2. Andrew Hayden
Sr. Product Marketing Manager
PAUL OVIGELE
ERPfixers

6. Data
Process

15. •
•
•
•
•

16. What is ERPfixers?
ERPfixers provides top-quality experts in the major SAP modules.
ERPfixers Offerings:
• SAP Implementation and Support
• SAP Best Practices Assessment
• Material Ledger Conversion
• Enhanced Cost Component Reports
• S/4 HANA Transitional Roadmap
For more information go to www.erpfixers.com

17. How AI can be leveraged for SAP
Financial Processes

18. AI for Financial Master Data
Cleansing and standardizing master data entries,
ensuring consistency and accuracy across the system.
Performing real-time validation checks to ensure the
integrity of the data being entered
Preventing data inconsistencies intelligently merge or
eliminate duplicate records to maintain a single source
of truth
Continuously monitoring master data changes and
ensuring compliance with internal policies and
regulatory requirement

19. Accounts Payable (AP) Automation
❑ Streamlining invoice processing by using OCR to extract relevant data from invoices such as
invoice number, date, supplier information, line-item details, and amounts.
❑ Automating data extraction by eliminating the need for manual data entry and reducing errors
associated with manual processing
❑ Matching invoices with purchase orders against predefined rules, such as checking for
duplicate invoices, and verifying pricing and quantity discrepancies
❑ Accelerating payment cycles by routing invoices to the appropriate stakeholders for approval
based on predefined rules and thresholds.

20. Accounts Receivable (AR) Optimization
• Predicting cash flow based on analyzing historical payment data within SAP to identify trends
and patterns in customer payment behavior.
• Identifying late-paying customers by evaluating payment terms, average payment delays, and
frequency of late payments
• Segmenting customers based on their payment behavior, risk profiles, and other relevant
factors and categorizing them into groups with similar characteristics
• Leveraging external data sources, such as credit reports, financial statements, and industry
benchmarks, to enrich customer profiles and assess their creditworthiness.

21. Financial Forecasting and Planning
Source
Data • Integrating
data from
various
sources
within SAP,
including
historical
financial
data,
operational
data, market
trends, and
external
factors such
as economic
indicators
and industry
benchmarks
Pattern
Recognition
• Recognizing
recurring
patterns in
financial
metrics such
as revenue,
expenses,
cash flow,
and
profitability,
in order to
generate
insights into
future trends
Risk
Evaluation
• Evaluating
risks and
uncertainties
associated
with financial
forecasts by
analyzing
factors such
as market
volatility,
regulatory
changes,
and
macroecono
mic
indicators
Visualization
• Improving
decision-
making by
generating
visualizations
and reports
to
communicate
financial
forecasts
effectively to
stakeholders,
using
interactive
dashboards,
charts, and
graphs

22. Summary of AI Benefits for SAP Financials
Real-time
validation to ensure
data integrity
Automating data
processing and
extraction
Improving decision
making and
compliance
Detecting
anomalies
Predicting future
behavior based on
historical data

27. Speaker Bio
Paul Ovigele has worked as an ERP financials consultant
since 1997 in both North America and Europe, specializing
in implementing the FI and CO modules along with their
integrated areas for companies in various industries.
Paul speaks at numerous SAP conferences, offers
strategic and functional-level trainings to companies, and
is considered one the leading experts on Material Ledger.
Paul is the author of:
• 100 Things You Should Know About Financial
Accounting
• Reconciling CO-PA to the General Ledger
• Introducing the Material Ledger in S/4 HANA,
• Material Ledger in S/4HANA 1st & 2nd Edition