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An asset allocation optimization model for key clients and financial products is developed and deployed on a business platform by compiling a program to a module using MATLAB to show how to integrate financial big data and fintech in a real application for a bank. Firstly, we establish a single objective linear programming model with the percent of assets in products as the decision variables, the minimum-weighted duration as the objective, and the business requirements as constraints. Then, we select non-integer linear programming as the model solver by testing two algorithm solvers with six real test cases separately, according to the solving time. Finally, we directly compile the model and the algorithm program into a module to complete the deployment into a business platform to quickly complete the transformation of data and model the actual productivity of the bank.

How to Integrate Financial Big Data and FinTech in a Real Application in Banks: A Case of the Modeling of Asset Allocation for Products Based on Data