Duplicate Payments: Remove the Noise of False Positives Karl - - PowerPoint PPT Presentation
Duplicate Payments: Remove the Noise of False Positives Karl Andersson, Founder Phone: 508-480-8990 Fax: 781-634-0500 www.technology-insight.com Webcast Logistics Collapse or expand the main menu Full screen or reduced screen Raise hand
Karl Andersson, Founder
Phone: 508-480-8990 Fax: 781-634-0500 www.technology-insight.com
Collapse or expand the main menu Send us your questions Full screen or reduced screen Raise hand
5 min
Background
5 min
What Can Go Wrong Assessing Your Risk
10 min
Definition Impact
10 min
Architecture Technology & Process
20 min
analysis solution developed specifically to empower A/P to drive:
– Business process – Special projects – Duplicate payment identification & recovery – Risk management
Data Entry Vendor Master PO Issues Receiving Part Master Electronic Feeds ERP Issues Supplier ERP Issues Procurement Card 2 Way Matching Billing Processes of Supplier Recurring Payments
Lower Higher
Risk
transaction volume use of system controls internal controls # of systems invoice processing
low
(< 100,000)
mid
(100,000 – 400,000)
high
(400,000+)
90% automated 10% manual One with pcard or t&e Two plus with pcard &/or t&e One no pcard or t&e 50% automated 50% manual 10% automated 90% manual
payments but is not
– Rent & lease payments – Utility – Contractual
– Highly accurate – Software users will use the obvious few – While captures many, also misses many.
– Cast net wider but capture a high volume
– Lacks refinement
1 Algorithms 200 High # of candidates Low
# of pairs of candidate duplicate transactions True duplicate payments Noise
require significant resource to review.
times.
– E.g. $2000 or higher
– E.g. Compare to transactions within last 6 months
1 Algorithms 200 High # of candidates Low
Cumulative total of duplicate payments recovered
Audit software results
Absolute # of duplicate payments
removes noise of obvious false positives
specific reporting needs on an ongoing basis
SAP PeopleSoft Oracle Legacy JD Edwards Lawson P-Card Any System T&E
Technology Insight DataShark ERP Independent Database
DataShark A/P
monthly, quarterly or annual
(153+ algorithms)
(150+ algorithms)
cross system cross vendor cross currency duplicate vendors data entry errors – all fields and more…
credits monthly / regular payments and more…
invoice systems:
SAP Oracle PeopleSoft JD Edwards Legacy Any system
Data Normalization Execute DataShark Technology
% likelihood & value
research & recovery with DataShark Tracking & Recovery tool
to continuously refine algorithms
true duplicate payment hit rate
algorithms to remove obvious ‘noise’
using proprietary DataShark Dashboard
each customer’s solution
Analyst Review & Customization DataShark A/P Delivery
Technology Insight classifies as “Best Buy”
Data from Procurement Card Company
– Data is cleaned & modified to create a Parent vendor master file. – A time consuming & manual process
TIC results
1 Algorithms 200 High # of candidates Low
Audit software results
Absolute # of duplicate payments
Cumulative total of duplicate payments recovered
Audit Software TIC’s DataShark A/P Savings # of Algorithms 10 153+ # of Candidates 1,500 290 80% Reduction # of True Duplicates 30 147 490% Increase # of False Positives 1,470 143 90% Reduction Savings $117,000 $573,300 $456,300 More to Bottom Line
Example Company: 100,000 invoices, average invoice size of $3,900
– Multiple systems – P-card and T&E
– No obligation to TIC
CEO and Founder direct: 508.281.4697 mobile: 617.233.3525 email: kandersson@technology-insight.com www.technology-insight.com
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