Simulation of Enterprise Financial Management Early Warning Model Based on Neural Network Algorithm

Model simulation evaluation plays a crucial role in forecasting enterprise financial management risks, yet it often suffers from imprecise outcome assessments. Traditional statistical models fall short in addressing these evaluation challenges within corporate finance settings, leading to suboptimal evaluations. To address this, the study introduces an innovative neural network algorithm tailored for model simulation assessment and analysis. Initially, financial management's predictive theory guides the parameter assessment for our model, with indicators categorized based on specific simulation evaluation needs to diminish interfering variables. Subsequently, this theory is employed to simulate and scrutinize the corporate financial risk prediction model, resulting in a detailed model simulation evaluation strategy and a thorough analysis of its outcomes. MATLAB simulations confirm that, against set criteria, the neural network algorithm's simulation for corporate financial risk prediction surpasses traditional statistical models in evaluation precision and enhancing business decision-making efficacy.