Financial institution customer credit risk analysis method and system based on federal learning

Abstract

The invention discloses a financial institution customer credit risk analysis method and system based on federated learning, and the system comprises a client and a server, the client accesses the server through a network interface, the server manages the address and version of the client, and the server configures the authentication information of the client in real time; the client comprises a framework application, a training application and a prediction application; the server comprises a framework service, a version service and a model service; according to the financial institution customer credit risk analysis method and system based on federated learning, under the condition of ensuring data security and protecting data privacy, a data island is broken, a financial institution customer credit risk prediction model is trained, and future data is predicted; and model closed-loop management: the server manages model preprocessing of each client before training, manages model parameter merging after client training, and realizes closed-loop process management and control.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, in particular to a method and system for analyzing customer credit risk of financial institutions based on federated learning. Background technique [0002] Financial institutions need to conduct risk analysis operations on customers, so as to be able to understand the customer's credit information, and then determine the relevant rights and interests of the customer, and federated machine learning is also known as federated learning, federated learning, and alliance learning. Federated machine learning is a machine learning framework that can effectively help multiple financial institutions build a federated learning network for data usage and machine learning modeling while meeting the requirements of user privacy protection, data security and government regulations. Combining the customer credit risk analysis of financial institutions with federated learning, to a certain exten...

AI Technical Summary

Problems solved by technology

Federated machine learning is a machine learning framework that can effectively help multiple financial institutions build a federated learning network for data usage and machine learning modeling while meeting the requirements of user privacy protection, data security and government regulations. Combining the customer credit risk analysis of financial institutions with federated learning, to a certain extent, it is impossible to break the data islands, train the customer credit risk prediction model of financial institutions and analyze the data while ensuring data security and protecting data privacy. The role of future data for forecasting

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