Concluding remarks
Systemic risk requires complex analysis. It can be seen from the view of identifying and analyzing the interlinkages and interdependencies of the credit exposures and counterparties where there is an expected chain reaction after default and downgrading credit events.
Such events will affect the value of their exposure, which may influence other counterparties, other assets, collaterals and the P&L as well as both market and funding liquidity of the portfolio that it belongs to. Credit risk events to counterparties will have direct impact on the value and liquidity of the financial instruments that they are linked to. Moreover, they may affect other counterparties. As a chain reaction to other exposures and counterparties, systemic risk is expected to cause a significant degree of unexpected losses. Such losses must be well defined and measured quantitatively.The interlinkages and interdependencies of specific instruments and/or counterparties with other financial instruments and counterparties may cause concentration risk. Indeed, in such a risk a credit event on an exposure and/or counterparty could immediately impact many other counterparties and/or exposures.
In the modelling of both concentration and systemic risks we need to integrate market, credit and behavior risk factors in a sense to understand, identify and measure their correlations and co-movements in both canonical (i.e., expected) and stress (i.e., unexpected) volatile conditions. Then we need to measure their impact in value, income and liquidity. Thus, financial analysis plays a key role in managing concentration and systemic risks.
The participants and credit exposures in marketplace lending may suffer from concentration and systemic risk. We need to understand what would happen to the entire system if certain groups of counterparties fail to fulfil their obligations, and how this would influence the credit quality of other correlated counterparties.
What could happen if a contract with certain characteristics (e.g., linked to a number of obligors with a range of credit quality) partially defaulted? What might be the impact to the investors? In fact, in marketplace lending financial contracts, if a borrower defaults, the credit event impacts many lenders.Indeed, there are many cases referring to systemic and concentration risk, depending on the structure of the contracts and credit portfolios. In this chapter, we have aimed to highlight the main combinations to be considered in building a framework for a complete model to identify and manage these types of risks.
NOTES
1. Clusters can be a group of exposures with a combination of similar characteristics, e.g., have the same contract type, belong to the same portfolio, have the same credit quality, influenced by the same market conditions, etc.
2. Explained in Chapter 10 (Credit Enhancements).
3. E.g., based on Basel regulation a capital adequacy against losses must be held by the financial credit institutions.
4. Via central banks, governments and thus tax payers.
5. Cluster is a group of counterparties that may share similar characteristics, e.g., are linked to the same sector, region, belong to the same credit quality/rating class, have similar descriptive characteristics, etc.
6. Moldow, Charles (2014) A Trillion Dollar Market By the People, For the People: How Marketplace Lending Will Remake Banking As We Know It.
7. See for instance the exchange of governmental depths among Euro-Zone countries.
8. Cluster indicates group of assets influenced by the same or similar risk factors, i.e., interest or FX rates, prices, etc.
9. It is based on the Herfindahl index.
10. A cluster of counterparties or assets implies a group of them that share similar characteristics, e.g., have the same credit quality, belong to the same (or correlated) sector, region, etc., influenced by same risk factors, etc.