Learning Objective:
Participants will develop the skills to assess economic
conditions, internal and external factors that can
influence projected data. Financial modeling tools
used in this course will provide a foundation for
future analysis of asset based lending cash flows.
CPE Credit:
8 Hours
Prerequisites:
Excel 2000 or higher and an understanding of basic Excel
functions such as SUM, IF statements, and editing
commands. At least one year of financial analysis
or accounting are recommended.
Advanced
Preparation: Computer should have Excel
installed. A cash flow model will be distributed
at the start of the course and students must be able to
download or copy the course Excel model.
Delivery Method:
Group Internet (Webinar) Group Live upon request
Course Level:
Advanced
Registration:
Contact Clear Choice Seminars, Inc. at
www.ccsiweb.com
(see Contact page)
or by phone at 410 747-7994 for more information and
pricing.
Background
Asset Based Lending has a unique cash position in a company that causes funding from the
lender to be a source of cash, while receivable collections act as a reduction to the
loan. Borrower projections can include numerous assumptions and business rules that
are fine for managing the business, but don't address the special cash flow economics of
Asset Based Lending. Finally, the business environment, industry and overall
economic trends are often presented by the borrower, with little research or testing from
the lender. Topics such as EBITDA, Interest Coverage, Debt Coverage and of
course ABL specific changes in working capital are all covered.
Many lenders and accountants have simply "plugged" the revolving loan component
to get the balance sheet to balance. Special models and tools are needed
to assess Asset Based Lending cash flows, but developing these tools in-house
and teaching people to use them would be a large project. This course
comes with an Asset Based Lending cash flow model in Excel.
Since the "book" and projections presented to the lender will paint the company
in the best possible light, analysis of the industry and economic factors should be done
outside of "the book." Cash Flow Analysis for Asset Based Lending teaches
classic analysis methods and the newest internet research methods to help the lender
understand the business environment of a new transaction.
Students are taught to look at the numbers and analyze trends. The focus is:
-
Industry analysis
-
Classical and internet research tools
-
Cash flow model assumptions
-
Practical case study using the cash flow model
-
Integration of field examination findings in analysis of projections
-
Analysis of the cash flow model results with sensitivity testing
Benefits of This Course
Lenders in the Asset Based Lending profession need tools to analyze projections that
include cash sources from revolving lines of credit. The overview and traditional
analysis tools shown in the course will serve as a guide to research different businesses
and to seek more information about a business, even after the deal is booked.
The course model is an excellent tool to teach students the economic timing of ABL cash
flows and will serve as a strong analysis model for real-world transactions. By
using the model, students will learn about the impact of operating cycle turnover and cash
flow timing, while having the ability to test the sensitivity of model assumptions in
dozens of areas.
Course Requirements
Students can include account officers, field examiners, financial analysts and other
professionals engaged in the analysis of projections for Asset Based Lending.
A computer will be needed for each student. All machines should have some version of
Windows (XP, Vista, Win7, Win8) and licensed versions of Excel. An
understanding of spreadsheets is useful, but not required. All students will need
calculators.
Materials You Keep
A well documented ABL Cash Flow Model in Excel is presented along with a
detailed "cook book" of line-by-line inputs. The cash flow model includes
tabs for the ABL Cash Flow Model, EBITDA adjustments and Tangible Net Worth
analysis. Models from the borrower can easily be linked into the input
fields.
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