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ECLSMART: Enhanced Credit Loss Management Automation and Real-time Analytics Tool to Credit Risk Modeling and Management

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dc.contributor.author Wijenayake, Lukshan
dc.date.accessioned 2025-05-23T05:12:34Z
dc.date.available 2025-05-23T05:12:34Z
dc.date.issued 2024
dc.identifier.citation Wijenayake, Lukshan (2024) ECLSMART: Enhanced Credit Loss Management Automation and Real-time Analytics Tool to Credit Risk Modeling and Management. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019875
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2359
dc.description.abstract "The process of computing Expected Credit Loss (ECL) under IFRS 9 and SLFRS 9 is complex, especially for banks, financial institutions, and companies. Currently, many organizations rely on manual processes using Excel, which are time-consuming, prone to errors, and require significant human effort. This project aims to develop a web-based application called ECLSMART to automate ECL calculations for Ernst & Young (EY). The project began with research through interviews, literature reviews, and an industry survey to confirm the problem and gather requirements. Existing solutions were analyzed, revealing that most are either not suitable for Sri Lankan accounting standards or are overly complex and costly. The current manual process increases the risk of errors, especially with the complexity of the ECL model and the need for forward-looking economic assumptions. ECLSMART addresses these issues by automating the ECL calculation process, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and Economic Factor Adjustment (EFA). The application allows users to upload data, classify risks, generate reports, and perform real-time EFA analysis. It also provides customizable dashboards, ensuring compliance with Sri Lankan standards and client-specific methodologies. ECLSMART includes user authentication and security features to ensure data privacy and confidentiality." en_US
dc.language.iso en en_US
dc.subject IFRS 9 en_US
dc.subject Expected Credit Loss en_US
dc.subject Automation en_US
dc.title ECLSMART: Enhanced Credit Loss Management Automation and Real-time Analytics Tool to Credit Risk Modeling and Management en_US
dc.type Thesis en_US


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