Essays on Bank Risk

This PhD Thesis is composed of three chapters, each discussing a specific type of risk that banks face. The first chapter talks about Systemic Risk and how banks get exposed to it through the Interbank Funding Market. Exposures in the said market have Systemic Risk implications because the market creates linkages, where the failure of one party can affect the others in the market. By showing that CDS Spreads, as bank risk indicators, are positively related to their Net Interbank Funding Market Exposures, this chapter establishes the above Systemic Risk Implications of Interbank Funding. Meanwhile, the second chapter discusses how banks may handle Illiquidity Risk, defined as the possibility of having sudden funding needs. Illiquidity Risk is embodied in this chapter through Loan Commitments as they oblige banks to lend to its clients, up to a certain amount of funds at any time. This chapter points out that using Securitization as funding facility, could allow the banks to manage this Illiquidity Risk. To make this case, this chapter demonstrates empirically that banks having an increase in Loan Commitments, may experience an increase in risk profile but such can be offset by an accompanying increase in Securitization Activity. Lastly, the third chapter focuses on how banks manage Credit Risk also through Securitization. Securitization has a Credit Risk management property by allowing the offloading of risk. This chapter investigates how banks use such property by looking at the effect of securitization on the banks’ loan portfolios and overall risk and returns. The findings are that securitization is positively related to loan portfolio size and the portfolio share of risky loans, which translates to higher risk and returns. Thus, this chapter points out that Credit Risk management through Securitization may be have been done towards higher risk taking for high returns.

Development of advanced tools and methods for the assessment and management of risk due to atypical major accident scenarios

Proper hazard identification has become progressively more difficult to achieve, as witnessed by several major accidents that took place in Europe, such as the Ammonium Nitrate explosion at Toulouse (2001) and the vapour cloud explosion at Buncefield (2005), whose accident scenarios were not considered by their site safety case. Furthermore, the rapid renewal in the industrial technology has brought about the need to upgrade hazard identification methodologies. Accident scenarios of emerging technologies, which are not still properly identified, may remain unidentified until they take place for the first time. The consideration of atypical scenarios deviating from normal expectations of unwanted events or worst case reference scenarios is thus extremely challenging. A specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was developed as a complementary tool to bow-tie identification techniques. The main aim of the methodology is to provide an easier but comprehensive hazard identification of the industrial process analysed, by systematizing information from early signals of risk related to past events, near misses and inherent studies. DyPASI was validated on the two examples of new and emerging technologies: Liquefied Natural Gas regasification and Carbon Capture and Storage. The study broadened the knowledge on the related emerging risks and, at the same time, demonstrated that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards. Moreover, in order to tackle underlying accident causes of atypical events, three methods for the development of early warning indicators were assessed: the Resilience-based Early Warning Indicator (REWI) method, the Dual Assurance method and the Emerging Risk Key Performance Indicator method. REWI was found to be the most complementary and effective of the three, demonstrating that its synergy with DyPASI would be an adequate strategy to improve hazard identification methodologies towards the capture of atypical accident scenarios.