Current Volume 9
The complexities of financial risk management are increasing, given the modern-day business environment. That is to say, with evolving markets, technology, and globalization, businesses are affected. For organizations, they face multiple financial risks that include credit risk, market risk, liquidity risk, operational risk, etc. All of these can impact the operations of the organization significantly. The use of data analytics in risk assessment compensates for potential biases that otherwise distort behaviour and choices in decision-making processes. The selected company is based on Pune PR Tech Pvt. analysis of sdata analytics for risk assessment and financial stability. Pvt. Ltd., Nagpur. In this paper, a theoretical and conceptual investigation is presented on how predictive analytics, machine learning algorithms and big data frameworks can aid the identification of financial risk and organizational resilience. Through data analytics, companies can process huge amounts of data which may be structured or unstructured. Also, they can identify patterns and derive insights from them. The implementation of data-driven risk management practices boosts financial stability by enhancing forecasting accuracy and reducing the impact of uncertainties related to financial crisis. The integration of analytical technologies into financial management systems is critical for growth and gaining a competitive edge.
Risk Assessment, Financial Stability, Data Analytic, Predictive Analytic, Machine Learning, Big Data Analytic, Financial Risk Management, Decision Making System
IRE Journals:
Darshika Sanjay Makode, Prof. Abhijeet Gajbhiye "A Study on Risk Assessment and Financial Stability Analysis Using Data Analytics in PR Tech Pvt, Nagpur" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 3547-3554 https://doi.org/10.64388/IREV9I10-1716972
IEEE:
Darshika Sanjay Makode, Prof. Abhijeet Gajbhiye
"A Study on Risk Assessment and Financial Stability Analysis Using Data Analytics in PR Tech Pvt, Nagpur" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716972