Customer Profile: Jiangsu Bank is a well-known commercial bank in China, providing a wide range of financial products and services for individuals and enterprises. The bank has always been committed to using innovative technologies to enhance customer engagement and promote the popularization of its banking products. On the path of digital transformation, Jiangsu Bank is committed to enhancing its marketing efforts through a digital marketing platform that integrates social, financial and gamification elements, thereby attracting and retaining customers. Project Background: In response to the increasingly fierce competition in the financial industry and the growing demand for personalized services, Jiangsu Bank has decided to develop financial products and services for a digital marketing platform. The main goal of this platform is to build a customer base, or “customer pool”, by providing unique financial products and services, gamified experiences and social interaction functions. The platform needs to combine innovative marketing strategies with a user-friendly interface to ensure customer engagement, enhance brand loyalty, and drive revenue growth. This project aims to integrate various financial services such as wealth management, equity-based financial products, and social finance, and build a digital ecosystem that enables users to participate in financial activities, share products, engage in interactive

Customer Profile: The Agricultural Development Bank of China (CADB) is a state-owned commercial bank in China, mainly dedicated to providing financial services for the agricultural sector. This bank plays a crucial role in supporting the economic development of rural China by providing loans and financial products for farmers, enterprises and rural development projects. CADB is committed to improving its financial management processes to ensure the stability and growth of its business. Project Background: In order to enhance the accuracy and efficiency of financial management and risk control, the Agricultural Development Bank of China recognizes the need for an advanced asset-liability management (ALM) system. The ALM system has the capabilities of liquidity management, cash flow prediction, and scenario modeling. By implementing this system, the Agricultural Development Bank of China strives to ensure that its asset-liability management process is more accurate. And it can better adapt to the constantly changing market environment. The ALM system needs to focus on enhancing key financial indicators such as the cash flow gap, liquidity indicators, and the management of high-quality liquid asset reserves, and integrate advanced stress testing and scenario analysis modeling tools to simulate different market environments and assess the potential impact of these factors

Customer Profile: Ping An Bank is one of the largest and most innovative commercial banks in China and is affiliated with Ping An Insurance Group. Ping An Bank offers a comprehensive range of financial products and services, including retail banking, corporate banking and wealth management, and plays a leading role in promoting the digital transformation and innovation of China’s financial services industry. Project Background: Ping An Bank is committed to strengthening risk management practices and developing a market risk measurement engine in order to better handle the complex financial products and derivatives it deals with on a daily basis. The goal of this project is to create the first self-developed market risk engine, which is capable of pricing and valuing various financial instruments, calculating sensitivity, and conducting stress tests and value at risk (VaR) calculations. This system needs to handle multiple asset classes, including foreign exchange, bonds, inter-bank lending, options, swaps and other derivatives. In addition, the engine must also support multiple computing scenarios, simplify pricing and sensitivity analysis, and facilitate the management of complex investment portfolios across different customer types. This system is designed to utilize big data technology to enhance computing speed and accuracy, improve user experience, and