After the destructive impact of the global financial crisis of 2008, many believe that pre-crisis financial market regulation did not take the "big picture" of the system suffciently into account and, subsequently, financial supervision mainly "missed the forest for the trees". As a result, the...

This paper investigates the main individual driving forces of Hungarian household credit risk and measures the shockabsorbing capacity of the banking system in relation to adverse macroeconomic events. The analysis relies on survey evidence gathered by the Magyar Nemzeti Bank (MNB) in January...

This article aims to identify the most relevant variables that allow through a neural network model (RNA), with supervised learning, in a kind of error correction and feedforward perceptron multilayer architecture to achieve the best predictors of low risk, in the process of microcredit....

This paper investigates the main individual driving forces of Hungarian household credit risk and measures the shockabsorbing capacity of the banking system in relation to adverse macroeconomic events. The analysis relies on survey evidence gathered by the Magyar Nemzeti Bank (MNB) in January...

The dynamic development of the mortgage market, especially in the period before the current financial crisis, revealed that within the EU there are local mortgage credit markets and that it is necessary to harmonize the rules of the system and consumer protection within the Community. The...

We study the exposure of mortgage borrowers in Switzerland to interest rate, income and house price risks and examine how the households' choice of risky mortgages is related to individual interest rate expectations and risk-aversion. Our analysis is based on a unique data set of household...

Using Danish household level data, we find that a relatively large share of total interest-only mortgage debt is held by families with few liquid assets and high loan to value ratios. This may arise because families with interest-only loans do not fully use the lower instalments to increase...

This article aims to identify the most relevant variables that allow through a neural network model (RNA), with supervised learning, in a kind of error correction and feedforward perceptron multilayer architecture to achieve the best predictors of low risk, in the process of microcredit....

Borrowers' housing equity is an important component of their wealth and a critical determinant of their vulnerability to shocks. In this paper, we create a unique data set that allows us to provide a comprehensive look at the ratio of housing debt to housing values - what we refer to as...

On December 16th of 2015, the Fed initiated "liftoff," raising the federal funds rate range by 25 basis points and ending a 7-year regime of near-zero rates. We use a unique dataset of 640,000 loan-hour observations to measure the impact of liftoff on interest rates in the peer-to-peer lending...