Year: 2025
Type: article
Abstract: Foreign exchange volatility is a risky situation for multinational corporations, especially those with large global supply chains and multi-market operations. Asian Paints, being among the largest Indian paint manufacturers with extensive global reach, is significantly vulnerable to currency fluctuations due to raw material importation, foreign subsidiary operations, and cross-border transactions. Factual management of forex exposure is therefore vital in a bid to safeguard profitability, ensure price stability, and ensure competitiveness. The current research examines how predictive analytics can enhance forex risk management by Asian Paints. Predictive analytics, powered by strong data modeling, enables organizations to forecast currency movement, identify volatility patterns, and make timely hedging choices. The study critically assesses how data-driven forecast tools enhance the decision-making process for forward contracts, options, and natural hedging instruments. With predictive models, Asian Paints can shift from passive to active risk hedging, minimizing unexpected losses and enhancing the accuracy of financial planning. The study also addresses topics like model dependability, quality of data, and the integration of predictive data in current treasury procedures. In addition, the study finds the strategic advantages of predictive analytics in enabling corporate governance, risk management prioritization towards long-term business goals, and building resilience in unstable global financial environments. Overall, the current research affirms that predictive analytics has the potential to deliver Asian Paints a sustainable competitive advantage in terms of increased financial solidity, operational efficiency, and wellinformed strategic decisions.
Authors: Batani Raghavendra Rao, Keshav Kumar, Meenu Sharma, Khushi Chopra, Krishnakumar S, Manas Milind Bagewadi, Muhammad Thameem N K, Muhammed Shamal
Institution: Jain University
Language: English
Subfield: Accounting
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4414926198
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