Multimodal semantic reasoning is used by large language models to improve the quality and efficiency of work and promote inclusive finance in the new era of digital economy credit risk control systems. The old ways of risk control cannot make good use of unstructured data

are slow to detect risks

and do not clearly present the reasons for decisions. Based on the actual operation of commercial banks

this paper will present the basic logic and various values of large model applications in risk management

set up an all-encompassing operating framework that includes data-driven support

tiered risk identification

collaborative decision-making

etc.

and develop phased implementation plans

cross-departmental coordination mechanisms

and all-round lifecycle management solutions in accordance with current regulations. Some practical and applicable intelligent risk control frameworks have been put forward in this paper to provide some inspiration for the digitalisation of risk management in the banking sector.