From 5 Days to 40 Minutes! MDBS Invited to IBM Hands-on Experience Camp, Demonstrating the Efficiency of AI in Real-World Implementation

Having long served clients in the financial industry, MDBS thoroughly understands the rigorous standards financial systems demand regarding security, stability, and maintenance efficiency.

Take the routine security scans conducted by financial clients as an example. Whenever scan results flag vulnerabilities to patch or packages to upgrade, engineering teams typically have to verify legacy APIs one by one, adjust dependencies, modify code, and rerun tests. In the past, this type of upgrade work usually took about five working days to complete.

This experience allowed the team to gain a more tangible understanding of the value AI Agents bring to the software development lifecycle (SDLC). AI is no longer merely a tool for speeding up code generation; it can proactively assist with task planning, code modification, test execution, and self-verification of its own outputs.

In addition to exchanging past experiences, MDBS’s engineering team focused on the live development of a "Credit Card Transaction Monitoring System" during the workshop.

The team simulated common anomaly detection requirements in financial transaction scenarios—including monitoring logic for high-value transactions, high-frequency transactions, and duplicate transactions. They further completed data model design, API development, frontend monitoring interface creation, and security check processes, successfully validating the potential of AI-assisted development in enterprise-grade systems.

With the support of IBM Bob, MDBS verified the collaborative value of AI in areas such as code structure analysis, modular development, query logic implementation, security rule checks, and the establishment of team development standards.

The application of IBM Bob goes far beyond code writing. It can be extended to a wide range of technical pain points commonly faced by financial clients, such as system upgrades, security vulnerability patches, SQL query troubleshooting, user permission management, legacy system refactoring, and monitoring dashboard development. Tasks that previously relied heavily on human experience and required substantial time can, in the future, be handled much more efficiently through AI Agent collaboration.

Looking ahead, MDBS will continue to closely follow the development of AI engineering tools and enterprise-grade applications. By combining its practical experience in fintech, system development, and digital transformation, MDBS aims to help enterprises build technical solutions that are more efficient, secure, and maintainable.