The new accounting standards can have material implications for allowance and earnings dynamics. Join our researchers, Amnon Levy and Pierre Xu, explore a large sample of banks to better understand channels by which the standards affect shareholder value.
- Understand the impact of IFRS 9 and CECL on earnings volatility
- Explore the relationship between bank’s equity valuation and earnings volatility
- Evaluate credit portfolio management techniques that can reduce earnings volatility and increase valuation
Moody's Analytics Managing Director Amnon Levy, Moody's Analytics Director Libor Pospisil, and Moody's Investor's Service Jim Hempstead presented at the International Association of Credit Portfolio Managers Spring Conference entitled Managing Credit Risk and Emerging Threats: Lessons from the Gaps Revealed by the Pandemic.
This paper describes a conceptually sound quantitative and practical approach to increasing portfolio return/risk, details the requisite steps, and shows how they can be effectively performed using Moody’s Analytics PortfolioStudio®, a cloud-based, credit portfolio management solution designed for business users.
High-level overview of the modeling methodologies implemented in RiskFrontier™ and their business applications. RiskFrontier calculates a credit investment's value at analysis date, its value distribution at a user-specified investment horizon, and its marginal contribution to portfolio risk, for every instrument in the portfolio.
We study the impact of COVID on concentration risk, relevant in the context of limit-setting, portfolio allocation, and other concentration-sensitive measures. Analysing a European portfolio, we show how our solutions can be used to navigate the COVID crisis and better understand risk within a portfolio framework.
Crises reveal behavior incongruent to historic patterns, requiring new data and analyses. COVID shows established models did not evaluate credit adequately. The Cross-Sectional COVID Overlay assesses current credit, projected ratings, and loss measures in new ways, anchoring to well-understood starting points and scenarios.
With COVID-19 continuing to batter the global economy, many banks are struggling to model credit losses as they prepare for their upcoming Comprehensive Capital Analysis and Review (CCAR) submissions as well as 3rd Quarter earnings.
We introduce a granular, obligor-level, scenario-based model for rating transition matrices. It recognizes differences in the statistical properties of ratings and forward-looking PDs, deviating from approaches assuming a one-to-one relationship between segment rating and PD or that decouple dynamics of ratings and PDs.
Well-established models that evaluate the current credit environment are not working given COVID-19. Internal ratings cannot update at frequencies required to react well. This paper addresses these challenges, presenting applications users can incorporate into Internal Rating Assessment and Projected Ratings and Loss.
The COVID-19 pandemic has brought credit risks that are unprecedented in size, are fast-changing, and have vastly different manifestations across industries. The uncertainty of impact is driven by epidemiological progression and sociological response, balanced by fiscal and monetary stimulus.
Some Small and Medium-Sized Enterprises (SMEs) in the UK and beyond will have enough working capital relative to fixed expenses to withstand an extended business closure, but many will need help.