Transfer Pricing 21-Apr-2015 FINAL

Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Capital IQ®.Not for distribution to the public. Copyright © 2015 by Standard & Poor’s Financial Services LLC (S&P). All rights reserved.

Intercompany Financing:Determining Credit Quality And Pricing

Rick Kanungo, CFA, FRMSenior Director, Enterprise Solutions, S&P Capital IQ

Boris NemirovTax Principal, Deloitte

James ToomeyVice President, Regional and Global Accounts, S&P Capital IQ(Moderator)

April 21, 2015

Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Capital IQ®.Not for distribution to the public. Copyright © 2015 by Standard & Poor’s Financial Services LLC (S&P). All rights reserved.

Intercompany Financing:Determining Credit Quality And Pricing

Rick Kanungo, CFA, FRMSenior Director, Enterprise Solutions, S&P Capital IQ

Boris NemirovTax Principal, Deloitte

James ToomeyVice President, Regional and Global Accounts, S&P Capital IQ(Moderator)

April 21, 2015

3 Permission to reprint or distribute any content from this presentation requires the prior written approval of S&P Capital IQ. Not for distribution to the public.

Today’s Speakers

Boris Nemirov*Tax Principal

Deloitte

Rick Kanungo, CFA, FRMSenior Director, Enterprise Solutions

S&P Capital IQ

James ToomeyVice President, Regional and Global Accounts

S&P Capital IQ(Moderator)

*The views expressed by Mr. Nemirov are solely those of the author in his private capacity and do not in any way represent the views of S&P Capital IQ, its affiliates and/or any of its employees.


Topics Of Discussion

• Introductions and agenda

• Overview of credit and pricing challenges in intercompany financing

• Evaluating credit worthiness of unrated companies

– Approaches used in the industry; which ones are preferred

– Credit models: Methodology and case examples

• Pricing the intercompany financing instrument

– Approaches used in the industry, what are the challenges?

– Case examples

Corporate yield curve – methodology and case example

Z-spread curve – case example

Credit Default Swap (CDS) curve – case example

• Intercompany financing guarantees

– Reducing cost of debt; ceiling rate for guarantee pay based on spread differential


Overview Of Credit And PricingChallenges In Intercompany Finance

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Marketplace Changes

Rapidly evolving and recently volatile debt markets.

Jurisdictions

Growing list of countries requiring transfer pricing documentation.

Base Erosion and Profit Shifting initiative has focused the tax authorities’ views on debt issue.

Re-evaluation

Existing financing transactions may requirere-evaluation due to reorganization or upcoming financing needs.

Tax Authorities

Tax authorities are increasingly focused on intercompany cross-border financing transactions and are becoming more sophisticated and assertive.

Litigation

Increasing global incidence of tax litigation involving various intercompany financial transactions.

Ambiguity

Lack of specific guidance by tax authorities on the treatment of intercompany financial transactions.

Credit And Pricing Challenges In Intercompany Finance


Evaluating Credit Worthiness Of Unrated Companies:Approaches Used In The Industry

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• Can be used if borrower has recently issued debt to third parties

• Interest rate on debt issued to third parties may be used to infer an implied credit rating

Implied Credit Rating

• Estimate credit rating using third party software/ratings guidance and borrower’s financial data

Synthetic Credit Rating

• If group/parent credit rating is available: notching is possible

• Rating agencies provide guidance on adjusting group/ parent rating to arrive at subsidiary credit rating

Public Credit Rating

• The above analyses allow for the estimation of the issuer credit rating

• Additional consideration must be given to contractual and structural subordination in order to arrive at an issue rating

Credit Rating AnalysisThree approaches commonly used:

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Credit Rating Analysis

Bottom-Up Approach

• Relies on financial data of the borrower

• Maps a company’s financial ratios to acredit rating

• Pros:− Based on financial data of the specific borrower

− Takes the standalone credit worthiness of the borrower as a starting point

− Allows analyst to model the impact of contemplated debt on credit worthiness of the borrower

− Analyst can model the impact of qualitative factors such as implicit group / parent support,if appropriate

• Cons− May not fully account for qualitative factors that

ratings agencies take into consideration

Top Down Approach

• Uses parent or group rating as thestarting point

• Adjusts group/parent rating based on ratings agency guidance

• Pros:

− Relies on ratings agency analysis and opinion as the starting point

• Cons:

− Does not account for the credit worthiness of the borrower on a standalone basis

− Does not allow to model impact of additional funding on rating

− May not fully account for the qualitative factors at the borrower level that ratings agencies take into consideration

− Credit ratings are generally updated less frequently than financial data


Evaluating Credit Worthiness Of Unrated Companies:Why Certain Types Of Models Are Preferred

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Default ProbabilityEstimation Approach

• Typically relies on data collected by banks on Financing Instrument defaults

• Maps a company’s financial ratios to a Financing Instrument default probability, which correlates to a credit rating

• May be able to account for macro-economic factors

• Pros:

− Data may be updated frequently

• Cons:

− Credit ratings can be unstable because of frequent updates

− Results need to be calibrated to ensure a robust rating estimate

− Often more reliable for smaller companies

Credit RatingEstimation Approach

• Maps a company’s financial ratios directly to a credit rating based on the actual ratings of companies with similar financial characteristics

• Pros:− Credit ratings are updated less frequently,

leading to more stable results

− Correlates to basis on which capital markets data are available

− Reliable for companies of most sizes (above a min threshold)

− Does not require calibration

• Cons:− Data are not updated as frequently

Synthetic Credit RatingsThere Are Two General Methods For Estimating A Synthetic Credit Rating:


Different Approaches Used In The Industry


Standard & Poor’s Ratings: Group Rating Methodology

Anchor

Business risk: FairCountry risk: Very lowIndustry risk: IntermediateCompetitive position: FairFinancial risk AggressiveCash flow/Leverage: Aggressive

Anchor: bb-

Modifiers

Diversification/Portfolio effect: Neutral (no impact)Capital structure: Neutral (no impact)Liquidity: Adequate (no impact)Financial policy: Neutral (no impact)Management and governance: Satisfactory (no impact)Comparable rating analysis: Neutral (no impact)

Stand-alone credit profile (SACP) : bb-

Group credit profile: bbb+

Entity status within group: Moderately strategic (+1 notch from SACP)

Corporate Credit Rating: BB/ Stable/--

Source: http://www.standardandpoors.com/spf/upload/Ratings_EMEA/GroupRatingsMethodolgy19November2013.pdfAs of November 19, 2013.

Source: https://www.capitaliq.com/CIQDotNet/CreditResearch/SPResearch.aspx?DocumentId=30310144&From=SNP_CRSAs of: April 9, 2015

Identify the members of a group

Determine a Group Credit Profile

Assess Status of Group members• Core• Highly Strategic• Strategically important• Moderately strategic• Non-strategic

Determine the standalone credit profile of relevant group members (if required)

Assign potential Issuer Credit Rating. Take highest of:a) Assign potential issuer credit rating based om Group

Rating Methodology (or criteria for insulated subsidiaries)b) Assign a potential issuer credit rating based on

government support criteriac) Assign a potential issuer credit rating based on a credit

substitution guarantee

Apply constraints to the potential issuer credit rating (posed by sovereign or transfer and convertibility - T&C - assessment)

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2

3

4

5

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Methodology Excerpt Example: Subsidiary XYZ

Please note: Credit ratings are provided by Standard & Poor’s Ratings Services, which is analytically and editorially independent from any other analytical group at McGraw Hill Financial. For illustrative purposes only.

http://www.standardandpoors.com/spf/upload/Ratings_EMEA/GroupRatingsMethodolgy19November2013.pdf

http://www.standardandpoors.com/spf/upload/Ratings_EMEA/GroupRatingsMethodolgy19November2013.pdf

https://www.capitaliq.com/CIQDotNet/CreditResearch/SPResearch.aspx?DocumentId=30310144&From=SNP_CRS

https://www.capitaliq.com/CIQDotNet/CreditResearch/SPResearch.aspx?DocumentId=30310144&From=SNP_CRS


One Quantitative Approach: CreditModel®

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2

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Model Calibrated to:

• Standard & Poor’s ratings, not defaults

• Country or Region(grouped by country of risk)

• GICS® industry

Financial Factors

• Enter ratios or raw financials

• Financial factors depend on choices above

• Sensitivity (factor weights) change based on current values and are non-monotonic

https://www.spcreditpro.com/recoveryapp/docs/CreditModel_2_6_Technical%20_Reference_Guide.pdf Source: S&P Capital IQ. GICS = Global Industry Classification Standard. For illustrative purposes only.

https://www.spcreditpro.com/recoveryapp/docs/CreditModel_2_6_Technical%20_Reference_Guide.pdf

https://www.spcreditpro.com/recoveryapp/docs/CreditModel_2_6_Technical%20_Reference_Guide.pdf


Credit Score Of Subsidiary – CreditModel

Source: S&P Capital IQ; Scored on 4/3/2015. Lowercase nomenclature is used to differentiate S&P Capital IQ credit scores from the credit ratings issued by Standard & Poor’s Ratings Services. For illustrative purposes only.


Quantitative Approach 2: Probability Of Default (PD) Fundamentals

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2

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Features:

• Model calibratedto defaults

• Model for Financial Institutions

• Score entities of any size

https://www.spcreditpro.com/recoveryapp/docs/PD_Model_Public_Corporate_Fundamentals-Technical_Reference_Guide.pdfhttps://www.spcreditpro.com/recoveryapp/docs/PD_Model_Private_Corporate_Fundamentals-Technical_Reference_Guide.pdf Source: S&P Capital IQ. For illustrative purposes only.

https://www.spcreditpro.com/recoveryapp/docs/PD_Model_Public_Corporate_Fundamentals-Technical_Reference_Guide.pdf






Credit Score Of Subsidiary – PD Fundamentals

Source: S&P Capital IQ. Lowercase nomenclature is used to differentiate S&P Capital IQ credit scores from the credit ratings issued by Standard & Poor’s Ratings Services. For illustrative purposes only.

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Overview of Interest Rate Benchmarking• Interest rates on intercompany funding transactions are typically

benchmarked using third party Financing Instrument arrangements or third party securities data (e.g., bond data, preferred share data, etc.)

• Identical transactions often not available

• Adjustments can be made so that the third party transactions are comparable to the intercompany transaction’s terms

• Typical Financing Instrument agreement terms considered in pricing include:

– Amount– Interest rate– Fixed/floating rate– Active date– Tenor– Currency– Secured/Unsecured– Seniority

– Convertibility– Optionality (e.g., callable,

puttable, PIKable, etc.)– Fees (e.g., annual fees,

commitment fees, assignment fees, etc.)

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• Data related to primary and secondary Financing Instrument and bond transactions, including information regarding the characteristics of the debt. In addition to many others, this includes:

• Data for bond indices as well as for individual bond prices

• Primary and secondary market data for preferred shares

• Historical Libor, Euribor, etc.

Primary & Secondary Market Data

− Interest Rate − Credit Rating − Tenor

− Secured/Unsecured − Fixed/Floating Rate − Seniority

− Currency − Deal Amount − Country of Borrower

Adjustments

• Fixed/Floating rate adjustments made using Fixed/Floating swap rates

• Currency adjustments made using cross-currency swaps

• Tenor adjustments made using yield curve analysis

• Option adjustments made using option pricing models

Interest Rate Benchmarking – Data Sources


S&P Capital IQ Corporate Yield Curves

• Standard & Poor’s Ratings

Credit Quality

Candidate Sources:

• FINRA TRACE

• Trax (formerly Xtrakter)

• S&P Capital IQ Quote

Quotes, Trades

• Includes parsed quotes frombuy-side firms

• Highest consistency of prices for individual bonds

• GICS Sectors(10 sectors + non-financial composite)

• Currency• Maturity

Reference Data

Market Activity Grade:

# of trades/ quotes

• <4: not considered• 8 and above: 100% weight: • 4-8: linearly weighted (e.g. 6: 50% weight)

Term Structure:• Rich term structure coverage Clean

Input Data

Credits with rich term structure

coverage• Standard & Poor’s

Ratings

• Indicative quotes

• S&P Capital IQFixed IncomeTerms & Conditions

• GICS Sectors

Combined Spot Curves1. Curve Shape

Convertible to:

• Credit Spread

• Full Yield Curves

• Market Risk VaR and Conditional Scenarios

Bond issues with frequent daily price updates

FILTERING AGGREGATION

2. Curve Level

INPUT

Source: https://www.capitaliq.com/CIQDotNet/FixedIncome/CorporateYieldCurve/CYCUserGuide.pdf

https://www.capitaliq.com/CIQDotNet/FixedIncome/CorporateYieldCurve/CYCUserGuide.pdf




Corporate Yield Curves

Source: S&P Capital IQ. For illustrative purposes only.


Financing Instrument Guarantees

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Financing Instrument Guarantee Analysis – ApproachesInterest Rate Differential Analysis

• Credit score the debtor on a stand-alone basis

– If relying on synthetic rating, often done after adjusting financials for new funding

– Consideration may potentially be given to implicit support of group/parent

• Establish a range of interest rates between the actual rate (on a guaranteed basis) and the rate on a stand-alone basis

• Using interest rate differential as a starting point, determine a range of guarantee fees based on various factors (e.g., negotiating power of the parties, jurisdictions involved, cost of capital of guarantor, etc.)

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Guidance on Pricing Financing Instrument Guarantees

• United States

– Treas. Reg. Sec. 1.482-9 excludes financial guarantees from the Services Cost Method

• Canada

– GE Capital case

Guarantees have more than a nominal value

Affirmed use of yield differential approach

Recognized passive association by modifying rating for implicit support (for which the guarantor was not compensated)

• Rest of the world

– In some cases there has been acceptance of the basic premise of employing the stand-alone rating as a starting point for the calculation of guarantee fees (UK)

– In other jurisdictions, guarantee fees are treated as equity payments (Germany)


Q&A


Boris Nemirov*Tax Principal

Deloitte

Rick Kanungo, CFA, FRMSenior Director, Enterprise Solutions

S&P Capital IQ

James ToomeyVice President, Regional and Global Accounts

S&P Capital IQ(Moderator)


Thank You

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BiographiesRick Kanungo, CFA, FRMSenior Director, Enterprise Solutions, S&P Capital IQRick has nineteen years of industry experience and has been with the firm for seven years. Currently, he is responsible for Strategy, Thought Leadership and Go-To-Market activities for Enterprise Solution products at S&P Capital IQ, a McGraw Hill Financial brand. Enterprise Solutions is the data feed and content licensing business for S&P Capital IQ. Previously, Rick managed a global team of subject matter experts responsible for lending pre-sales expertise on analytical products and for delivering thought leadership. He was also a product manager for two analytical products with responsibility for development and commercial strategy. His prior industry experience includes credit analysis at S&P Ratings, private equity at Credit Suisse and prime brokerage at Chase, Lehman and Merrill. Rick holds an MBA from the Yale School of Management with concentrations in Finance and Investment Management. He is a member of the CFA Institute where he is a registered Chartered Financial Analyst and the Global Association of Risk Professionals (GARP) where he is a certified Financial Risk Manager.

Boris Nemirov*Tax Principal, DeloitteBoris Nemirov is a Tax Principal in the New York office of Deloitte Tax LLP’s Transfer Pricing Group. His experience includes sixteen years of transfer pricing economic consulting, since joining Deloitte in 1999. Over the years, Mr. Nemirov consulted on a multitude of transfer pricing issues and led the preparation of transfer pricing documentation and planning studies in a variety of industries for both inbound and outbound taxpayers. In addition, Mr. Nemirov has worked on a number of business model optimization, restructuring and intellectual property projects, involving the valuation of intangible assets, derivation of platform contributions and development of royalty rates. Mr. Nemirov has also consulted on and defended under audit headquarters cost allocation issues. Mr. Nemirov’s experience includes negotiating bilateral advance pricing agreements involving the tax authorities in the United States, Canada and Japan. Furthermore, Mr. Nemirov specializes in financial transactions transfer pricing focusing on intercompany financing, factoring, risk transfers, guarantees and cash pooling arrangements. He also leads numerous global transfer pricing documentation engagements for multinational clients. In recent years, Mr. Nemirov worked on several planning engagements aimed at enhancing and streamlining, from a tax and transfer pricing perspectives, business changes and costcutting initiatives of several multinational conglomerates. Mr. Nemirov has also led engagements for multinational companies with the objective of improving the intellectual property ownership structure for better alignment with business objectives and natural organic growth of the organizations. Mr. Nemirov is the U.S. Transfer Pricing Technology Leader and spearheads the Operational Transfer Pricing and Data Analytics initiatives partnering with the Tax Management Consulting Group to deliver these cutting edge solutions to clients. Mr. Nemirov was heavily involved for many years as a subject matter specialist in, and now globally leads, a project to design the next generation transfer pricing modeling and reporting software that has already been successfully used by the group worldwide for over five years. He is also responsible for managing all software and databases utilized by the U.S. transfer pricing practice. Mr. Nemirov is a Deloitte Faculty Excellence certified facilitator and has, for the past ten years, actively participated in and served as the Dean of a multitude of national training programs. Finally, Mr. Nemirov is a frequent speaker at the Tax Executives Institute events and numerous Deloitte internal and external conferences. Mr. Nemirov also actively participates in many national initiatives, including those aimed at Deloitte Tax’s response to BEPS and appeared in the 2013 Guide to the World's Leading Transfer Pricing Advisers. Mr. Nemirov holds a B.A. in Economics and an M.B.A. in Finance & Accounting.

James ToomeyVice President, Regional and Global Accounts, S&P Capital IQJim is responsible for Desktop and Enterprise Solutions for the global consulting market across S&P Capital IQ delivering high quality data, analytical tools and ratings information. Jim has experience in the money management, investment banking and private equity markets delivering S&P solutions in a consultative sales role and is a designated Subject Matter Expert (SME) for content verticals for Transfer Pricing, Executive Compensation, Litigation Consulting and Valuation. Jim leads the Global Consulting Sales team coordinating large sales across enterprise organizations. Examples of the subject matter Market Segments include Tax Transfer Pricing (example: Big 4 Accounting firms), Executive Compensation Consulting (example: Towers Watson, AON Hewitt), Litigation Consulting (example: CRA International, Bates White), Valuation (example: CBIZ, Big 4 Accounting firms), Audit (example: Big 4 Accounting firms, BDO Seidman, Grant Thornton), Strategy and other Management Consultants (ex. McKinsey, Accenture). Jim joined S&P Capital IQ as an Analyst at Compustat, was an Account Manager for S&P Capital IQ Equity Services and served as a Senior Director for IHS Economics (DRI) specializing in Industry analysis. He initiated the Redistribution Strategy Sales team and marketed S&P Dow Jones Indices to the investment community. Jim coordinates delivery of information to global revenue authorities and the international consulting community. He has over 10 years of experience in Transfer Pricing and recently chaired a round table on the effects of FIN 48 on Transfer Pricing. Jim has a Bachelor’s degree from the University of Colorado and completed the Certified Financial Planner (CFP) designation from the Certified Financial Board of Standards in Washington, DC. He has been recognized with multiple S&P sales awards and recently by the Australian CPA Society for his work in Asia Pacific. He is a member of the International Transfer Pricing Professionals Group, Transfer Pricing Economists, Content Management Specialists and the Executive Compensation Network.


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Transfer Pricing 21-Apr-2015 FINAL