{"title":"Credit Risk Modelling Using RNN-LSTM Hybrid Model for Digital Financial Institutions","authors":"Gabriel Musyoka, Antony Waititu, Herbert Imboga","doi":"10.11648/j.ijsd.20241002.11","DOIUrl":"https://doi.org/10.11648/j.ijsd.20241002.11","url":null,"abstract":"In response to the rapidly evolving financial market and the escalating concern surrounding credit risk in digital financial institutions, this project addresses the urgency for accurate credit risk prediction models. Traditional methods such as Neural network models, kernel-based virtual machines, Z-score, and Logit (logistic regression model) have all been used, but their results have proven less than satisfactory. The project focuses on developing a credit scoring model specifically tailored for digital financial institutions, by leveraging a hybrid model that combines long short-term memory (LSTM) networks with recurrent neural networks (RNN). This innovative approach capitalizes on the strengths of the Long-Short Term Memory (LSTM) for long-term predictions and Recurrent Neural Network (RNN) for its recurrent neural network capabilities. A key component of the approach is feature selection, which entails extracting a subset of pertinent features from the credit risk data using RNN in order to help classify loan applications. The researcher chose to use data from Kaggle to study and compare the efficacy of different models. The findings reveal that the RNN-LSTM hybrid model outperforms other RNNs, LSTMs, and traditional models. Specifically, the hybrid model demonstrated distinct advantages, showcasing higher accuracy and a superior Area Under the Curve (AUC) compared to individual RNN and LSTM models. While RNN and LSTM models exhibited slightly lower accuracy individually, their combination in the hybrid model proved to be the optimal choice. In summary, the RNN-LSTM hybrid model developed stands out as the most effective solution for predicting credit risk in digital financial institutions, surpassing the performance of standalone RNN and LSTM models as well as traditional methodologies. This research contributes valuable insights for banks, regulators, and investors seeking robust credit risk assessment tools in the dynamic landscape of digital finance.","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"109 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140713499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kiswendsida Mahamoudou Ouedraogo, Delwendé Abdoul-Kabir Kafando, François Xavier Ouedraogo, Pierre Clovis Nitiéma
{"title":"Investigating the Impact of Variable Dividends and Tail Dependence in a Compound Poisson Risk Model","authors":"Kiswendsida Mahamoudou Ouedraogo, Delwendé Abdoul-Kabir Kafando, François Xavier Ouedraogo, Pierre Clovis Nitiéma","doi":"10.11648/j.ijsd.20241001.11","DOIUrl":"https://doi.org/10.11648/j.ijsd.20241001.11","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"125 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139615183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Synthesis of C4 Olefin by Ethanol Coupling Based on Multivariate Statistical Analysis","authors":"Hua Xu","doi":"10.11648/j.ijsd.20230904.11","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230904.11","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"17 8‐9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138978850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexander Kwaku Boateng, Richard Puurbalanta, Gideon Mensah Engmann, Ernest Zamanah, Angela Osei-Mainoo
{"title":"Mixed Autoregressive Model for Spatial Data: A Bayesian Application to Poverty Mapping","authors":"Alexander Kwaku Boateng, Richard Puurbalanta, Gideon Mensah Engmann, Ernest Zamanah, Angela Osei-Mainoo","doi":"10.11648/j.ijsd.20230903.12","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230903.12","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"772 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139309295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling Count Data for HIV-Positive Patients on Antiretroviral Treatment in Kenya","authors":"Anna Nanjala Muricho, Thomas Mageto, S. Mwalili","doi":"10.11648/j.ijsd.20230903.11","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230903.11","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139306456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayes Estimator Parameters Exponential Distribution of Type I Sensor Data Using Linear Exponential Loss Function Method Based on Prior Jeffrey","authors":"null Afriani, Ardi Kurniawan, E. Ana","doi":"10.11648/j.ijsd.20230902.12","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230902.12","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115663041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variable Selection for Semi-Parametric Models with Interaction Under High Dimensional Data","authors":"Ya-Feng Xia, Na Kui","doi":"10.11648/j.ijsd.20230902.11","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230902.11","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115085365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bo Yang, Yunyuan Yang, W. Zheng, Yanmei Li, Xinping Yang
{"title":"Bayesian Analysis on the Spatial Difference of Input Risk of Overseas Cases of COVID-19 in China","authors":"Bo Yang, Yunyuan Yang, W. Zheng, Yanmei Li, Xinping Yang","doi":"10.11648/j.ijsd.20230901.15","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230901.15","url":null,"abstract":": To analyze the spatial difference of COVID-19 import risk is helpful for scientific prevention and control. On the basis of clustering 25 provinces and cities with epidemic input in study time, a multinomial distribution model was established under the Bayesian framework. All parameters Bayesian estimation was obtained by MCMC method. 25 provinces and cities with overseas input were divided into 9 categories from March 3 to April 23","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116059412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian Multiple Linear Regression Model for GDP in Nepal","authors":"Ranjita Pandey, Dipendra Bahadur Chand, H. Tolani","doi":"10.11648/j.ijsd.20230901.12","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230901.12","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131036999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analyzing Dynamic Regimes of GARCH Model on Stock Price Volatility","authors":"Rosemary Ukamaka Okafor, Josephine Nneamaka Onyeka-Ubaka","doi":"10.11648/j.ijsd.20230901.13","DOIUrl":"https://doi.org/10.11648/j.ijsd.20230901.13","url":null,"abstract":"","PeriodicalId":427819,"journal":{"name":"International Journal of Statistical Distributions and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130686386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}