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- Galina's research evolves around credit risk of individuals and small businesses (SMEs) using advanced statistical and machine-learning techniques, applied to Big Data, in particular Open Banking (OB) financial transactions. An area of specific focus is financial vulnerability, fairness and social impact of credit.
orcid.org/0000-0001-8722-2201
Her research evolves around credit risk of individuals and small businesses (SMEs) using advanced statistical and machine-learning techniques, applied to Big Data, in particular Open Banking (OB) financial transactions. An area of specific focus is financial vulnerability, fairness and social impact of credit.
The increasing usage of new data sources and machine learning (ML) technology in credit modeling raises concerns with regards to potentially unfair decision-making that rely on protected...
This paper expands the literature on credit risk management by assessing the effectiveness of aspects of corporate governance for predicting financial distress in a dynamic discrete-time survival analysis model.
- Zhiyong Li, Zhiyong Li, Jonathan Crook, Galina Andreeva, Ying Tang
- 101.3K
- 2021
- Pacific-Basin Finance Journal
Galina Andreeva, Wendy Johnson, The University of Edinburgh. OUTLINE. Motivation. Previous research in Credit Risk Management. Pilot Study in SA Taxi. Exploratory Factor Analysis. Next Steps. MOTIVATION. Explore ways within the domain of ‘personality’ to quantitatively measure ‘willingness to repay’ when credit history not available.
Credit Risk Analysis and Modeling In this paper, the following credit risk analysis methods are described; Credit risk factors profiling and analysis. Credit risk predictive modeling or default predictive modeling. Credit risk modeling or finance risk modeling. Internal credit risk scoring. Credit Risk Profiling
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Sep 20, 2024 · Galina Andreeva is Personal Chair of Societal Aspects of Credit, Co-Head of the Management Science & Business Economics Group, CRC Director. She researches credit risk using advanced statistical and machine-learning techniques, applied to Big Data, in particular Open Banking.
