CUFT Database

Beginning in 2009, CUFTanalytics has sourced publicly filed credit agreements from the United States Securities and Exchange Commission using its proprietary search algorithm.  The documents are reviewed, and the data is gathered and maintained in a database (the “CUFT Database”).  In addition, we add to this transactional data the most current credit risk data (Standard & Poor (S&P)’s and Moody’s Investor Services credit ratings and S&P’s Creditscores).

CUFTanalytics uses this data for consulting purposes, however the senior loan data from the CUFT Database is licensed to Bureau van Dijk for inclusion in their transfer pricing solution, TP Catalyst.  For more details regarding subscriptions to the loan module within TP Catalyst please see their website

Built specifically for transfer pricing purposes and the data is supported by the actual credit agreements.  The data is available to subscribers of Bureau van Dijk’s TP Catalyst solution.

On average, we add roughly 1,100 to 1,200 senior loan records to our CUFT Database each year.  The below tables provide a snapshot of our senior loan database:

 

Based on Credit Risk Measures

Avg Credit Rating Total 2016 2015 2014 2013 2012 2011 2009 - 2010
A- and above 219  40  49  33  15  22  46  14 
BBB- to BBB+ 1,067  190  186  183  131  139  140  98 
BB- to BB+ 1,577  238  250  221  243  221  197  207 
B- to B+ 1,507  202  149  229  265  236  190  236 
Below B- 144  30  16  18  17  10  45 
Total Rated 4,514  700  650  684  671  626  583  600 
Total Non Rated 3,640  501  521  458  473  480  519  688 
Total Records 8,154  1201  1,171  1,142  1,144  1,106  1,102  1,288 

* Note that the average credit rating is the average between the respective Moody's credit rating and the S&P credit rating for the borrower. If the borrower is rated by just one of those rating agencies than the average rating is the rating given by the rating agency that has rated the borrower. If the ratings of the two rating agencies differ by an even number of notches it is the middle rating that is the average credit rating. If the ratings differ by an odd number of notches then the average credit rating is calculated as the upper rating less (n - 1)/2, where n is the number of notches that the credit rating agencies differ.

 

S&P Creditscore Total 2016 2015 2014 2013 2012 2011 2009 - 2010
a- and above 471  69  95  80  37  66  75  49 
bbb- to bbb+ 2,020  285  296  283  271  276  336  273 
bb- to bb+ 2,687  405  369  342  348  391  407  425 
b- to b+ 2,355  312  312  361  387  278  210  495 
below b- 273  57  43  41  53  23  22  34 
Total Scored 7,806  1,128 1,115  1,107  1,096  1,034  1,050  1,276 
Total Non Scored 348  73  56  35  48  72  52  12 
Total Records 8,154  1,201 1,171  1,142  1,144  1,106  1,102  1,288 

 

 

Based on Industry

Major Industry Group SIC codes Total 2016 2015 2014 2013 2012 2011 2009 - 2010
Agriculture, Forestry & Fishing 01 to 09 57  12  11 
Mining 10 to 14 379  42  43  61  63  57  52  61 
Construction 15 to 17 155  23  30  20  22  23  22  15 
Manufacturing 20 to 39 3,563  554  577  465  453  463  478  573 
Transportation, Communications, Electric, Gas & Sanitary Services 40 to 49 1,217  169  173  159  177  189  145  205 
Wholesale Trade 50 to 51 363  60  45  58  60  49  53  38 
Retail Trade 52 to 59 645  99  80  101  99  83  81  102 
Finance, Real Estate & Insurance 60 to 67 95  20  14  14  18  15 
Services 70 to 89 1,680  238  196  255  244  220  250  277 
Totals 8,154  1,201  1,171  1,142  1,144  1,106  1,102  1,288 

 

Did You Know?

The senior loan data from the CUFT Database is subscribed through BvD's TP Catalyst by tax administrations, multinational corporations and large and small accounting and tax consulting firms across the world spanning nearly 30 different countries.  Contact Us to learn more.

Featured Pages

  • CUFTanalytics regularly publishes transfer pricing research and analysis - Learn More
  • The case between Chevron Australia and the ATO has been decided - Learn More
  • CUFTanalytics posts the latest news on BEPS for intercompany financial transactions - Learn More
  •  

Recent Publications

  • Intercompany Financial Transactions:

    Factors to Consider In Analyzing the Impact of Implicit Support
    (Bloomberg BNA: 20/2/2014)

  • Transfer Pricing and Intra-group Cash Pooling:

    (Bloomberg BNA: 14/2/2011)

  • Intercompany Financial Transactions:

    Selecting Comparable Data 
    (Bloomberg BNA: 22/4/2010)

CUFTanalytics

A Calgary Alberta Canada company
Email: inquiry@cuftanalytics.com
Copyright 2017 by CUFTanalytics Terms Of Use Privacy Statement
Design: CuftClassic by IPW