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