Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management
This research presents a systematic review of a substantial body of high-quality research articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive analysis of a DPM wide spectrum approaches including Textual Models, Systematic Review Studies, Hybrid Models, Intelligen...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402415801X |
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| _version_ | 1846167086091468800 |
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| author | Jahanzaib Alvi Imtiaz Arif Kehkashan Nizam |
| author_facet | Jahanzaib Alvi Imtiaz Arif Kehkashan Nizam |
| author_sort | Jahanzaib Alvi |
| collection | DOAJ |
| description | This research presents a systematic review of a substantial body of high-quality research articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive analysis of a DPM wide spectrum approaches including Textual Models, Systematic Review Studies, Hybrid Models, Intelligent Models and Statistical Models. The reason behind this study is rooted in the critical need to mitigate and understand the credit default risk that poses a significant threat to financial stability worldwide. By employing an evidence-based approach and methodological rigorously, this research critically evaluates the gaps, effectiveness and evolution in existing DPM methodologies. It is not only synthesized the current landscape of DPM study but also identified the direction for the future research, by offering novel insights and bridging theoretical gaps for enhancing the strategies of credit risk management. This study stands out by focusing on high citation research from top tier publishers, ensuring the quality and relevance of its analysis. The findings of this study have profound implications for stakeholders across the financial sector, including bankers, investors, regulatory bodies, and researchers. It aims to advance financial stability by providing a comprehensive overview of DPM advancements and pointing towards areas that require further exploration. By doing so, it contributes significantly to the development of more effective and sophisticated DPM strategies, thereby enhancing the robustness of financial institutions against potential defaults. |
| format | Article |
| id | doaj-art-fad070f61b664beaae408c1e5145a709 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-fad070f61b664beaae408c1e5145a7092024-11-15T06:13:30ZengElsevierHeliyon2405-84402024-11-011021e39770Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk managementJahanzaib Alvi0Imtiaz Arif1Kehkashan Nizam2Corresponding author.; Department of Business Administration, IQRA University Karachi, PakistanDepartment of Business Administration, IQRA University Karachi, PakistanDepartment of Business Administration, IQRA University Karachi, PakistanThis research presents a systematic review of a substantial body of high-quality research articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive analysis of a DPM wide spectrum approaches including Textual Models, Systematic Review Studies, Hybrid Models, Intelligent Models and Statistical Models. The reason behind this study is rooted in the critical need to mitigate and understand the credit default risk that poses a significant threat to financial stability worldwide. By employing an evidence-based approach and methodological rigorously, this research critically evaluates the gaps, effectiveness and evolution in existing DPM methodologies. It is not only synthesized the current landscape of DPM study but also identified the direction for the future research, by offering novel insights and bridging theoretical gaps for enhancing the strategies of credit risk management. This study stands out by focusing on high citation research from top tier publishers, ensuring the quality and relevance of its analysis. The findings of this study have profound implications for stakeholders across the financial sector, including bankers, investors, regulatory bodies, and researchers. It aims to advance financial stability by providing a comprehensive overview of DPM advancements and pointing towards areas that require further exploration. By doing so, it contributes significantly to the development of more effective and sophisticated DPM strategies, thereby enhancing the robustness of financial institutions against potential defaults.http://www.sciencedirect.com/science/article/pii/S240584402415801XDefault prediction models (DPM)Credit risk managementSystematic literature reviewFinancial stabilityHybrid modeling approaches |
| spellingShingle | Jahanzaib Alvi Imtiaz Arif Kehkashan Nizam Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management Heliyon Default prediction models (DPM) Credit risk management Systematic literature review Financial stability Hybrid modeling approaches |
| title | Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management |
| title_full | Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management |
| title_fullStr | Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management |
| title_full_unstemmed | Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management |
| title_short | Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management |
| title_sort | advancing financial resilience a systematic review of default prediction models and future directions in credit risk management |
| topic | Default prediction models (DPM) Credit risk management Systematic literature review Financial stability Hybrid modeling approaches |
| url | http://www.sciencedirect.com/science/article/pii/S240584402415801X |
| work_keys_str_mv | AT jahanzaibalvi advancingfinancialresilienceasystematicreviewofdefaultpredictionmodelsandfuturedirectionsincreditriskmanagement AT imtiazarif advancingfinancialresilienceasystematicreviewofdefaultpredictionmodelsandfuturedirectionsincreditriskmanagement AT kehkashannizam advancingfinancialresilienceasystematicreviewofdefaultpredictionmodelsandfuturedirectionsincreditriskmanagement |