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Analysis of stability and exposure of Croatian bank system to non-credit risks
Wittine, Zoran; Vuk, Ivana - In: Business and Economic Research : BER 6 (2016) 2, pp. 331-342
Persistent link: https://www.econbiz.de/10011590050
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Non-performing loans in the banking systems of Serbia, Croatia and Macedonia : comparative analysis
Delova Jolevska, Evica; Andovski, Ilija - In: Ekonomika : međunarodni časopis za ekonomsku teoriju … 61 (2015) 1, pp. 115-130
Persistent link: https://www.econbiz.de/10010510689
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The profitability of Austrian banks' subsidiaries in Croatia, Hungary and Romania and how the financial crisis affected their business models
Kavan, Stefan; Martin, Florian - In: Financial stability report 29 (2015), pp. 59-71
Persistent link: https://www.econbiz.de/10011296241
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Credit risk and bank profitability : case of Croatia
Pepur, Sandra; Tripović, Marija - In: Finance in Central and Southeastern Europe, (pp. 135-144). 2017
Persistent link: https://www.econbiz.de/10011922046
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Are some banks more lenient in the implementation of placement classification rules?
Ridzak, Tomislav - 2012
Persistent link: https://www.econbiz.de/10009488914
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Loan screening when banks have superior information technology
Gao, Yun; Ueda, Kenichi - 2024
Persistent link: https://www.econbiz.de/10014500523
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The use of financial technology in the agriculture sector
McIntosh, Craig; Mansini, Caio Scuarcialupi - 2018
The finance sector has a key role to play in allowing agriculture to contribute to economic growth and poverty reduction. A rapidly evolving technological landscape is opening up new possibilities to target and price credit, to share risk, and to harness information technology to expand...
Persistent link: https://www.econbiz.de/10011904472
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Explainable Machine learning in Credit Risk Management
Bussmann, Niklas - 2020
The paper proposes an explainable AI model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing credit scoring platforms. The model applies similarity networks to Shapley values, so that AI predictions are grouped...
Persistent link: https://www.econbiz.de/10012845786
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The Real Effects of FinTech Lending on SMEs : Evidence from Loan Applications
Eca, Afonso; Ferreira, Miguel A.; Prado, Melissa Porras; … - 2022
businesses who already have access to bank credit. Firms use FinTech to obtain long-term unsecured loans and reduce their … increase leverage and substitute long-term bank debt with FinTech debt. Our findings suggest that FinTech allows firms to … preserve financial flexibility, reduce their bank dependence and exposure to banking shocks …
Persistent link: https://www.econbiz.de/10013302730
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Consumer credit in the age of AI : beyond anti-discrimination law
Langenbucher, Katja - 2022
Search costs for lenders when evaluating potential borrowers are driven by the quality of the underwriting model and by access to data. Both have undergone radical change over the last years, due to the advent of big data and machine learning. For some, this holds the promise of inclusion and...
Persistent link: https://www.econbiz.de/10013445118