Abstract: The financial sector is increasingly adopting automation and cloud based solutions to boost efficiency cut costs and enhance customer satisfaction. This report offers an examination of how AWS Step Functions and AWS Lambda can be used to streamline credit card approval processes. Traditional credit card approvals are often complicated time consuming and prone, to errors making it necessary to shift towards efficient, scalable and automated methods. AWS Step Functions facilitate the orchestration of AWS services, within serverless workflows while AWS Lambda enables the execution of code based on events without the requirement of server management. When combined these tools offer a platform for streamlining and enhancing business operations such, as credit card authorization processes. By integrating these services decision making speed and accuracy are improved scalability is. Essential security features are implemented for handling financial information. This analysis delves into the structure and advantages of AWS Step Functions and Lambda in the context of credit card approval procedures such as data validation, credit score calculations, fraud detection and decision making. It also examines real world case studies illustrating their application outlines practices for maximizing the benefits of serverless computing technology and touches on trends, like advanced machine learning models, edge computing advancements and enhanced security measures. By using these AWS services banks can enhance their effectiveness, scalability and security which in turn helps them better cater to customers and stay competitive in a changing market. The results highlight how serverless computing has the potential to revolutionize credit card evaluation procedures creating possibilities, for advancement and expansion within the sector.