Developing a microservice solution for automated investment monitoring in Wealth Management

The thesis focuses on the development of a backend software application built during an internship at Alpian Technologies, to work as a back-office solution for a specialized team at Fideuram Asset Management. The main aim of the application is to automate and optimize the periodic monitoring of discretionary mandates, which denotes an investing strategy whereby a client delegates to a bank the management of their portfolio. This monitoring ensures that investment strategies applied to the customers at the bank remain aligned with the agreed-upon risk profiles. The important contributions of the project include the automation of a critical monitoring procedure once done manually and subject to inefficiencies and a greater potential for errors. By bringing in cutting-edge technologies like Spring Boot for REST services, gRPC for efficient service communication, Kotlin for reliable backend development, and Docker for containerized deployments, the project improved the accuracy and efficiency of investment compliance processes. The implementation of the microservices structure, in addition to the CI/CD pipelines guarantees the scalability, maintainability, and continuous improvement of the platform. It should also be noted that the monitoring and management of investment data in one place make for much more ease of access to and use by the working part of this software, thus substantially enhancing the workflow and possibility to maintain investments compliant. This thesis provides evidence of the successful application of modern software technologies to the financial sector, making the case for the possibilities of automation, the digital transformation and enhancement of the monitoring of investment portfolios. Results reflect the impact of this work, which includes lowering operational workload, enhanced compliance efficiency, high level of testing employed, and ultimately providing a scalable solution for further expanding into other areas of investment management. The project has laid the groundwork for future improvements involving real-time monitoring, further automation, and enhanced data integration capabilities.