Integrated Trading for Financial Services Company

Employees: 256,000+ 
Operating in: 100+ countries worldwide
Consumers served: millions
Industry: Financial Services
Asset management, Commercial banking, Consumer banking ,Wealth management
Goal: Migrate a legacy mutual fund application to transform investment strategies.

Business Problem/ Scope of Work

The Financial Services and Banking Company was facing a major business challenge with their legacy mutual fund application which was outdated and unable to keep up with the demands of the business and its customers. The current application had poor performance, scalability, and reliability. Additionally, the application lacked the necessary features and functionality to effectively manage client portfolios, such as the ability to place buy, sell, or exchange orders. This was causing a major problem for the mutual fund managers to serve their clients effectively.
To address this challenge, Pronix IT Solutions team was engaged to modernize and upgrade the legacy application. The goal was to provide a more efficient and user-friendly platform for portfolio management, which will enable the mutual fund managers to better serve their clients and improve their business performance.


Business Solution

The business solution for this case study is to migrate the legacy application to a new, modern system known as CONNECT app. The CONNECT app will replace the three legacy applications (PBA-Private Banking only US region, JPMA -US Based Trading of own security mutual funds, IPB-International Private Bank) into a single application. This will provide better user experience by having different lines of business (LOBs) instead of users accessing the whole application. Based on user access, specific LOBs will be redirected. The new system will also provide a new user interface design solution for easy graphical user interface (GUI). To ensure continuity of service during the migration, the legacy application will be maintained until the new application is ready to go live.


Technical Solutions

Integrated Trading Application
The technical solution for this case study includes the implementation of React JS, Forms, Events, Keys, Router, and custom reusable React components. A reusable component library was created and application state was managed using Redux. React functions, reducers, and actions were created for state management using Redux. Jest framework was used for creating test cases for React components.
Webpack was used as a module bundler and Babel was used for compiling and building a component-based React architecture. SASS preprocessing was used for configuring tasks. Spring JDBC custom queries were utilized to save and update the database using REST API from UI operations such as adding and deleting. REST API endpoints were created for end-users to perform create, update, delete operations through the frontend to the database via Axios API calls to the React frontend. Kafka producer and consumer applications were implemented on a Kafka cluster setup with the help of Zookeeper.
Spring Kafka API calls were used to process messages smoothly on the Kafka cluster setup. RESTful resources were developed using Rest Template and consumed REST from various vendors. Completable Future was implemented using Java 8 for parallel calls for microservices. Spring config server was used for centralized configuration and Splunk was used for centralized logging.
Concourse and Jenkins were used for Microservices deployment. Swagger UI (JSON/YAML) was integrated and integration tests were written along with REST documentation.

Technologies/ Skills Used

The case study for "Integrated Trading Mutual Funds, Morcom Trading, e-Ticketing to Financial Services and Banking Company" implemented by Pronix IT Solutions team, utilized a variety of technologies to achieve the desired outcomes.
The primary programming language used was Java 1.8, with React 16.x for building the user interface. The project also utilized SpringBoot2.X for creating the backend services and GIT for version control. SpringBatch4.X was used for batch processing, Jest 21.2.1 for testing, and redux and redux-thunk for state management.
Jenkins(Jules) was used for continuous integration and delivery, and Kafka was used for handling real-time data streams. The team also used Swagger for API documentation and testing.
These technologies were carefully selected and integrated by the Pronix IT Solutions team to achieve the desired outcomes and improve the overall performance of the financial services and banking company's trading and e-ticketing operations. The use of these technologies demonstrates the team's expertise in utilizing the latest and most appropriate tools to deliver effective solutions to clients

Customer Success Outcomes

Integrated Trading for Financial Services Company Customer Success Outcomes

Increased Revenue: By streamlining the trading process and improving the accuracy of data, the integrated trading system helped the financial services company to generate more revenue by 20% increase.

Improved Efficiency: The new integrated trading system allowed the company to process trades more quickly, reducing the time required to complete trades from hours to minutes by 40%.
Faster Trading Processing Time: The new system allowed the company to process trades more quickly, reducing the time required to complete trades from hours to minutes by 50% improvement in processing time for trades.
Increased Data Accuracy: The new integrated trading system provided the company with more accurate and reliable data, reducing the likelihood of errors and discrepancies in trading by 25% improvement in data accuracy for trading.
Cost Savings: By integrating its trading systems, the company was able to reduce its overall operational costs by 15%.
Improved Customer Satisfaction: The new integrated trading system allowed the company to provide its customers with faster and more reliable trading services, improving their overall satisfaction by 20%.
Improved Compliance: The new integrated trading system allowed the company to meet regulatory requirements more efficiently and accurately, reducing the risk of non-compliance by 30%

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