Blockchain-enabled KYC integration for CLV optimization with robust M-Estimation and IRLS method
This research introduces an innovative approach in implementing Know Your Customer (KYC) on blockchain technology as a means of using data, hybrid robust m-estimation, and the iteratively reweighted less squares (IRLS) method to optimize CLV data. This approach aims to improve the accuracy and relia...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | ICT Express |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405959525000347 |
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| Summary: | This research introduces an innovative approach in implementing Know Your Customer (KYC) on blockchain technology as a means of using data, hybrid robust m-estimation, and the iteratively reweighted less squares (IRLS) method to optimize CLV data. This approach aims to improve the accuracy and reliability of CLV predictions by ensuring the security and reliability of customer data. This tool can help companies manage and increase CLV more effectively, meeting data security and compliance standards. The R-squared validation test results are close to 1, so the model can explain data variations well. RMSE and MSE have small values, so the model has good performance in predicting the target value. With these achievements, this approach contributes to the development of better marketing strategies and business decisions in an increasingly complex and rapidly changing digital environment. |
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| ISSN: | 2405-9595 |