Create a Bad Debt Early Warning System Meeting Start Time will be 10:03 Pacific Time
Agenda • Session objectives • Current challenges facing AR departments • Review of current credit tools • Introduction of payment trending as a new tool • Late payment calculation discussion • Rules based risk identification • Controlling customers via inbound order hold/release process • Challenges • Opportunities for improvements • ERP enhancements • Questions
Cforia Software • Cforia is a market leader in AR automation software with 140 accounts world-wide managing over $80 Billion in yearly AR • Dozens of ERP applications supported including SAP, Oracle, JDE, PeopleSoft, etc… • AR automation is designed to: • Reduce bad debt • Decrease DSO • Improve deductions processing • Headcount avoidance or reduction
Chris Caparon • VP of Professional Services for Cforia Software • Education: BSEE, BSCE from the University of Michigan • 10 years of ERP implementation experience • 7 years of managing Cforia’s software services team • Personally lead over 100 AR automation projects
Challenges Accounts receivable is a top asset on your company’s balance sheet Its the most at-risk balance sheet asset from the credit crisis Cash flow is a priority Decreasing or flat sales Tighter credit policies Staff reductions the norm World-wide DSO will be increasing for the foreseeable future As companies will hold onto their money longer Companies with less access to credit will be a challenge
Challenges Continued Deductions and charge backs from retailers will increase as their margins tighten Bad debt is a new and real threat Your AR is a bank for your customers Are they a good risk?
"Watch your receivables like a hawk." - Jerry York, CEO of Harwinton Capital on the coming recession, during CFO Rising, March 2008
Credit Control– Current State Customer Credit -Current State Tools
Hierarchy of Tools • Agency reviews – (DnB, Experian, etc…) • Establish initial credit limits • Latency of data • Each database has holes • Intuition and business intelligence • Credit and peer groups • Collector/analyst interaction • Media and news • Financials and credit scoring • When to trigger? • Credit checking in ERP system • Held order management
New Tools and Techniques • Payment Trending to identify at-risk customers • Leveraging payment trend information locked within your accounting system to alert you to customers at risk • As customer liquidity decreases - their payment timing degrades over time • Deploying that business intelligence within your ERP system by upgrading your credit checking and order management logic • Credit limit management
Payment Trend Analysis • We are going to explain how you can mine this information within your own databases
Let’s Discuss Terminology • DSO vs. DBT • DSO (Days Sales Outstanding) • Excellent business metric • Calculation is inappropriate due to sales variable • DBT (Days Beyond Terms) • Extremely predictive tracking mechanism • It can be calculated from everyone’s database
Terminology Continued • Credit Rating vs. Credit Risk • Credit Rating • Agency driven • Credit Risk • Internal assessment based upon your decision criteria • Can be very different than ratings
Establish Guidelines • The amount of degradation is a key control mechanism • Place thresholds in your calculations to notify the credit managers when customers cross the line • Drives credit risk classification • Use that as a trigger mechanism to engage your existing credit scoring tools or use Cforia’s consolidated credit reporting platform • Credit limit changes • Credit risk establishment
Consolidated Credit Reporting • Edgar Online provides financials up-to-date within 24 hours including: P&L, Balance Sheet, Cash flow and ratios over 4 years • Equifax USA offers financial trade (bank info); Commercial credit cards, LOC’s (Business Lines of Credit), Business Loans and Leases, and industry specific trade data reporting millions of tradelines. • Access to consortium of 350 banks credit databases (SBFE) • Equifax Canada has the largest and most complete database for Canadian Commercial Credit Reports for companies going back over 100 years.
Consolidated Credit Reporting • Experian has the most Commercial Collections with over 250 agencies reporting business bad debts and thousands of companies reporting industry trade data. • Experian also provides Business Owner Scores and credit reports with FICO scores from Experian and Fair Isaac. • Graydon International houses the most comprehensive International database, with over 60 million Commercial Cedit Reports from more than 130 countries. • LexisNexis provides Bankruptcy, Tax Liens, Judgments, Corporate Info and UCC’s.
Create a set of rules that Automate sections of your AR database - In this case, a credit rule (#1)
Assign different risk classes (sub group) based On % DBT percentage
The sub group detail is where you set your thresholds
The list of companies are displayed for review
Automated Credit Reports
Collectables – Clean receivables Disputes – Dirty receivables Deductions- Dirty receivables AR Database’s are Complex • Clean Receivables • Collectables : transactions that are not disputed & whose receipt can be forecast • Dirty Receivables • Disputes : transactions that disputed and not paid • Deductions : transactions that are customer debits
Headquarters Parent Parent Customer Customer Customer Customer Customer Invoice Deduct Credit Invoice Deduct Invoice Credit Invoice Invoice Customer Structures are Challenging
The Failure of ERP • Most, if not all, ERP systems fail to deliver accurate DBT data • ERP systems are woeful for creating trending over time information • Rely on BI tools and report writers • The data delivered does not reflect the customer’s actual payment patterns • The underlying calculations are not transparent or flexible to meet the unique needs of companies
DBT Considerations • Create a DBT value that accurately scores the customers payment pattern • Understand that they can be negative! • Select time intervals (week, month, 90 days) • Also look at open invoice DBT • Filter out deductions, credits, disputed late pays • How do you flag disputes in your systems? • Can be product dependent • Service vs. spare parts • Minimum transaction value • Weighted average • Set to zero for certain customer types • Employee, demo’s, inter-company, etc… • Measure at the customer or parent level? • Different calculations by customer type?
Trigger for Action • Once a customer hits a threshold, it is a call to action • Automatic customer, sales rep notification via AR Automation tool • Credit reviews • Financial statement requests and credit scoring • Credit group discussions • The reevaluation of their credit limit
ERP System Challenges • Credit checking process in all unmodified ERP systems does not meet the needs of most businesses • Math used to check credit in ERP systems • (Open AR + Open Orders)/credit limit • Blanket Orders and seasonality create problems • We need to change how your order entry credit checking system works • As a result, order hold & release can be very manual and labor intensive
Goals • Create an order credit checking process that aligns with your optimal credit policy • Minimize the number of nuisance holds to enable your credit department to manage by exception
Additional Criteria Required • Credit Risk • Collection strategy • DBT trending • Specific age bucket values • What about disputes and deductions? • # late payments over time period • Date of last credit review • Commit windows to filter out future orders • Last order date
ERP Improvements • This is a hard modification to most systems • Order entry program must be opened • User exits may exist • Requires IT support and programming • ERP may not have enough data to support your desired decision tree • What is the right criteria to make you trust and defend the result?
Conclusion • Establish criteria for DBT calculations • Benchmark customer DBT data • Evaluate current triggers for reviewing credit files • Put scheduled automated process in place • Month end is a great start • Tune your order credit checking process to eliminate nuisance holds • Eliminate non value adding activities