Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on...

This paper reviews the rules in place in selected countries to limit risk concentrations in the credit portfolio. The paper focuses on a number of issues suggested by international organizations for countries and bank supervisors to consider in imposing standards for risk diversification in the...

As is well known, most models of credit risk have failed to measure the credit risks in the context of the global financial crisis. In this context, financial industry representatives, regulators and academics worldwide have given new impetus to efforts to improve credit risk modeling for...

We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire...

Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have...

The global financial crisis (GFC) has renewed interest in emergency liquidity support (sometimes referred to as 'Lender of Last Resort') provided by central banks to financial institutions and challenged the traditional way of conducting these operations. Despite a vast literature on the topic,...

Based on technical assistance to central banks by the IMF's Monetary and Capital Markets Department and Information Technology Department, this paper examines fintech and the related area of cybersecurity from the perspective of central bank risk management. The paper draws on findings from the...

The traditional approach to the stress testing of financial institutions focuses on capital adequacy and solvency. Liquidity stress tests have been applied in parallel to and independently from solvency stress tests, based on scenarios which may not be consistent with those used in solvency...

Value-at-Risk (VaR) models often are used to estimate the equity investment that is required to limit the default rate on funding debt. Typical VaR ""buffer stock"" capital calculations produce biased estimates. To ensure accuracy, VaR must be modified by: (1) measuring loss relative to initial...

Counterparty risk in the United States stemming from exposures to OTC derivatives payables (after netting) is now concentrated in five banks?Goldman Sachs, JPMorgan, Bank of America, Morgan Stanley and Citi. This note analyzes how such risks have shifted over the past year. We estimate that the...