360 Finance Research Paper Accepted by International Joint Conference on Neural Networks
SHANGHAI, China, March. 30, 2020 -- 360 Finance, Inc. (NASDAQ: QFIN) (“360 Finance” or the “Company”), a leading digital consumer finance platform, today announced that its whitepaper titled “Effective Automated Feature Derivation via Reinforcement Learning for Microcredit Default Prediction” (the “Whitepaper”) was accepted for the 2020 International Joint Conference on Neural Networks (IJCNN 2020), a flagship conference of the Computational Intelligence Society that covers a wide range of topics in the field of neural networks, from biological neural networks to artificial neural computation.
IJCNN 2020 is part of the IEEE World Congress on Computational Intelligence (IEEE WCCI), the world’s largest technical event in the field of computational intelligence. WCCI 2020 features the flagship conference of the Computational Intelligence Society: IJCNN 2020, the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020), and the 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020) under one roof. It encourages cross-fertilization of ideas among the three big areas and provides a forum for intellectuals from all over the world to discuss and present their research findings on computational intelligence. IEEE WCCI 2020 will be held in Glasgow, Scotland from July 19-24, 2020. According to IJCNN, 1,532 papers from 82 countries were submitted for IJCNN 2019, among which 803 papers were accepted. Very few papers accepted were submitted from China.
Mr. Haisheng Wu, Chief Executive Officer and Director of 360 Finance, commented, “360 Finance is proud to be among the very few Chinese fintech firms to have their papers accepted by IJCNN, which I believe is a testament to our cutting-edge technology and continuous commitment to investing in R&D. Consumer finance is developing rapidly and market participants find that the key challenge lies in deploying the proper risk management and credit scoring methods that evaluate the probability of default or sorts borrowers into different default risk classes. Platforms are often burdened with an overwhelming quantity of raw data, while the traditional feature engineering-driven credit scoring system is heavily dependent on expert knowledge. This results in processes that are often time-consuming and may generate significant trial-and-error costs. To address these issues and improve loan default predictions, our financial risk control algorithm team developed a new performance-driven framework to automatically generate discriminating features from raw data, via reinforced learning, to address the issues and improve loan default prediction. This new method turns up promising results and demonstrates how it can significantly reduce the time and labor costs for daily modeling and model iterations. Additionally, this method also allows us to use raw data to generate very high-quality features which can, in turn, improve the effectiveness of the credit assessment model.”
“Going forward, we will continue to invest in risk management technologies and provide more cutting-edge solutions that fuel innovation and market development for consumer finance. We are thrilled to have our whitepaper accepted and look forward to attending this year’s IJCNN where we will share more of our research with the market as we continue to drive disruptive, innovative and compliant solutions for tech-driven consumer finance.”
About 360 Finance
360 Finance, Inc. (NASDAQ: QFIN) (“360 Finance” or the “Company”) is a leading digital consumer finance platform and the finance partner of the 360 Group. The Company provides tailored online consumer finance products to prime, underserved borrowers funded primarily by its funding partners. The Company’s proprietary technology platform enables a unique user experience supported by resolute risk management. When coupled with its partnership with 360 Group, the Company’s technology translates to a meaningful borrower acquisition, borrower retention and funding advantage, supporting the rapid growth and scaling of its business.
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For more information, please contact:
Mr. Christian Arnell
Ms. Linda Bergkamp