Authors: Mollah Mohammad Mahabubuzzaman
Abstract: The FinTech industry, which works mainly with digital tools, deals with a lot of transactions and new financial products.This environment brings a number of different and complex risks. Traditional risk management methods, which are based on fixed predictions, are often not enough to handle the unpredictable nature of these digital systems. This paper argues that using stochastic finance gives the best foundation for a strong, consistent, and forward-thinking risk management system in the FinTech industry. We show how tools like Geometric Brownian Motion, Poisson processes, Monte Carlo simulations, and machine learning to spot unusual activity can be used in six main risk areas: credit card fraud, market risks, money liquidity issues, IT and operational problems, transaction risks, and stopping money used for terrorism. We also look at how it helps with keeping enough cash on hand. The study shows that using a stochastic approach is not just helpful but necessary for FinTech companies to handle uncertainty, follow rules, stay stable, and build a lasting competitive edge.
