DYNAMIC PRICING IN FINANCIAL TECHNOLOGY: EVALUATING MACHINE LEARNING SOLUTIONS FOR MARKET ADAPTABILITY

The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competitiveness. In this context, machine learning algorithms provide a powerful framework for making data-driven pricing decisions by learning from historical data and predicting future trends.