5 Concluding Remarks

Financial crises have repeatedly confirmed that the lack of liquidity is an inherent risk throughout the banking sector (Pohl, 2017). Liquidity and solvency are two interrelated dimensions of credit risk that cannot be modelled, or stressed, sep- arately. Nonetheless, the interaction between liquidity and solvency tends to be omitted in stress testing practices. In response to calls from regulators to develop integrated liquidity and solvency stress tests (Basel Committee on Banking Su- pervision, 2015), we have developed a coherent framework for joint stress testing of solvency and liquidity risk. In our framework, solvency shocks affect liquidity through margin require- ments, via firm’s ability to raise short-term funding, and through credit risksen- sitive outflows. Consequently, this leads to endogenous liquidity shocks. Inturn, solvency stress is exacerbated through the cost of new funding resulting from a liquidity shortfall, and fire sales. We distinguish between two types of failure: financial institutions can become illiquid without being insolvent, insolvent while remaining liquid, or – in the case of extreme shocks – both illiquid and insolvent. The model illustrates the danger of underestimating credit risk by models that do not account for the solvency-liquidity nexus. As shown by our examples, balance sheet composition has a significant effect on the solvency-liquidity nexus. Inpar- ticular, our insights show that structural solvency risk models are insufficient to capture this dependency and we advocate the use of a more granular balance sheet view by the regulators when conducting a stress test. Our proposed framework provides a more realistic stress test framework which establishes coherence between design of solvency and liquidity stress tests. It also includes mitigating actions that can be extracted from the bank’s contingency funding plan and recovery plan. By defining the concept of Liquidity at Risk, we provide a tool to quantify the total draw on liquidity resources of the bank conditional on the stress scenario defined directly in terms of an adverse shock to risk factors. Sudden liquidity stress can result in the inability to obtain sufficient funding in due time and can lead to insolvency. The tool is calibrated using available regulatory templates on financial data, risk data, and liquidity monitoring templates. The model is amenable to reverse stress testing and naturally permits a range of sensitivity tests around crucial in- puts including changes to the classification of fair valued instruments, the liquidity generation capacity of unencumbered securities, the evolution of market haircuts and funding costs, and fluctuations in creditors’ risk appetite framework. The model yields useful policy implications for central banks and supervisory authorities. It helps supervisors to identify whether managerial options to fend off liquidity risk are helpful in avoiding insolvency or illiquidity in plausible stress scenarios. It also enables to identify sources of systemic spillovers, that is, shocks

©International Monetary Fund. Not for Redistribution to risk factors that can become a conduit of systemic risk propagation and can threaten financial stability. Crucially, it helps authorities to make better decisions regarding the provision of central bank emergency liquidity assistance (ELA) to “illiquid but solvent’’ financial institutions. Ultimately, it serves to quantify the amount of resolution funding, which remain perhaps the key likely impediment in banking resolution.

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