해외동향 | Impact of FinTech on payment institutions' and e-money institutions' business models | 한국금융연구원

[LHKOREA]

2019-08-13 일자 [제 19-58 호]

Impact of FinTech on payment institutions' and e-money institutions' business models
EBA (2019-08-13)

The European Banking Authority (EBA) published today a thematic Report on the impact of FinTech on payment institutions' (PIs) and electronic money institutions' (EMIs) business models. This Report points out the EBA's k ..  more

Machine learning explainability in finance: an application to default risk analysis
Bank of England (2019-08-13)

We propose a framework for addressing the 'black box' problem present in some Machine Learning (ML) applications. We implement our approach by using the Quantitative Input Influence (QII) method of Datta et al (2016) in ..  more

(Un)conventional policy and the effective lower bound
BIS (2019-08-13)

We study the optimal combination of interest rate policy and unconventional monetary policy in a model where agency costs generate a spread between deposit and lending rates. We show that credit policy can be a powerful ..  more

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제 목	발행기관
Machine learning explainability in finance: an application to default risk analysis	Bank of England
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Impact of FinTech on payment institutions' and e-money institutions' business models	EBA
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(Un)conventional policy and the effective lower bound	BIS
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