly dependent on the issuing authority for certificates. Despite the University Grants Commission (UGC) taking strict measures against individuals, Indian universities, colleges, and associations, we do come across several acts of torts. Some of the technology-savvy institutions have moved to digital certificates and digital signatures. However, this has an inherent weakness, i.e., they still need to rely on a trusted third party. Blockchain technology has three foundational components, data structures based on cryptography that make it secure and tamperproof, consensus protocols that allow it to function truthfully and without any central authority or a third party smart contracts, which provide efficiency and business value transactions. These key features of blockchain, if implemented appropriately, effectively has the potential to mitigate the inherent reputational risk arising from fraudulent academic certificate matters. Niti Ayog is currently developing a blockchain-based proof of concepts to solve traditional educational qualifications related to identity misrepresentation and document forgery. The immutability attribute of the blockchain ensures that tampering and manipulation of the record are not attainable. This paper focuses on the reputational risk Indian universities and institution may face when its certifications are not easily verifiable. Therefore, it becomes easy targets for bad actors to exploit vulnerabilities by issuing counterfeit certificates. Secondary published data, including various scholarly journals, reports, industry publications, and website sources, are utilized to develop this case study. The paper also explores how blockchain technology with specific reference to the proof of concept SuperCert proposed by Niti Ayog for Indian academic institutions may provide effective preventive control to overcome such reputational risk using the ABCD analysis framework as a research case study

A Panel Data Analysis of Stock Returns and Accounting Information in Indian Paint Industry

The accounting ratios and published financial information serve as a critical tool for investors, creditors, and other stakeholders to ascertain companies' profitability, control, and financial status, which may significantly impact the Stock returns and performance on exchanges. This paper aims to examine whether crucial accounting information affects the price of paint companies in India. In this paper, nine-years (2012-2020) accounting ratios such as returns on asset, equity, and cash cycles for the five listed paint companies in India as explanatory (independent) variables to estimate stock returns. Secondary data is collected chronologically and at a regular yearly frequency. Variables data are derived from the company’s financial statements, Stock Exchange and related website. The study aims to assess and elaborate these accounting ratios effectiveness to substantiate the stock returns of these listed companies. The study uses three-panel data models, the pooled OLS, fixed and random effects, to assess stock returns for the cross-sectional data of these five paint companies. This research indicates that accounting information is significant and positively affects the price of Paint company stock returns on the stock exchange. Both Fixed and Random effect model found to fit the data, significance level of 0.05 (Fixed (FE) at F= 6.3625, p<0.000 and R2 of 0.5462, i.e., fixed effect elaborates for about 55% of the return variance. Random effect at F=10.8647 and p<0.000 and R2 of 0.4429, i.e., elaborates for about 44% of stock return variance. Based on the Hausman data test alternative hypothesis is found to be consistent and therefore Random Effect (RE) model is being used to conclude the findings. The paper's fundamental limitation includes use of limited regressors, companies, and time period. A further qualitative analysis together with other accounting performance indicators as regressors may be included in future studies. These ratios include interest coverage, debt ratios, effective tax rates, asset turnover ratios, dividend distribution ratios, sustainable growth, and top line revenue growt