Ramakrishna Ramadugu | Osmania University (original) (raw)

Papers by Ramakrishna Ramadugu

IJCRT, 2022

The study aimed a) to evaluate the influence of AI-based security systems on customer trust and p... more The study aimed a) to evaluate the influence of AI-based security systems on customer trust and perception
of safety in fintech services, b) to analyze the impact of AI-driven security features on customer satisfaction
levels in fintech-based companies, and c) to explore the correlation between AI-based security measures and
customer retention rates in fintech companies. The study aimed at consumers of fintech firms and was
undertaken in the Delhi NCR region with a stratified random sampling method to get respondents. The
target population consists of 200 participants for the study. The study is descriptive and experimental.
Primary data is gathered employing a questionnaire and secondary data is collected from journals, books,
articles, reports, etc. Data collected are analyzed using statistical tools including the use of frequency tables,
mean, standard deviations, correlation, and regression by use of MS Excel and SPSS. The findings
underlined how AI-based security systems transform the essential elements of customer satisfaction and
engagement in fintech companies. Also, it has been found that there is a moderate positive relationship
between the usage of advanced safety techniques based on AI and the customers’ retention percentages,
which confirms the role of these remedies in creating customer satisfaction, engagement, and loyalty.
Keywords: Artificial Intelligence (AI), Customer Satisfaction, Customer Engagement, Customer
Relationship Management (CRM), and FinTech Compan

INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG), 2024

The study aimed to examine how artificial intelligence (AI)-powered security systems enhance cust... more The study aimed to examine how artificial intelligence (AI)-powered security systems enhance customer
trust and engagement in Forex (FX) Trading platforms, the study also mark the effectiveness of AI
technologies in mitigating security threats on FX platforms, and explore the role of AI in ensuring
regulatory compliance and transparency, thereby fostering a more secure trading environment. The study
used both qualitative and quantitative data. Empirical in nature, the study focuses on the users of trading
platforms engaged in Foreign Exchange (FX) dealing in the Delhi NCR region. The study uses descriptive
and exploratory research design and provides a target population of 250 respondents. A structured
questionnaire is employed as the main source of data collection to address the research questions. The data
is analyzed by statistical tools such as MS Excel and SPSS, using mean, S.D., correlation, regression, etc.
The study showed that there is a clear positive correlation between the level of incorporation of AI security
systems and the level of customer engagement, with AI technologies accounting for an important share of
the variation in security threat prevention. Also, the study confirmed the role of AI in compliance and
openness, which exhibits a moderate positive relationship between them.
Keywords: Artificial Intelligence, Customer Trust, Customer Engagement, Cyber Security, and Forex (FX)
Trading Platforms.

Turkish Online Journal of Qualitative Inquiry (TOJQI), 2020

The volatility of global currency markets presents a major challenge to firms engaged in cross-bo... more The volatility of global currency markets presents a major challenge to firms engaged in cross-border payments with foreign exchange (FX) risk. This study examines different FX risk management strategies, and specifically the effectiveness of hedging instruments, i.e., options, futures, and forward contracts, in reducing currency exposure. A study of major currency pairs from 2015 to 2019 shows that EUR/GBP and USD/GBP pairs are highly volatile, mainly influenced by geopolitical factors such as Brexit. Results are quantified and show that options contracts are the best at mitigating FX risk, reducing exposure by an average of 31.8%, followed closely by futures and forward contracts. Smaller risk reduction is provided by natural hedging, an imperfect solution but indicating the need for a diversification approach. The firms that did not use any hedging strategies had higher exposure to FX risk. Interviews of firms reveal that hedging is effective, but that cost and operational complexity may inhibit some firms from using these strategies. In general, the study emphasizes the need to adopt a comprehensive FX risk management framework that incorporates financial instruments and natural hedging to stabilize the financial condition in cross-border transactions.
Keywords: Cross-border payments, Hedging strategies, Currency volatility, FX exposure, Options contracts, Forward contracts.

Educational Administration: Theory and Practice, 2024

This study examines the ethical and regulatory challenges influencing the adoption of ge... more This study examines the ethical and regulatory challenges influencing the adoption of generative AI in the banking sector. Qualitative findings identified key concerns such as data bias in loan approvals, the explainability of AI decisions, and the tensionbetween innovation and operational risk control. Quantitative results revealed that regulatory non-compliance (mean = 4.8, SD = 0.2) and data privacy risks (mean = 4.7, SD = 0.3) are the most significant concerns. Other identified risks include bias and fairness issues (mean = 4.5, SD = 0.4), lack of transparency (mean = 4.6, SD = 0.3), and customer trust erosion (mean = 4.3, SD = 0.5). The analysis demonstrated a 35% reduction in AI adoption speed due to regulatory constraints, with a Pearson correlation coefficient of -0.62, indicating a strong negative relationship between regulatory barriers and innovation pace. Regression results further highlighted that data privacy measures (β = 0.55, p < 0.001) and customer trust (β = 0.37, p = 0.01) positively influence AI adoption, while regulatory complexity (β = -0.45, p = 0.002) negatively impacts it. These findings emphasize the need for enhanced governance frameworks that balance innovation, ethical considerations, and compliance to unlock the full potential of generative AI in the financial sector.Keywords: Generative AI, Banking Sector, Regulatory

TechRxiv, 2024

This study contributes to the ongoing discourse about the resilience of financial institutions by... more This study contributes to the ongoing discourse about the resilience of financial institutions by assessing whether actions related
to capital policy in Europe contribute to systemic risk. Using a versatile hierarchical framework, I estimate systemic risk and
evaluate the multi-level effects of capital policy measures across Europe and over time. This probabilistic approach yields
a hierarchy of implications for systemic risk due to capital policy measures for each of the 21 European countries over 83
quarters. I specifically examine tightening, loosening, and unclear policy measures in the dataset. My findings uncover that the
accumulation of tightening policy actions inadvertently leads to an increase in system risk by 1 to 10 quarterly percentage points
at the bank level. When considering the intra-national probability of ’random effects,’ institutions in Greece, Ireland, and the
United Kingdom seem to contribute to heightened systemic risk. My results indicate that capital adequacy regulation could
inadvertently heighten systemic risk. This unintentional correlation may arise from various smaller institutions collectively
amplifying systemic risk dynamics by investing in similar asset classes to adhere to capital rules.

Journal for ReAttach Therapy and Developmental Diversities, 2023

There are so many digital wallets, like PayPal, Google Pay, and Apple Pay, we have started transa... more There are so many digital wallets, like PayPal, Google Pay, and Apple Pay, we have started transacting money in a completely different way. That said, with the growing popularity of digital wallets, fraud is increasing, which is becoming a mammoth task to secure users’ sensitive financial data. Rule-based systems, which are traditionally used for fraud detection, have failed to fight complex fraud schemes. In this work, we investigate the use of artificial intelligence (AI) and machine learning (ML) to enhance the security of digital wallets by studying their capacity to detect and prevent fraudulent transactions. Various AI/ML models were tested including Random Forests and Recurrent Neural Networks (RNNs), and results show that these models greatly increase fraud detection accuracy and decrease false positives. It compares AI/ML models with traditional fraud prevention techniques and shows that AI/ML models adapt to changing fraud patterns much more swiftly. Although AI/ML models give promising results, theimplementation is not effective due to computational costs, false positives, and issues with data privacy. The research reveals that deploying AI/ML-based fraud detection systems within the business can enhance the security of digital wallets by a significant amount.Keywords: Artificial intelligence, machine learning, fraud detection, PayPal, Google Pay, Recurrent Neural Networks (RNNs), Random Forests, cybersecurity, financial security

Journal of Population Therapeutics & Clinical Pharmacology , 2022

Background: Financial technology (fintech) has evolved rapidly, changing the global financial lan... more Background: Financial technology (fintech) has evolved rapidly, changing the global financial
landscape consumer behavior, and institutional operations. This study looks at the adoption of key
fintech technologies like blockchain, artificial intelligence (AI), and mobile payments, based on trends
before 2021.
Methods: The approach was mixed methods, using quantitative data from surveys of 150 fintech
stakeholders across North America, Europe, and Asia, and qualitative insights from literature reviews
of industry reports and financial data from 2015 to 2020.
Results and Discussion: The research shows that mobile payment systems are adopted by 78% of
people, mostly in Asia, and North America leading to AI usage at 62%. Overall, fintech adoption led
to an average 15% revenue growth for firms, a 20% increase in customer retention, and a 17%
decrease in fraud-related losses. Regulatory compliance and consumer trust were the biggest
challenges for 62% and 30% of respondents, respectively. The study also shows regional differences
in fintech adoption strategies, and that institutions need to address regulatory complexities and build
consumer confidence to promote wider adoption.
Conclusion: With the further evolution of fintech technologies, those in financial institutions need to
understand what will influence the adoption of these technologies, and address identified challenges
in this study, to effectively leverage these innovations. More research continues to be needed to further
study the long-term effects of fintech on financial stability and consumer conduct.
Keywords: Financial Technology, FinTech, Technology, Global Financial Landscape, economy

European Chemical Bulletin, 2021

The rate of service and the satisfaction of customers relative to available biometric and passwor... more The rate of service and the satisfaction of customers relative to available biometric and password-based technologies. In this study, the traditional PIN/password inputs were contrasted with the biometric techniques of fingerprint, iris, face, and voice scans. Success rate indicates that iris scanning has a much higher success rate of 99.1% and a shallow failure level of 0.9%, closely followed by fingerprint authentication which had 98.7% success. Of all the biometric methods voice recognition gave the lowest results with only 95.2% accuracy and averaging (2.4) seconds for the authentication process. User satisfaction was highest for fingerprint (ease of use (4.8), security (4.6), overall satisfaction (4.7), iris scanning, and PIN/password getting the lowest mark in ease of use (3.9). Biometric authentication methods used in the study showed higher accuracy and user-friendliness than the PIN/password method.
Keywords: Finger scan, Fingerprint validation, Tears, Face recognition, Voice recognition, PIN, Customer satisfaction, Efficiency rate