From filing to grant: Predicting patent outcomes in FinTech using a predictive analytics perspective
Yazarlar (3)
Milad Armani Dehghani
Nottingham Trent University, İngiltere
Nottingham Trent University, İngiltere
Doç. Dr. Mehmet ŞAHİNER Yalova Üniversitesi, Türkiye
Noptanit Chotisarn
Thammasat Business School, Tayland
Thammasat Business School, Tayland
| Makale Türü |
Özgün Makale
(ESCI dergilerinde yayınlanan tam makale)
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| Dergi Adı | World Patent Information | ||
| Dergi ISSN | 0172-2190 Dergi Bilgileri (2025) | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2025 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-03-2026 |
| Cilt / Sayı / Sayfa | 84 / 1 / – | DOI | 10.1016/j.wpi.2025.102423 |
| Makale Linki | https://doi.org/10.1016/j.wpi.2025.102423 | ||
| UAK Araştırma Alanları |
Finansal Teknoloji
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| Özet |
| Patents are critical indicators of innovation, especially in fast-evolving domains like Financial Technology (FinTech). However, accurately predicting patent grant outcomes with modern artificial intelligence techniques has remained challenging. This study addresses that gap by applying state-of-the-art machine learning (ML), including ensemble methods and deep learning models, to a dataset of 20,008 FinTech patent applications from 2000 to 2020. We demonstrate that our ML framework can forecast grant success with high precision (up to 89 %), revealing that patent quality and strategic filing choices, such as optimal IPC classes and jurisdictions, are key determinants of grant probability. The findings highlight practical implications for innovators and intellectual property managers, such as better resource allocation and informed patent strategy decisions. Overall, this work introduces a novel, AI-driven approach to patent analytics in FinTech, offering a forward-looking tool to enhance innovation management and strategic IP planning. |
| Anahtar Kelimeler |
| Financial technology | Machine learning | Patent quality | Patent strategy | Probability of grant | Technology trends |
Science Direct
From filing to grant: Predicting patent outcomes in FinTech using a predictive analytics perspective
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 3 |
| Scopus | 5 |