Suihai Chen
ABSTRACT
Loan risk analysis is a common challenge faced by global financial institutions. Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. Aiming at the characteristics of unbalanced loan data and high noise, this paper proposes an improved Gray Wolf optimization strategy (PSO-GWO). PSO-GWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf algorithm (GWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. To a certain extent, it avoids the inefficiency of the Gray Wolf algorithm, balances the ability of local search and global development, and improves the accuracy of the model. Compared with the traditional credit evaluation model, PSO-GWO-CatBoost has better accuracy and practical application value.
- Wu, H. , & Wang, B. 2019. An analysis of basic statistical data of Chinese academic libraries in 2018. Journal of Academic Libraries.Google Scholar
- Xu, J., Hajiyev, A., Nickel, S., & Gen, M. 2017. [advances in intelligent systems and computing] proceedings of the tenth international conference on management science and engineering management volume 502 || slotting optimization of warehousing system based on the Hungarian method.Google Scholar
- Annamraju, A, & Nandiraju, S. 2019. Load Frequency Control of an Autonomous Microgrid Using Robust Fuzzy PI Controller. 2019 8th International Conference on Power Systems (ICPS).Google ScholarCross Ref
- Hua, B., Huang, Y., Yunhua, W. U., Chen, Z., & Nicholas, D. 2019. Spacecraft formation reconfiguration trajectory planning with avoidance constraints using adaptive pigeon-inspired optimization.Google Scholar
- Xue, X. , & Xiao, M. 2018. Deformation evaluation on surrounding rocks of underground caverns based on pso-lssvm. Tunnelling and Underground Space Technology, 69(oct.), 171-181.Google Scholar
- Kumar, A. , Pant, S. , & Ram, M. 2016. System reliability optimization using the gray wolf optimizer algorithm. Quality & Reliability Engineering International, 33(7), 1327-1335.Google ScholarCross Ref
- Karimi, F. , & Vaez, S. 2019. Two-stage optimal seismic design of steel moment frames using the lrfd-pbd method. Journal of Constructional Steel Research, 155(APR.), 77-89.Google ScholarCross Ref
- Malik, H. , Srivastava, S. , Sood, Y. R. , & Ahmad, A. 2019. [advances in intelligent systems and computing] applications of artificial intelligence techniques in engineering volume 697 (sigma 2018, volume 2) || comparative study of random forest and neural network for prediction in direct marketing. , 10.1007/978-981-13-1822-1(Chapter 37), 401-410.Google Scholar
- Narinder, S. , & Singh, S. B. 2017. Hybrid algorithm of particle swarm optimization and grey wolf optimizer for improving convergence performance. Journal of Applied Mathematics, 2017, 1-15.Google ScholarCross Ref
- Nisbet, & Robert. 2018. Handbook of statistical analysis and data mining applications || accessory tools for doing data mining. 99-117.Google Scholar
Index Terms
- Algorithmic Loan Risk Prediction Method Based on PSO-GWO-Catboost
Recommendations
The Implications of Credit Risk Modeling for Banks’ Loan Loss Provisions and Loan-Origination Procyclicality
Economic policymakers express concern that procyclical lending by banks imperils financial stability. Prior research finds that banks that record timelier loan loss provisions originate more loans during downturns, consistent with loan loss–provision ...
The Study on the Loan Risk Pricing of the Bank in Internal Rating-Based Approach
ICRMEM '08: Proceedings of the 2008 International Conference on Risk Management & Engineering ManagementLoan risk pricing system of the bank is the core of interest rate marketization. Realizing independent pricing of loan interest rate will be an inevitable tendency. At present, commercial banks of China have widely developed credit rating system for ...
Research on Interest Rate Risk of Housing Mortgage Loan Based on Computer Simulation
In recent years, with the rapid increase of the business volume of housing mortgage loans of commercial banks, the risk of prepayment is increasingly exposed. Prepayment will have a great impact on the duration and convexity of housing mortgage loans of ...
Comments