Digital Collection Automation in Retail Banking: A Behavior-Based Approach from Bangladesh
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| Natura: | Recurso digital |
| Lingua: | inglese |
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2025
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| _version_ | 1866902178373828608 |
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| author | Hasan, S M Tanvir |
| author_facet | Hasan, S M Tanvir |
| contents | <p><span>This paper explores a practical digital transformation initiative implemented in the retail collection process of a commercial bank in Bangladesh. In response to increasing operational inefficiencies and customer contact challenges, the bank introduced a behavior-based digital loan recovery strategy. By integrating communication channels such as automated voice calls, SMS, email, mobile app notifications, and robotics-assisted outreach, the bank designed a unified and scalable platform to reduce dependency on manual collection.</span></p> <p><span>The strategy focused on customer segmentation, AI-based trigger systems, and behavior analysis to identify delinquency patterns and engage borrowers smartly. Within a 30-day pilot, significant improvements were recorded in contact rates, repayment intent, and loan recovery response.</span></p> <p><span>This case provides insights into how emerging market banks can adopt lean yet impactful solutions using digital tools and behavioral science without relying heavily on field collection forces. It also presents policy suggestions to support AI and data science integration into retail financial services for broader financial inclusion.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16016094 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Digital Collection Automation in Retail Banking: A Behavior-Based Approach from Bangladesh Hasan, S M Tanvir Retail Banking, Digital Collection, Robotics, Customer Segmentation, Data Analytics, Behavioral Science, Loan Recovery, Bangladesh, AI in Finance, Risk Scoring, NPL Recovery <p><span>This paper explores a practical digital transformation initiative implemented in the retail collection process of a commercial bank in Bangladesh. In response to increasing operational inefficiencies and customer contact challenges, the bank introduced a behavior-based digital loan recovery strategy. By integrating communication channels such as automated voice calls, SMS, email, mobile app notifications, and robotics-assisted outreach, the bank designed a unified and scalable platform to reduce dependency on manual collection.</span></p> <p><span>The strategy focused on customer segmentation, AI-based trigger systems, and behavior analysis to identify delinquency patterns and engage borrowers smartly. Within a 30-day pilot, significant improvements were recorded in contact rates, repayment intent, and loan recovery response.</span></p> <p><span>This case provides insights into how emerging market banks can adopt lean yet impactful solutions using digital tools and behavioral science without relying heavily on field collection forces. It also presents policy suggestions to support AI and data science integration into retail financial services for broader financial inclusion.</span></p> |
| title | Digital Collection Automation in Retail Banking: A Behavior-Based Approach from Bangladesh |
| topic | Retail Banking, Digital Collection, Robotics, Customer Segmentation, Data Analytics, Behavioral Science, Loan Recovery, Bangladesh, AI in Finance, Risk Scoring, NPL Recovery |
| url | https://doi.org/10.5281/zenodo.16016094 |