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Intelligent Pricing with Clarity: Interpretable AI for Customer-Centric Time Deposit Interest Rates
Date
2024-01-01
Author
Imece, Salih
Hamza Gundog, Bugra
Koroglu, Bilge
İyigün, Cem
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Time deposits represent a savings account type where customers place their funds for a designated period. The process of determining interest rates tailored to individual customer-specific time-deposit contracts presents a formidable challenge. It involves the intricate balance of ensuring customer satisfaction while concurrently ensuring banking profitability. In our study, we focused on the prediction of interest rates for time deposit contracts by leveraging customer-specific and macroeconomic features. The data utilized was sourced from a private bank in Turkey. We delved into several machine learning algorithms to secure reliable results and executed rigorous statistical comparisons among them. Subsequently, our emphasis shifted to the realm of explainable AI techniques, allowing us to derive substantial insights from the machine learning algorithms, particularly concerning customer-specific aspects. In light of this framework, our research bears significant relevance for our banking partner, proffering both elucidation and a decisive approach.
Subject Keywords
Customer-specific interest rates
,
Explainable artificial intelligence (XAI)
,
Machine learning algorithms
,
Time deposit contracts
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85203202034&origin=inward
https://hdl.handle.net/11511/111128
DOI
https://doi.org/10.1007/978-3-031-67192-0_9
Conference Name
International Conference on Intelligent and Fuzzy Systems, INFUS 2024
Collections
Department of Industrial Engineering, Conference / Seminar
Citation Formats
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BibTeX
S. Imece, B. Hamza Gundog, B. Koroglu, and C. İyigün, “Intelligent Pricing with Clarity: Interpretable AI for Customer-Centric Time Deposit Interest Rates,” Çanakkale, Türkiye, 2024, vol. 1090 LNNS, Accessed: 00, 2024. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85203202034&origin=inward.