Protecting Against Payment Fraud in SAP S/4HANA

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Protecting
Against Payment
Fraud in SAP
S/4HANA
1

Payment Fraud has increased with the shift to remote
work
2
82%
Percent of
companies
reported being
targets of payment
fraud in 2019 *
75%
Percent of
organizations who
experienced
Business Email
Compromise (BEC)
in 2019*
54%
Percent of
organizations
reporting financial
loss as a result of
BEC*
58%
Percentage of
payment fraud
committed by an
individual outside
the organization*
As of 9/22/2020 the FTC had 205,000 reports of fraud linked to
coronavirus since the beginning of the year. **
According to Barracuda researchers, 2020 Payment Fraud
increase 667% from February to March
3
1
Americans have lost over $145 million due to these COVID-19
related scams according to the Federal Trade Commission
(9/22/20) **
2
COVID-19 and Payment Fraud
* 2020 AFP Payments Fraud & Control Survey ** 2020 Federal Trade Commission Report

Fraud Statistics from 2020 AFP Study
3

Question 1: Who in your organization is
responsible for managing payment fraud?
4
A. Compliance / Risk
B. Finance
C. Accounts Payable
D.Treasury
E. IT

Preventing Fraud – A Shared Responsibility
• Workforce Education & Training
• Standardized Controls and Approval
Processes
• IT Security Policies
• Technology Solution

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Source: 2020 AFP Payments Fraud and Control Survey
Employee Education and
Training are critical
• Policies - verify changes:
invoices, bank & contact information
• Confirm requests using system of
record information
• Institute Strong Internal controls
that prohibit payment initiation
based on emails

Standardize Controls and Approval
Processes
7
Paymen
t
Request
Payment
Initiation
Payment
Approval
Payment
Documentatio
n
Payment
Transmission

IT Security Policies
• Embrace the Cloud
• Network Security
• Application Security
• Vendor / Third Party Security
8

Question 2: What is the biggest challenge for
your company in managing fraud?
9
A. Lack of resources & commitment from
Management
B. Lack of internal expertise to design & implement
controls
C. Difficulty to identify the right set of tools and data
D. Hurdles related to implementing & maintaining
the tools

Enterprise Connectivity and Payment Complexity
10

Payment hub
11
Single Payment file from SAP via API Deconstruction and
reconstruction transforming to required bank format. Fraud
Detection (rules & ML)

12
Payment Fraud Prevention
Detection Rules
• Real time screening
• User Defined rules
• Resolution Workflow
Machine Learning
• Algorithm to detect
anomalies
• Detect variances in historical
trends
• Learn against the data
Rapid Deployment
• Deploy in days/weeks
• Manage all payments
across the enterprise
Sanction Screening
• Screen before bank
• OFAC +30 global lists
• Avoid banking fines
kyriba

Sanction Screening prevents payments to
unauthorized entities!
13
More and more sanctioned
entities, frequent updates
of the sanctions lists

Fraud Rules can be identified
1st payment to a bank account
but for an existing vendor
Payment to a country where you
have no business
Modification of a payment
imported from back-office
Anomaly compared to your
payment history
High number of payments
to the same vendor
Modification of a sensitive
field
Vendor, beneficiary bank or
country blacklisted according to
a sanction list
Payment to high risk
countries

Machine Learning to detect payment
anomalies
Detect new fraud patterns
Provider managed process –
you shouldn’t have to worry
Get alerted when a payment is
an anomaly compared to the
payment history
Obvious anomalies Limited signals of possible fraudAmbiguous anomalies
Machine Learning Model
Implement the rules to comply with
internal policies
Benefit from a large scope of anti-
fraud controls
Be in control of when you get
alerted
Rule-based engine
15

Question 3: Are you actively seeking a technology
solution to identify and prevent fraud?
16
A. Yes
B. No
C. Not Sure

• Multiple ERPs with different approval
processes
• Regional treasury/shared services require
lesser numbers of approval due to limited in-
country staff
• CEO and/or CFO have ability to execute or
influence payments with only one other
approval
• Payments backup documents stored in a
different system than payment approvals
• Payment files can be opened and modified
• Lack of automated detection for duplicate
and unusual payments
Scenarios that are ripe for payments fraud

Fraud Examples: Breakdown of
Controls
• Global Financial Services Firm – lost $18M in a
phishing scheme.
• Toy Manufacturer nearly lost $3M in a BEC
scheme. That they got their money back was
timing.
• Tech Firm – released $1.2M wire from
Deepfake CFO impersonation
• Automotive Component Manufacturer
received email request to send $4billion yen
($37 million) to a third party

What is at stake?
• Loss of Funds
• Loss of Job
• Exposure of Confidential Data
• Regulatory Risk (dependent on industry)
• Reputational Risk

Why clients
are not as
protected as
they believe:
• “My bank will cover me”
• “We have cyber security insurance”
• “We have approval process in place”

Thank You!
Questions?
Kirsten Lemke
Kyriba
Kirsten.Lemke@Kyriba.com
612-868-9300

Protecting Against Payment Fraud in SAP S/4HANA

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