Managing Director, Head of Portfolio and Balance Sheet Research
Dr. Amnon Levy heads the group responsible for research development and quantitative services related to Moody’s Analytics portfolio and balance sheet solutions.
Amnon has a BA in economics from the University of California at Berkeley and a PhD in finance from the Kellogg Graduate School of Management, Northwestern University. Prior to joining Moody’s Analytics, he was a visiting assistant professor at the Stern School of Business, New York University, and the Haas School of Business, University of California at Berkeley. He has also taught corporate finance at the Kellogg School of Management, Northwestern University, and worked at the Board of Governors of the Federal Reserve System. He is currently teaching a course on credit risk in the Haas School of Business MFE program.
Amnon has been published in the Journal of Financial Economics, the Journal of Monetary Economics, the Encyclopedia of Quantitative Finance, the Journal of Banking and Finance, and the Journal of Risk Model Validation. His current research interests include the impact of credit in ALM, and unifying the management of regulatory capital, economic risks, and the impact of accounting rules.
A Composite Capital Measure Unifying Business Decision Rules in the Face of Regulatory Requirements Under New Accounting Standards
Prudent credit risk management ensures institutions maintain sufficient capital and limit the possibility of a capital breach. With CECL and IFRS 9, the resulting trend toward greater credit earnings volatility raises uncertainty in capital supply, ultimately causing an increase in required capital. It is ever more challenging for institutions to manage their top-of-the house capital while steering their business to achieve the desired performance level. This paper introduces an approach that quantifies the additional capital buffer an institution requires, beyond the required regulatory minimum, to limit the likelihood of a capital breach. In addition, we introduce a new measure that allocates capital and recognizes an instrument's regulatory capital requirements, loss allowance, economic concentration risks, and the instrument's contribution to the uncertainty in capital supply and demand. In-line with the Composite Capital Measure introduced in Levy and Xu (2017), this extended measure includes far-reaching implications for business decisions. Using a series of case studies, we demonstrate the limitations of alternative measures and how institutions can optimize performance by allocating capital and making business decisions according to the new measure.
Measuring and Managing the Impact of IFRS 9 and CECL Requirements on Dynamics in Allowance, Earnings, and Bank Capital
Reserving for loan loss is one of the most important accounting aspects for banks. Its objective is to cover estimated losses on impaired financial instruments due to defaults and non-payment. Reserve measurement affects both the balance sheet and income statement. It impacts earnings, capital, dividends and bonuses, and attracts the attention of bank stakeholders ranging from the board of directors and regulators to equity investors. In response to the so-called “too-little, too-late” problem experienced with loan loss reserve during the Great Financial Crisis, accounting standard setters now require that banks provision against loan loss based on expected credit losses (ECL). Arguably, calculating the Expected Credit Loss Model under IFRS 9 and CECL presents a momentous accounting change for banks, with the new standards coming into effect sometime between 2018 and 2021, depending on the jurisdiction.
Using a long history of public firm defaults from Moody's Investor Services and Moody's Analytics, this study illustrates a validation approach for jointly testing the impact of PD and correlation upon model performance. We construct predicted default distributions using a variety of PD and correlation inputs and examine how the predicted distribution compares with the realized distribution. The comparison is done by looking at the percentile of realized defaults with respect to the predicted default distribution. We compare the performance of two typical portfolio parameterizations: (1) a through-the-cycle style parameterization using agency ratings-based long-term average default rates and Basel II correlations; and (2) a point-in-time style parameterization using public EDF credit measure, and Moody's Analytics Global Correlation Model (GCorr™). Results demonstrate that a through-the-cycle style parameterization results in a less conservative view of economic capital and substantial serial correlation in capital estimates. Results also show that when point-in-time measures are used, the tested economic capital model produces consistent and conservative economic capital estimates over time. A version of this paper appears in the Journal of Risk Model Validation, March 2013.
Amnon Levy, managing director and head of portfolio and balance sheet research at Moody's Analytics, discusses the evolving expectations of institutions for credit portfolio management, as well as how it is being altered and adapted amid greater impact from new regulatory and technological advancements.
A Composite Capital Allocation Measure Integrating Regulatory and Economic Capital, and the Impact of IFRS 9 and CECL
We propose a composite capital allocation measure integrating regulatory and economic capital. The approach builds upon the economic framework underpinning traditional RORAC-style business decision rules, allowing for an optimized risk-return tradeoff while adhering to regulatory capital constraints. The measure has a number of depictions, and it can be viewed as a weighted sum of economic and regulatory capital, as economic capital adjusted for a regulatory capital charge, or as regulatory capital adjusted for concentration risk and diversification benefits. Intuitively, when represented as economic capital adjusted for a regulatory capital charge, the adjustment can be represented as the additional top-of-the-house regulatory capital, above economic capital, allocated by each instrument's required regulatory capital. We show that the measure has ideal properties for an integrated capital measure. When regulatory capital is binding, composite capital aggregates to the institution's top-of-the-house target capitalization rate. We find the measure is higher than economic capital, but lower than regulatory capital for instruments with high credit quality, reflecting the high regulatory capital charge for this instrument class. Finally, we address how IFRS 9/CECL impacts the CCM and discuss the broader implications of the new accounting standards.
IFRS 9 materially changes how institutions set aside loss allowance. With allowances flowing into earnings, the new rules can have dramatic effects on earnings volatility. In this paper, we propose general methodologies to measure and manage credit earnings volatility of a loan portfolio under IFRS 9. We walk through IFRS 9 rules and the different mechanisms that it interacts with which flow into earnings dynamics. We demonstrate that earnings will be impacted significantly by credit migration under IFRS 9. In addition, the increased sensitivity to migration will be further compounded by the impact of correlation and concentration. We propose a modeling framework that measures portfolio credit earnings volatility and discuss several metrics that can be used to better manage earnings risk.
How to Manage the Impact of IFRS 9 on Earnings Volatility and the Supply and Demand of Regulatory Capital
With the implementation of IFRS 9 underway, institutions want to better quantify the impact of IFRS 9 on provisions, result earnings and capital buffers. During this video webinar, we will discuss the strategic impact of IFRS 9 on earnings, capital and investment concentration.
International Financial Reporting Standard 9 (IFRS 9) is a high-impact symbolic, operational, IT and organisational transformation event for finance and risk. The Risk Chartis IFRS 9 Market Report focuses on the key challenges for banks implementing IFRS 9, including exclusive content from Moody's Analytics.
Managing Earnings Volatility and Uncertainty in the Supply and Demand for Regulatory Capital: The Impact of IFRS 9
This paper presents a novel modeling approach that allows for better management of the interplay between supply and demand dynamics for regulatory capital, combining an economic framework with regulatory capital and new loss recognition rules. The framework is particularly relevant in understanding the extent to which IFRS 9 can lead to more aggressive provisioning, which feeds into earnings volatility. Our approach provides guidance on how organizations can better manage their capital buffer, considering investment concentration, its impact on earnings volatility, and the relationship with regulatory capital requirements. Imperative to portfolio management, the framework recognizes the likelihood of a capital shortfall being significantly impacted by portfolio asset class, geography, industry, and name concentration, as extreme fluctuations in capital supply and demand occur more often for institutions holding more concentrated portfolios. Finally, we discuss integrated investment and strategic decision measures that account for the full spectrum of economic risks and interactions with regulatory and accounting rules, as well as instruments' contribution to earnings volatility and capital surplus dynamics.
Banks commonly use Risk Contribution, or contribution to portfolio Unexpected Loss (i.e., standard deviation), as a risk allocation method. While the method has some very desirable properties, it can also produce seemingly counterintuitive dynamics, whereby high interest income-producing assets are associated with higher risk, all else being equal. This dynamic manifests from the higher interest income assets possessing higher value, leading to higher standard deviation in absolute terms. In reality, financial institutions often use interest income to offset losses, and thus, associate higher interest with lower risk. This paper introduces a new, income-adjusted form of Risk Contribution-based capital allocation, designed so that interest income offsets losses. The measure demonstrates improved properties for exposures with particularly high coupons.