“Beyond the Fundamentals: Anatomy of
The Perfect Credit Department”
ICTF
April 7, 2014
Pamela Krank
President
The Credit Department Inc. (TCD)
Pkrank@tcd.com
Agenda
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Characteristics of “Perfect” Credit Departments
Efficiencies vs Effectiveness
Process/Technology/Resource Maximization
Strategies for Moving toward Perfection:
• AR Valuation
• Bad debt Analysis
The Credit Department, Inc (TCD)
Background
•Manage global trade credit for 52
mid-market companies all over the world
•70,000+ bill-to customers
•150,000+ open invoices daily
•Consulted in nearly 500 global companies’
Credit Departments
“A Perfect Credit Department”
A Generalization:
Smaller vs Larger Credit Departments
•Smaller Credit Departments (less
than 10 members) tend to be more
efficient and less effective
•Larger Credit Departments (10+
members) are usually more effective but
less efficient
Top Consulting Observations on
Credit Departments
1.
2.
3.
4.
5.
6.
7.
8.
9.
Insufficient focus on managing top risks
High cost per credit analysis, collection
account, deduction management
Work arbitrarily assigned
No retrospection on missed opportunities
Write-offs common practice
Poor/incomplete use of internal data
Lack of sophisticated tools/technologies
Inconsistent decision-making
Policies/procedures not followed/enforced
How do we get our Credit
Departments more effective
while meeting our CFO’s
lower cost goals?
Profile of Perfect/Ideal
Credit Departments
1.
2.
3.
4.
5.
6.
7.
8.
One Standard Process flow
Credit Scorecards Utilized
Credit Committee Formed
Maximize Automation/Paperless
Department of Specialists
Best-in-Class results
Efficient cost structure
No surprises
Process Flow
• Credit Policy directs each process
• Only those who add value are a part of the
process.
• Credit resources are defined by impact of
risk on the receivables portfolio
• Collection activity is driven by default risk
and cash flow priorities
• Value in diagramming processes
Credit Scorecards
Credit Committees
• Representatives from Credit, Finance, Sales,
Marketing, Executive
• Build consensus on credit policy and
updates
• Meet regularly to deal with sales forecasts vs
existing credit limitations
• Deal with inter-company process issues
• Create a path for approving lines beyond
credit recommendations aka, business
decisions.
Technology
Expectations
•Automate routine processes (letters, scheduling,
statements, small lines)
•Allow the system to determine daily work queues,
not individuals
•Expect analysts to spend time working risks
alerted by the system
•Code every past due item with status, review
dates
•Focus is on reporting risks and customer
information to top management
Staff Resource
Utilization
Current Resource Utilization
Example
Most Effective Resource
Utilization
Staff size determined by history of
account management
Process & technology maximized
first before replacing/hiring new staff
Employees are all “generalists” who
do the same tasks regardless of asset
allocation needs. Work generally
divided by alpha, region, or
division/product line.
Duties assigned to specialists (ie
credit analysts, collectors, deduction
specialists) based on numbers of
credit files, past due accounts,
#’s/complexity of deduction files, etc
Obstacles to a “Perfect”
Credit Department
– Lack of upper management support
– Existing team members unable to identify
process change needs/implement scorecards
– Insufficient budget for technology
– Change reluctance by employees
– Limited resources
“No Surprise” Reporting Example
No Surprise Tool: Valuation
of the Receivable Asset
•Assign risk probability to every
credit customer
•Compare probability of default to
exposure
•Assign statuses to every past due
item with historical probability
•Calculate the risk
Existing Exposure Example
Based on Risk Probability
Total Aging: $16,610,000:
Customer A/R Totals in these
categories from scorecards:
•Very high VH (20%+): $500,000
•High H (10%+): $760,000
•Medium high MH (5-10%):
$1,250,000
A/R Asset Valuation
Risk of Credit Default
•Very high VH (20%+): $500,000 * .20 = $100,000
•High H (10%+): $760,000 * .10 = $76,000
•Medium high MH (5-10%): $1,250,000 *.05 =
$62,500
Total reserve (part 1) based on Customer Risk
of default in Credit process: $238,500
Value so far: $16,610,000-$238,500 =
$16,371,500
Delinquent Account
Status Reserve Example
Status
Past write-off Existing
experience
Status
Balance
Predicted
Defaults
Bankruptcy
95%
$122,000
=$115,900
Bad debt
100%
$115,000
=$115,000
3rd party
85%
$80,000
=$68,000
Collection
Attorney
60%
$48,000
=$28,800
Final Demand 40%
$180,000
=$72,000
Installment
Note
$350,000
=$70,000
20%
Total Probable Status Bad debt =$469,700
A/R Total Valuation
Report Example
•$16,610,000 gross value
•($238,500) Default Risk Probability
•($469,700) Account Status Default
probability
Total Net Value of the Asset:
$15,901,800
Bad debt
Analysis Example
Customer name/acct #
____________________ ___________
Bad debt written off
$______________
History of risk changes
__/___/__ date ____score $________ line
amt
__/___/__ date ____score $________ line
amt
__/___/__ date ____score $________ line
amt
Within policy limits?
___ yes ____ no
Missed Opportunity
__________________________
Comments
_____________________________________
_____________________________________
_____________________________________
Conclusion
• Perfect Credit Departments are both
effective and efficient
• We need to ensure our process,
technology, and people resources match
the needs of the asset
• There are changes and enhancements we
can all make to strive toward perfection in
Credit.
• Surprises ruin perfection….our job is to
prevent them from happening
Thank you!
Pam Krank
The Credit Department Inc (TCD)
pkrank@tcd.com
800-451-0164 X 203
www.tcd.com