Model Risk Management: Quantitative and Qualitative Aspects
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Request for Information and Comment: Financial Institutions' Use of Artificial Intelligence, Including Machine Learning
Request for Information and Comment: Financial Institutions' Use of Artificial Intelligence, including Machine Learning May 21, 2021 Dr. Peter Quell Dr. Joseph L. Breeden Summary An increasing number of business decisions within the financial industry are made in whole or in part by machine learning applications. Since the application of these approaches in business decisions implies various forms of model risks, the Board of Governors of the Federal Reserve System, the Bureau of Consumer Financial Protection, the Federal Deposit Insurance Corporation, the National the Credit Union Administration, and Office of the Comptroller of the Currency issued an request for information and comment on the use of AI in the financial industry. The Model Risk Managers’ International Association MRMIA welcomes the opportunity to comment on the topics stated in the agencies’ document. Our contact is [email protected] . Request for information and comment on AI 2 TABLE OF CONTENTS Summary ..................................................................................................................... 2 1. Introduction to MRMIA ............................................................................................ 4 2. Explainability ........................................................................................................... 4 3. Risks from Broader or More Intensive Data Processing and Usage ................... 7 4. Overfitting ............................................................................................................... -
Franklin Investors Securities Trust
STATEMENT OF ADDITIONAL INFORMATION FRANKLIN INVESTORS SECURITIES TRUST March 1, 2021 Class Contents A A1 C R R6 Advisor Franklin Adjustable U.S. Goals, Strategies and Risks ........... 2 Government Securities Fund FISAX FAUGX FCSCX — FAURX FAUZX Officers and Trustees ................ 59 Franklin Floating Rate Daily Access Fund FAFRX — FCFRX — FFRDX FDAAX Fair Valuation. 65 Franklin Low Duration Total Proxy Voting Policies and Procedures .... 65 Return Fund FLDAX — FLDCX FLDRX FLRRX FLDZX Management and Other Services ....... 69 Franklin Total Return Fund FKBAX — FCTLX FTRRX FRERX FBDAX Portfolio Transactions ................ 74 Distributions and Taxes ............... 75 This Statement of Additional Information (SAI) is not a prospectus. It contains infor- Organization, Voting Rights and mation in addition to the information in the Funds’ (hereafter “the Fund”) prospectus. Principal Holders .................... 86 The Fund’s prospectus, dated March 1, 2021, which we may amend from time to Buying and Selling Shares. 89 time, contains the basic information you should know before investing in the Fund. The Underwriter ..................... 96 You should read this SAI together with the Fund’s prospectus. Performance ....................... 98 The audited financial statements and Report of Independent Registered PublicAc - Miscellaneous Information .............101 counting Firm in the Fund’s Annual Report to shareholders, for the fiscal year ended Description of Ratings ................101 October 31, 2020, are incorporated by reference (are legally a part of this SAI). For a free copy of the current prospectus or annual report, contact your investment representative or call (800) DIAL BEN/342-5236. Mutual funds, annuities, and other investment products: • are not insured by the Federal Deposit Insurance Corporation, the Federal Reserve Board, or any other agency of the U.S. -
What Matters Is Meta-Risks
spotlight RISK MANAGEMENT WHAT MATTERS IS META-RISKS JACK GRAY OF GMO RECKONS WE CAN ALL LEARN FROM OTHER PEOPLE’S MISTAKES WHEN IT COMES TO EMPLOYING EFFECTIVE MANAGEMENT TECHNIQUES FOR THOSE RISKS BEYOND THE SCORE OF EXPLICIT FINANCIAL RISKS. eta-risks are the qualitative implicit risks that pass The perceived complexity of quant tools exposes some to the beyond the scope of explicit financial risks. Most are meta-risk of failing to capitalise on their potential. The US Congress born from complex interactions between the behaviour rejected statistical sampling in the 2000 census as it is “less patterns of individuals and organisational structures. accurate”, even though it lowers the risk of miscounting. In the same MThe archetypal meta-risk is moral hazard where the very act of spirit are those who override the discipline of quant. As Nick hedging encourages reckless behaviour. The IMF has been accused of Leeson’s performance reached stellar heights, his supervisors creating moral hazard by providing countries with a safety net that expanded his trading limits. None had the wisdom to narrow them. tempts authorities to accept inappropriate risks. Similarly, Consider an investment committee that makes a global bet on Greenspan’s quick response to the sharp market downturn in 1998 commodities. The manager responsible for North America, who had probably contributed to the US equity bubble. previously been rolled, makes a stand: “Not in my portfolio.” The We are all exposed to the quintessentially human meta-risk of committee reduces the North American bet, but retains its overall hubris. We all risk acting like “masters of the universe”, believing we size by squeezing more into ‘ego-free’ regions. -
Best's Enterprise Risk Model: a Value-At-Risk Approach
Best's Enterprise Risk Model: A Value-at-Risk Approach By Seabury Insurance Capital April, 2001 Tim Freestone, Seabury Insurance Capital, 540 Madison Ave, 17th Floor, New York, NY 10022 (212) 284-1141 William Lui, Seabury Insurance Capital, 540 Madison Ave, 17th Floor, New York, NY 10022 (212) 284-1142 1 SEABURY CAPITAL Table of Contents 1. A.M. Best’s Enterprise Risk Model 2. A.M. Best’s Enterprise Risk Model Example 3. Applications of Best’s Enterprise Risk Model 4. Shareholder Value Perspectives 5. Appendix 2 SEABURY CAPITAL Best's Enterprise Risk Model Based on Value-at-Risk methodology, A.M. Best and Seabury jointly created A.M. Best’s Enterprise Risk Model (ERM) which should assess insurance companies’ risks more accurately. Our objectives for ERM are: • Consistent with state of art risk management concepts - Value at Risk (VaR). • Simple and transparent methodology. • Risk parameters are based on current market data. • Risk parameters can be easily updated annually. • Minimum burden imposed on insurance companies to produce inputs. • Explicitly models country risk. • Explicitly calculates the covariance between all of a company’s assets and liabilities globally. • Aggregates all of an insurance company’s risks into a composite risk measure for the whole insurance company. 3 SEABURY CAPITAL Best's Enterprise Risk Model will improve the rating process, but it will also generate some additional costs Advantages: ■ Based on historical market data ■ Most data are publicly available ■ Data is easily updated ■ The model can be easily expanded to include more risk factors Disadvantages: ■ Extra information request for the companies ■ Rating analysts need to verify that the companies understand the information specifications ■ Yearly update of the Variance-Covariance matrix 4 SEABURY CAPITAL Definition of Risk ■ Risk is measured in standard deviations. -
EFAMA Response to ESMA Discussion Paper on UCITS OTC
EFAMA Reply to ESMA’s Discussion Paper on the Calculation of counterparty risk by UCITS for OTC financial derivative transactions subject to clearing obligations (ESMA/2014/876) EFAMA is the representative association for the European investment management industry. EFAMA represents through its 27 member associations and 63 corporate members almost EUR 17 trillion in assets under management of which EUR 10.6 trillion managed by 55,000 investment funds at end June 2014. Just under 36,000 of these funds were UCITS (Undertakings for Collective Investments in Transferable Securities) funds. For more information about EFAMA, please visit www.efama.org Preliminary Remarks EFAMA welcomes the opportunity to respond to the ESMA Discussion paper on the Calculation of counterparty risk by UCITS for OTC financial derivative transactions subject to clearing obligations (ESMA/2014/876). We understand that the contributions sought will concur to refine the “working assumptions” presented in the discussion paper in view of a further consultation and possibly further recommendations to the European Commission for amendments to the relevant parts of the UCITS directive. Considering the clearing options potentially available to UCITS as “financial counterparties” under EMIR - i.e. (i) become a direct member of a CCP, (ii) become client to a Clearing Member (CM), and (iii) enter into an indirect clearing arrangement – and the prevailing market practices, we acknowledge that, at this stage, option (ii) is certainly the most viable one. Already in its revised Q&A on Risk Management and Calculation of Global Exposure and Counterparty Risk for UCITS in December 2013, we took note of ESMA’s choice to not be too prescriptive on the clearing model chosen by UCITS and the recent discussion paper further reflects this by well illustrating the pros and cons behind direct and indirect clearing arrangements. -
2018-09 Interest Rate Risk Management
FEDERAL HOUSING FINANCE AGENCY ADVISORY BULLETIN AB 2018-09: INTEREST RATE RISK MANAGEMENT Purpose This advisory bulletin (AB) provides Federal Housing Finance Agency (FHFA) guidance for interest rate risk management at the Federal Home Loan Banks (Banks), Fannie Mae, and Freddie Mac (the Enterprises), collectively known as the regulated entities. This guidance supersedes the Federal Housing Finance Board’s advisory bulletin, Interest Rate Risk Management (AB 2004-05). Interest rate risk management is a key component in the management of market risk. These guidelines describe principles the regulated entities should follow to identify, measure, monitor, and control interest rate risk. The AB is organized as follows: I. Governance A. Responsibilities of the Board B. Responsibilities of Senior Management C. Risk Management Roles and Responsibilities D. Policies and Procedures II. Interest Rate Risk Strategy, Limits, Mitigation, and Internal Controls A. Limits B. Interest Rate Risk Mitigation C. Internal Controls III. Risk Measurement System, Monitoring, and Reporting A. Interest Rate Risk Measurement System B. Scenario Analysis and Stress Testing C. Monitoring and Reporting Background Interest rate risk is the risk that changes in interest rates may adversely affect financial condition and performance. More specifically, interest rate risk is the sensitivity of cash flows, reported AB 2018-09 (September 28, 2018) Page 1 Public earnings, and economic value to changes in interest rates. As interest rates change, expected cash flows to and from a regulated entity change. The regulated entities may be exposed to changes in: the level of interest rates; the slope and curvature of the yield curve; the volatilities of interest rates; and the spread relationships between assets, liabilities, and derivatives. -