By Lou Felice, NAIC Health and Solvency Policy Advisor and Shanique (Nikki) Hall, CIPR Manager I Recent developments in the financial services industry have underscored the importance of opera onal risk manage-ment (ORM). Opera onal risk has played a role in many of the banking industry scandals taking place over the past two decades, including Barings Bank, Long-Term Capital Management, Bear Stearns and Lehman Brothers. The re-cent global financial crisis brought opera onal risk to the forefront once again. There were a wide range of causes for failures among financial ins tu ons that were linked to the securi za on process. Some of these were rooted in poor business prac ces or strategies. Loose underwri ng stand-ards are a prime example. However, other risks were rooted in a failure to ini ate or to adhere to proper procedures; exercise proper due diligence; and recognize external de-cep on (e.g., mortgage fraud). These failures are the es-sence of opera onal risk.1 As the financial system has become more interconnected and complex than ever before, the challenge of understand-ing and mi ga ng opera onal risks has increased. Improve-ments in ORM have taken on greater focus and visibility within the financial services industry and in many other industries over the past decade. In recent years, the NAIC, through its Solvency Moderniza on Ini a ve (SMI), has been exploring ways to increase the regulatory focus on opera onal risk. In addi on, in advance of the Solvency II regula ons, many large European insurance companies have begun to establish formal ORM programs. This ar cle provides an overview of opera onal risk and highlights some of the work financial ins tu ons have taken to effec-
vely measure and manage opera onal risk. O R The Interna onal Associa on of Insurance Supervisors (IAIS) defines “opera onal risk” as the risk of adverse change in the value of capital resources resul ng from opera onal events such as inadequacy or failure of internal systems, personnel, procedures or controls, as well as external events.2 It refers to risk that result from shor alls or inade-quacies in the management of otherwise quan fiable risk, and from unforeseen external events that can impact an insurer. Opera onal risk poten ally exists in all business ac vi es; it encompasses a wide range of events and ac-
ons or inac ons, such as fraud, human error, accoun ng errors, legal ac ons and system failures. Many of these problems arise during the course of conduc ng day-to-day business opera ons and are typically managed with li le or no incident.
It is important to dis nguish the nature of opera onal risk from that of other types of financial risk such as credit risk (counterparty failure risk, e.g. a credit downgrade or de-fault) or market risk (risk of loss due to an overall decline in the market). Financial ins tu ons normally take on a cer-tain amount of credit and market risk, which they typically try to manage through por olio diversifica on of credit instruments and equi es. Insurers also take on the risks associated with mispricing policies, mises ma ng liabili es and mismatching the dura on of investments vs. policy obliga ons, which also can be managed through geograph-ical or product diversifica on, reinsurance and effec ve hedging strategies. Opera onal risks, on the other hand, are inherent, as it is a necessary part of conduc ng business, but have the poten al to override management strategies and leave the ins tu on open to “tail risk,” thus crea ng the poten al for large losses. Opera onal risk became recognized as a major risk class in the mid-1990s following a number of large-scale insolven-cies in the banking industry caused or exacerbated by events outside of market and credit risk (i.e., BCCI, 1991; Orange County, 1994; Barings Bank, 1995; and Daiwa Bank, 1995, among others) and undermined the confidence in the banking system. In these cases, significant losses were in-curred due to opera onal risk failures. As a result, many regulators and banking execu ves recognized financial ins -tu ons were exposed to non-credit-related risks, which included opera onal risk.3 In response, the Basel Commi ee on Banking Supervision (BCBS) released a proposal in June 1999 to replace the 1988 Basel Capital Accord (Basel I), which applied to all banks in the U.S., with a new risk-sensi ve capital accord. The ini al consulta ve proposal introduced an opera onal risk catego-ry and corresponding capital requirements. According to BCBS, the change reflected the commi ee’s interest in mak-ing the New Basel Capital Accord (Basel II) “more risk sensi-
ve and the realiza on that risks other than credit and mar-ket can be substan al.”4 The Basel II defini on of opera onal risk is primarily linked to its origin; i.e., events related to trading ac vi es. Pillar 1 in Basel II is focused on only three risk categories in a bank’s
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1 Na onal Associa on of Insurance Commissioners, Center for Insurance Policy and Research. “Financing Home Ownership: Origins and Evolu on of Mortgage Securi -za on, Public Policy, Financial Innova ons and Crises.” August 2012.
2 IAIS Common Framework for the Supervision of Interna onally Ac ve Insurance Groups (ComFrame) defini on of “opera onal risk.” 3 Bleier, Michael. “Opera onal Risk in Basel II.” February 2004. 4 Basel Commi ee on Banking Supervision, Consulta ve Document, Opera onal Risk, January 2001.
trading opera ons: credit risk, opera onal risk and market risk.5 A majority of the published literature on opera onal risk is wri en on the banking sector and based on the defi-ni on of opera onal risk prescribed by Basel II. However, this defini on is inappropriate to adopt in insurance, as the insurance business model is much different from that of banking. Hence, the characteris cs and sources of opera-
onal risk are different in these two sectors. Banks are in the borrowing and lending business, while insurers act as risk-takers and managers of insurable risks. Banking/investment banking is a transac onal business, supported by short-term funding in the capital markets, whereas insur-ers’ business is not transac onal. Insurers cover risk expo-sures through reinsurance.6 Consequently, it has been argued opera onal failures in the insurance sector are much less likely to create systemic risk in the economy. However, for some large life insurers, the line between banking ac vi es and insurance ac vi es has been blurred. Furthermore, the existence of insurance-based large financial conglomerates has drawn the a en-
on of na onal and interna onal regulatory bodies. Exam-ples are the systemically important financial ins tu on (SIFI) designa on process in the United States and the glob-al Financial Stability Board/IAIS effort to iden fy and desig-nate globally systemically important insurers (G-SIIs). The former includes insurance-led ins tu ons within its scope, and the la er is focused on such groups. I /Q O R Historically, organiza ons have accepted opera onal risk as an unavoidable cost of doing business. However, given op-era onal risk has become recognized as a dis nct risk cate-gory, the value of effec vely managing opera onal risk has increased considerably of late. While there is currently a huge demand for opera onal risk quan fica on, the actual management of opera onal risk has not evolved commen-surately. This is because opera onal risk is difficult to iden -fy and assess as the causes are extremely heterogeneous, thus making developing sta s cal models for opera onal risk challenging. There are many different types of opera-
onal risk and the extent of opera onal risk can vary based on qualita ve factors including corporate governance and the quality of internal controls in place. The Financial Times recently noted opera onal risk is the most amorphous and the hardest to protect against.7 A sound opera onal risk model extends well beyond the confines of a formula-based quan fica on. It encompasses a company’s business ac vi es and is an integral part of an efficient enterprise risk-management framework. An insur-
er’s underlying opera onal risk profile should be thoroughly reviewed across its range of business ac vi es in order to iden fy and es mate the model input requirements. The principal challenge is to combine two essen al sources of informa on: empirical loss data and expert judgment. Many companies have been leveraging the experience of the banking industry, which has been focused on opera on-al risk for more than a decade. The BCBS framework in-cludes seven dis nct types of opera onal risks varying in terms of frequency and severity.8 For example, internal fraud is a risk considered low frequency, high severity. Fre-quency and severity are vital in es ma ng poten al opera-
onal risk losses. However, historical data on the frequency and severity of losses are o en not available. Thus, uniform historical data upon which opera onal risk capital charges could be built is lacking. Most financial ins tu ons are s ll in the process of collec ng data. Organiza ons, such as the Opera onal Risk Consor um (ORIC), have begun to collect data from par cipa ng finan-cial ins tu ons to develop opera onal risk loss data consor-
ums. The ORIC database includes loss data provided by 225 large companies, including data from 16 core insurer mem-bers of the Associa on of Bri sh Insurers (ABI) and is focused on European opera ons. The database offers benchmarks against peers for loss experience comparison purposes and comparison of overall risk-management prac ces. The anon-ymized informa on is divided into eight categories with four severity levels and includes the frequency and amounts of loss events. Although there are poten al drawbacks to using self-reported data, it could be beneficial in iden fying trends. The informa on is used to generate management reports that assist companies in priori zing resources to iden fy and ad-dress control weaknesses in specific areas. Although the abil-ity to integrate the data into models for purposes of a pre-cise capital calcula on is not there yet, use of scenario analy-sis could improve an en es ability to avoid significant losses from opera onal risk failures.
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5 Vaughan, Therese M. “The Implica ons of Solvency II for U.S. Insurance Regula-on.” Network Financial Ins tute Policy Brief. February 2009.
6 Acharyya, Madhu. “Why the current prac ce of opera onal risk management in insurance is fundamentally flawed - evidence from the field.” The Business School, Bournemouth University, United Kingdom. 7 Masters, Brooke. “Opera onal risk muscles into focus.” Financial Times. November 25, 2012. 8 Basel Commi ee on Banking Supervision. “Opera onal risk transfer across financial sectors.” August 2003.
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O R I C R An opera onal risk event can cause severe losses and may lead to an insurer’s insolvency or near insolvency. Tradi on-al risk mi ga on approaches (e.g., internal controls, au-di ng) are not expressly designed for low frequency, high severity events.9 They are designed around capturing trans-ac onal errors, which tend to be of a manageable loss size, whereas opera onal risk in insurance en es originates mainly in other areas. It is, therefore, important to have an explicit opera onal risk buffer in the regulatory capital test to provide a buffer for costly opera onal risk events. This is being recognized by regulatory authori es around the globe, and has captured the a en on of the insurance in-dustry, as well. As noted above, databases (such as ORIC and others) are being developed and expanded to include volunteer data donors from the insurance industry. State insurance regulators, working together through the NAIC, have been looking at whether and how best to incor-porate internal and external aspects of opera onal risk more explicitly into the risk-based capital (RBC) formulas. In 2013, the Capital Adequacy (E) Task Force turned its a en on to opera onal risk. The Task Force’s Solvency Moderniza on RBC (E) Subgroup, Chaired by Alan Seeley of New Mexico’s Office of the Superintendent of Insurance, has been charged as follows: “Evaluate op ons for developing an opera onal risk charge in each of the RBC formulas and provide a recom-menda on to the Capital Adequacy (E) Task Force as to treatment of opera onal risk in the RBC formulas.” The Subgroup began by looking at how other jurisdic ons incorporate opera onal risk into their regulatory capital formulas, and received presenta ons from the Bermuda Monetary Authority and the Office of the Superintendent of Financial Ins tu ons Canada (OSFI). A third presenta on from the European Union (EU) covered the proposed regu-latory approach in Solvency II, which is not yet in effect. The Subgroup’s short-term goals include: iden fying appropri-ate risk exposure proxies; developing a simple factor-based capital requirement within the RBC formulas as early as 2014; and star ng a process for iden fying how and where the current RBC formulas could address opera onal risk. In the long run (three to five years to implementa on), the Subgroup plans to follow and provide input into further development and use of an opera onal risk database and other poten al qualita ve aspects that could lead to a more risk-sensi ve RBC approach. Recent NAIC ini a ves have also resulted in the adop on of the Risk Management and Own Risk and Solvency Assess-ment Model Act (#505), as well as corporate governance
standards as qualita ve means for considering internal op-era onal risk and some aspects of external risk via a group-wide assessment. An Own Risk and Solvency Assessment (ORSA) will require insurers to analyze all reasonably fore-seeable and relevant material risks (i.e., underwri ng, cred-it, market, opera onal, liquidity risks, etc.) that could have an impact on an insurer’s ability to meet its policyholder obliga ons. Resul ng from the NAIC’s SMI, large- and medi-um-size U.S. insurance groups and/or insurers will be re-quired to regularly conduct an ORSA star ng in 2015. Interna onally, methods to quan fy and model opera onal risks have mostly been captured using formulaic approaches (i.e., a factor applied to a base number line annual premi-ums revenue or defined assets or liabili es). Canadian capi-tal requirements for opera onal risk are formulaic, applying factors to risk exposure proxies with a focus on reten on of opera onal risk regardless of mi ga on strategies for other types of risks (e.g., reinsurance). Bermuda’s regulatory capi-tal formula includes a capital add-on that includes a qualita-
ve adjustment based on responses to a corporate govern-ance ques onnaire and possibly other inspec on or analysis findings. Solvency II requirements add the element of internal opera-
onal risk models to calcula ng regulatory capital require-ments. Solvency II includes a standard formula approach to opera onal risk that applies different factors to pre-established risk exposure proxies for life vs. non-life insur-ers. In addi on, there is an op on to use an internal model approach under Solvency II to establish a regulatory capital requirement for opera onal risk for insurance and reinsur-ance companies. The inputs to the models can vary based on the specifici es of the ins tu on’s business ac vi es, which can make comparisons across companies difficult. However the models are reviewed by regulators for sta s -cal integrity and conformity with internal capital models (the so-called “use test”). EU-U.S. I R D P In 2012, the EU and the U.S. completed a comparison of the U.S. insurance regulatory system with that of the three-pillar approach of the proposed Solvency II Direc ve in Eu-rope. This project, which looked at seven elements of regu-la on, is referred to as the EU-U.S. Insurance Regulatory Dialogue Project (EU-U.S. Dialogue) and is described in a final report issued in December 2012. One of the elements covered solvency and capital requirements.
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9 NAIC, Quan ta ve Impact Study No. 4, Opera onal Risk—Supplementary Infor-ma on. Retrieved from www.naic.org/documents/commi ees_e_capad_smi_sg_130327_opera onal_risk_2.pdf
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At the end of the EU-U.S. Dialogue, a number of future work streams were agreed upon to explore opportuni es to fur-ther harmonize the two systems. For capital and solvency, it was agreed, along with two other risk categories, to look at opera onal risk. Solvency II incorporates a provision for opera onal risk, and is in the development stages for U.S. RBC. The two sides will interact as follows: • The EU will share informa on on the methodology and
data used for calibra ng opera onal risk in Solvency II. This includes the recent delivery of a presenta on to NAIC staff currently responsible for the development of opera onal risk in the U.S.
• The U.S. will share informa on on the methodology and data used for calibra ng opera onal risk in RBC. This could include the U.S. coopera ng with EU coun-terparts during the ongoing work toward the defini on of a factor-based approach to opera onal risk to incor-porate in the RBC.
This ini al phase is tenta vely scheduled to run between now and June 30, 2014. In the longer-term, the par es might work together to develop/enhance an opera onal risk database. The EU has not embraced the ORIC database as yet, and the U.S. is interested in use of a database for its longer-term work on opera onal risk. This provides an area for further discussion and possible coopera on between U.S. and EU regulators. S Opera onal risk is now recognized as a major risk class across all financial ins tu ons. In the increasingly complex and interconnected global environment, the value of effec-
vely measuring and managing opera onal risk has in-creased significantly. State insurance regulators and the NAIC con nue to discuss opera onal risks, its possible inclu-sion into the RBC formulas, as well as its role in insolvencies and its interac on with other risk categories.
A A
Shanique (Nikki) Hall is the manager of the NAIC’s Center for Insurance Policy and Research. She joined the NAIC in 2000 a er working at J.P. Morgan Securi es in the Global Economic Research Division. At J.P. Morgan, she worked closely with the chief economist to publish research on the principal forces shaping the economy
and financial markets. Hall has more than 20 years of capital markets and insurance exper se. She has a bachelor’s degree in economics and an MBA in financial services. She also studied abroad at the London School of Economics.
Lou Felice is the health and solvency policy advisor at the NAIC. His role is to provide technical and policy analysis and advice to NAIC senior staff and leadership on solven-cy ma ers generally, including solvency impact of the federal Affordable Care Act, as well as advising on enhancements to U.S. RBC and represen ng the NAIC in
interna onal dialogues and projects relat-ed to solvency and capital requirements. Before joining the NA-IC, Felice served as chief of the Health Bureau at the New York State Department of Financial Services. Felice was co-recipient of the NAIC’s 2010 Robert L. Dineen Award for Outstanding Service and Contribu on to the State Regula on of Insurance.
NAIC Central Office Center for Insurance Policy and Research 1100 Walnut Street, Suite 1500 Kansas City, MO 64106-2197 Phone: 816-842-3600 Fax: 816-783-8175
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