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Jakarta Business Networkers
Fraud and Corruption in Indonesia
Consulting
Strictly private
and confidential
12 October 2017
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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Indonesia probes corruption related to Rolls-Royce and AirbusFormer chief of state airline Garuda placed under investigation
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Fraud and Corruption in Indonesia
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Fraud and Corruption in Indonesia
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Jakarta Business Networkers
Fraud and Corruption in Indonesia
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Agenda 1
Agenda Executive Summary Executive Summary
Fraud is everywhere
Executive Summary
9
2 Fraud triangle 11
3 Anti-corruption efforts and their effectiveness / KPK-'statistics' 18
4 Real life fraud cases 23
5 Suspicious Transaction Analysis 36
6 What can you do? 45
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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Fraud is everywhere
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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9
There are many kinds of financial crime
• Financial statement fraud
• Procurement fraud
• Bank card and cheque fraud
• Cyber fraud
• Counterfeit goods fraud
• Employee fraud
• Money laundering
• Tax fraud
• Insurance fraud
• Expense claim fraud
• Misappropriation of assets
• Insider trading
• EtcJakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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Fraud triangle
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Fraud and Corruption in Indonesia
PwC
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Rationalisation
• I’m doing the Company a favour.
This will definitely enhance
shareholder value
• I’ll help expose my Company’s
internal control weaknesses
• I’ll just borrow the money and return
it later
• I deserve it since I’ve sacrificed so
much for the company…
Incentive – fraud is often committed
because perpetrators are in some
form of financial difficulty or need
(e.g. gambling, drugs, living beyond
means, etc.)
• Pressure to meet loan covenants or
forecast numbers
• Pressure to meet market expectations
Opportunity
• Fraudsters are in the right position at the right time
• They recognise and seize the opportunity to commit fraud
• They understand operations, policies and procedures, and have access to
records/funds
It is generally accepted that the following three conditions must be present for fraud to occur:
Opportunity
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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RationalisationIncentive
!Fraud
Introduction to the Fraud Triangle
What is corruption?
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Corruption Fraud
vsOffering or receiving something
to Influence improperly the action
of another party
Action of misrepresentation that
knowingly is misleading
to gain financial benefit or avoid
obligation
Reported bribery and Corruption, by region
27%
12%
14%
25%
30%
35%
39%
39%
24%
12%
7%
19%
32%
43%
36%
34%
10% 50%
Global
Western Europe
North America
Latin America
Asia Pacific
Middle East*
Eastern Europe
Africa
20% 30% 40%
% of all respondents who experienced economic crime over the survey period
2011 Global 2014 GlobalJakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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0%
*Indonesia and Middle East included in
the “Asia Pacific” region in 2011
Source: PwC GECS
Source: Transparency International
2 Fraud triangle
90 Indonesia 37
Top 5 most/least corrupt countries
Corruption Perception Index 2016
Rank Country Score Rank Country Score
1 Denmark 90 1 Denmark 91
New Zealand 90 New Zealand 91
2 Finland 89 2 Finland 90
3 Sweden 88 3 Sweden 89
4 Switzerland 86 4 Norway 88
5 Norway 85 5 Switzerland 86
88 Indonesia 36
174 North Korea 12 174 North Korea 8
175 South Sudan 11 175 South Sudan 15
176 Somalia 10 176 Somalia 8
Corruption Perception Index 2015
Executive SummaryExecutive SummaryExecutive SummaryAgenda
Note: 1 is perceived to be least corrupt, 176 is perceived to be most corrupt
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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24%
24%
72%
22%
24%
23%
27%
29%
69%
Cybercrime
Bribery and Corruption
Procurement fraud
Asset Misappropriation
2014
2011
Jakarta Business Networkers 0% 20% 40% 60% 80%
Fraud and Corruption in Indonesia
PwC
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Bribery and
Corruption is identified as
one of the five most prevalent
forms of fraud, after Asset
Misappropriat
ion
PwC’s Global Economic Crime Survey indicates only slight changes year on year
Accounting fraud
Source: PwC GECS
Sector % of respondents reporting
Financial services 19%
Professional services 18%
Entertainment and media 14%
Sector % of respondents reporting
Engineering and construction 50%
Energy, utilities, and mining 42%
Government/state-owned enterprises 35%
Sectors reporting the least bribery and corruption:
Source: PwC GECS
Executive SummaryExecutive Summary2 Fraud triangle Agenda Executive Summary
Industries most at risk of bribery and corruption
Sectors reporting the most bribery and corruption:
Jakarta Business Networkers
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Anti-corruption efforts and their effectiveness / KPK-'statistics'
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Anti-corruption efforts and their effectiveness / KPK-'statistics‘
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Fraud and Corruption in Indonesia
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Anti-corruption efforts and their effectiveness / KPK-'statistics‘ (continued)
Total Cases in 2012: 49
Total Cases in 2016: 99
Source : http://nasional.kompas.com/read/2013/12/30/2149106/2013.KPK.Tangani.70.Kasus
Total Money Saved :
IDR 500 Billion
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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Anti-corruption efforts and their effectiveness / KPK-'statistics‘ (continued)
Source : KPK
Jakarta Business Networkers
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Positions of convicted:
• Judges
• Prosecutors
• Parliamentary Members
• Ministers
• Government Officials
• Ambassadors
• Commissioners
Bribery and corruption in high risk markets
10%
14%
26%
29%
40%
Lost opportunity to
competitor believe paid
bribe
Asked to pay bribe
0% 10% 20% 30%
Org with operations in high risk markets
Org with no operations in high risk markets
Respondents
with operations
in high risk
markets are twice
as likely to be
asked to pay a
bribe and believe
they lost an
opportunity to a
competitor bribe
3 Anti-corruption efforts and their effectiveness / KPK-
'statistics'
Source: PwC GECS
Jakarta Business Networkers
Executive SummaryExecutive SummaryExecutive SummaryAgenda
Fraud and Corruption in Indonesia
PwC
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22 22
Real life fraud cases
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A Business in a business
Customer Company Company Company Customer
Own transport
Fraudulent companyCustomer
Customer
√
√
X
Pick up goods from customer Bring goods to port Pick up goods from port Deliver goods to customer Result
Jakarta Business Networkers
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PwC
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Middleman
• During our image analysis and document vouching, we noted the following pattern from a number of transactions to end customers:
o A number of quotations from Company ABC to end customers
o A number of quotations from Fraud company to end customers
o POs received from Fraud company with lower product prices compared to identified quotations
o Sales to Fraud company with product deliveries directly to end customers
• The chart below summarises the above findings
Jakarta Business Networkers
Fraud and Corruption in Indonesia
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Cyber fraud
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There are many fraud schemes when it comes to procurement…..
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Below we have listed some of the fraud schemes we have come across during our engagements:
1. Supplier = Company X employee
2. All suppliers are owned by same person so tender is not "real“
3. Split POs to stay under approval threshold for Direct award when should have gone out for tender
4. Kick backs to Company X employees/procurement staff to get contracts
5. Overpayment for goods of lower quality
6. Company X pays for services that were never provided
7. Supplier is middleman and is owned by employee or his family member and provides goods to Company X with a mark up
8. Inappropriate and ineffective internal controls
1. Supplier = Company X employee
Issue
• The supplier is actually an employee of Company X,
but has not declared its business interest in the
supplying entity
• Undeclared conflict of interest
Approach
• Identify common addresses, bank accounts and phone
numbers through Suspicious Transaction Analysis,
Corporate Intelligence and forensic investigation
• Conduct Due Diligence before accepting/during
relationship with vendor
• Pre and post employment screening of employees
Outcome
• Identify undeclared conflicts of interest
Company X
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
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2. All suppliers are owned by same person so tender is not "real“
Issue
• Company X invites 3 companies to provide a proposal, but they are actually owned by the same person
Approach
• Identify common shareholders, directors, etc, common addresses,and phone numbers through Suspicious Transaction Analysis andforensic investigation
Outcome
• Establish whether entities are related
Proposal Proposal Proposal
Company X
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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3. Split POs to stay under approval threshold for Direct award when should have gone out for tender
Issue
• Company X procurement people arrange with
supplier to split POs into smaller POs to stay
under the threshold so that they can “direct
award” a contract and not have to go out for
tender
Approach
• Identify common shareholders, directors, etc,
common addresses, and phone numbers through
Suspicious Transaction Analysis and forensic
investigation
• Review G/L for unusual transactions, volume
and amounts
Outcome
• Identify POs that are connected and relate to the
same contract
Note: Approval threshold for direct appoint is US$ 750k
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
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4. Kick backs to Company X employees/procurement staff to get contracts
Issue
• Company X employees/procurement staff ask
vendors for kick backs before/in order for them
to get awarded contracts by vendor
Approach
• Identify correspondence (e.g. e-mail, SMS,
WhatsApp messages) between Company X staff
and vendors (use Forensic Technology Services)
• Pre and post employment screening of
employees
• Conduct data analytics between customers/staff
to identify inconsistencies in procurement
Outcome
• Identify employees who are requesting kick
backs from vendors
VendorProcurement staff/
employeeKick back
Contract
Company X
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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5. Overpayment for goods of lower quality
Issue
• Suppliers deliver lower quality goods, but charge
for higher quality goods and share the difference
in price with Company X staff
Approach
• Identify correspondence (e.g. e-mail, SMS,
WhatsApp messages) between Company X staff
and vendors (use Forensic Technology Services)
• Conduct price comparison/data analytics
Outcome
• Identify employees who are in collusion with
vendors
• Identify potential quality issues
Good worth US$100,
but invoiced US$ 150
50Company X pays US$ 1
to vendor
Vendor pays US$ 25
to employee
Company X
Company X
employee
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
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6. Company X pays for services that were never provided
Issue
• Supplier charges Company X for services that were
never provided and share the proceeds with Company
X staff
Approach
• Identify correspondence (e.g. e-mail, SMS, WhatsApp
messages) between Company X staff and vendors (use
Forensic Technology Services)
• Conduct walk through of procurement cycle to identify
weaknesses in internal controls and “points of leakage”
• Check sample of “services” transactions
Outcome
• Identify employees who are in collusion with vendors
• Identify “fake” transactions
Invoice for S$ 150
for services
Company X pays US$ 150
to vendor
Vendor pays US$ 25
to employee
Employee acknowledges
receipt of services
Company X
Company X
employee
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
PwC
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7. Supplier is middleman and is owned by employee or his family member and provides goods to Company X with a mark up
Issue
• Entity owned by Company X staff acts as
middleman and on-sells goods to Company X
with a mark-up
Approach
• Identify common addresses, bank accounts and
phone numbers through Suspicious Transaction
Analysis/data analytics and forensic
investigation
• Conduct Due Diligence before accepting new
vendors/during relationship
• Pre and post employment screening of
employees
• Conduct price survey
Outcome
• Identify undeclared conflicts of interest
Profit sharing
Marked up goodsGoods
Company X
Company X
employee
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
Fraud and Corruption in Indonesia
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9. Inappropriate and ineffective internal controls
Issue
• Employee had a conflict of interest, he/she did
not declare as claimed was not aware that he
should declare
Approach
• Conduct fraud risk Diagnostic (Company self
assessment initially) and Fraud “Risk Storm”
Workshops to “challenge” the initial assessment
• Update fraud risk assessment
• Review fraud risk policies and procedures
• Conduct fraud awareness training
Outcome
• Identify weaknesses in internal controls
Examples:
• No Code of Conduct
• No “conflict of interest” policy
• No whistleblower facility
• No proper segregation of duties
• No independence / declaration policy
• No SOPs
4 Real life fraud cases Executive SummaryExecutiveASguemndmaaryExecutive Summary
Jakarta Business Networkers
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Suspicious Transaction Analysis
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What is “Suspicious Transaction Analysis”?
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Suspicious Transaction Analysis (STA) is an automated fraud detection and data analysis process which can search through millions of transactions and master file data to identify those that require further investigation. STA complements an organisation’s existing schedule of audit and control tests, making best use of valuable resources. It is a tool which quickly identifies problem areas, particularly in those high risk functions such as payroll, accounts payable and expense claims.
STA utilises sophisticated software programs to data match and interrogate an organisation’s supplier and employee databases to quickly identify, for example:
• Duplicate payments (made either fraudulently or in error)
• Collusion between suppliers and employees
• Suppliers fitting known fraud profiles
• Unusual, anomalous or otherwise questionable transactions.
A proactive approach to fraud detection
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Benefits of Suspicious Transaction Analysis
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Benefits of Suspicious Transaction Analysis
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Some Case studies
Case Study One: Duplicate payments to suppliers
Our role: To undertake an STA over accounts payable and payroll for a large
organisation. There were no prior suspicions of fraud orerror.
Outcome: In addition to data quality issues, we identified a large number of duplicate
payments to suppliers amounting to over $1,700,000 which was recoverable from
suppliers.
Case Study Two: Overpaid Overtime
Our role: We were asked by a government agency to use STA to analyse staff salaries
and overtime payments over a three year period.
Outcome: We identified nine employees who were paid overtime rates in excess of$1,000 per hour, the highest being $4,989 per hour. These results allowed the agency
to investigate the payments and recover theover-payments.
Case Study Three: Duplicate payment of invoices and cleaning of supplier master
files
Our Role: We undertook an STA of master supplier and purchasing transaction files
for a large organisation. We identified approximately $600,000 of duplicate invoice
payments over a two year period. The STA also revealed that a number of suppliers
had been entered in the master file more thanonce.
Outcome: The organisation cleaned the master file of duplicated suppliers, thereby
reducing the risk of inadvertent duplicate payments and commenced to recover the
overpayments.
Case Study Four: Vehicle over-servicing
Our Role: Unsatisfied with the operating costs of its vehicle fleet, particularly relating
to vehicle maintenance, this organisation approached us to undertake an STA
specifically over vehicle maintenance payments.
Outcome: We analysed all electronic maintenance data for the entire vehicle fleet over
a three year period. Several anomalies were detected, including apparent over-
servicing of vehicles and vehicles serviced with either no labour costs or no parts costs.
Our client was able to revisit the service provider agreements with the intention of
terminating the relationship with the vehicle maintenance provider.
There are literally thousands of possible STA tests that can be run. The decision as to
which tests to run depends on a number of factors such as type of business, quality of
data, the number of records, internal control weaknesses, past fraud incidents and so
on.
Some of the more useful routine Accounts Payable and Payroll tests we run are listed
below. However, it should be noted that we can also tailor these tests or design
additional tests which will address your specific needs andconcerns.
5 Suspicious Transaction Analysis Executive SummaryExecutive SummaryExecutive SummaryAgenda
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Some examples of STA tests for Procurement
1.
2.
3.
4.
5.
6.
•
•
Collusion between employees and suppliers: Identify details shared between
employees and suppliers (either address, telephone or bank details). Identify
whether payroll and accounts payable transactions exist.
NB: In the event employee related suppliers reside on the Supplier Master File
for the purposes of the reimbursement of work related expenses, these will be
eliminated from the test results where the supplier name is the same as the
employee name.
Identify suppliers sharing address, telephone, with the PwC profile database
(prisons, document exchanges, serviced offices, postal services and adult
entertainment). Identify payments to these suppliers.
NB: In the event employee related suppliers reside on the Supplier Master File
for the purposes of the reimbursement of work related expenses, these will be
eliminated from the test results where the supplier name is the same as the
employee name.
Payments to suppliers which do not appear on the Supplier Master File (by
supplier number or bank details).
NB: In the event the Supplier Master File is maintained real time such that
only the latest bank details are captured, a historical listing of bank accounts
is required to eliminate false positives from theresults.
Duplicate supplier payment transactions to the same supplier based on:
Identical invoice amount and identical or similar invoice number
Identical invoice amount and description.
8. Duplicate supplier payment transactions based on identical invoice number
and amount to different supplier numbers.
9. One off payments to suppliers.
10. Invoices dated (i.e. suppliers invoices date) onweekends.
11. Active suppliers sharing information (address, telephone, bank details) with
one or more other suppliers within the same branch (i.e. different supplier
numbers within the same branch). Identify whether duplicate supplier
payments have occurred to these suppliers per Test No. 8.
12. Identify favourable payment of invoices (i.e. invoices paid within 10 days of
the suppliers invoice date).
13. Compare suppliers invoice date to the purchase order creation date to identify
purchase orders created on the same date or subsequent to the suppliers
invoice date.
14. Identify multiple invoices from the same supplier on the same date.
15. Identify active suppliers in the Supplier Master File which have no accounts
payable transactions (i.e. active on the Supplier Master File but they are not
really active because they have no transactions). Such suppliers should be
disabled on the Supplier MasterFile.
16. Split purchasing by employees: Identify multiple purchase orders created on
the same day or within three days of each other to the same supplier and
authoriser where the total value exceeds the acceptable tolerable level for the
authoriser.
5 Suspicious Transaction Analysis Executive SummaryExecutive SummaryExecutive SummaryAgenda
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Some examples of STA tests for Procurement (Cont’d)
18. Identify invoices paid before the suppliers invoice date.
19. Identify accounts payable transactions processed by employees while they are
on annual leave or sick leave.
20. Benford analysis on invoice amount.
21. Identify large invoices without purchase orders or which have not been
receipted.
22. Excessive purchasing from suppliers.
23. Identify duplicate cheques issued to different suppliers.
24. Identify quantity mismatches between the quantity ordered and the quantity
receipted.
25. Compare purchase order amount to the amount invoiced.
26. Analyse round invoice amounts from suppliers.
5 Suspicious Transaction Analysis Executive SummaryExecutive SummaryExecutive SummaryAgenda
Jakarta Business Networkers
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Some examples of STA tests for Payroll
1. Compare payroll dates with employee start and termination dates to identify
payments to employees:
• Prior to hire date
• More than 60 days after termination date.
2. Identify employees sharing address and/or telephone with the PwC Australian
profile database (prisons, document exchanges, serviced offices, postal services
and adult entertainment). Identify payroll transactions to these employees.
3. Employees sharing information (either bank details, DOB and same name, name
and address, or name and phone number) with one or more other employees (i.e.
different employee numbers). Identify payroll transactions to theseemployees.
4. Employees receiving excessive overtime as a proportion of gross pay (40% or
more of gross pay is overtime).
5. Employees receiving excessive allowances as a proportion of gross pay (40% or
more of gross pay is allowances).
6. Payroll payments with no tax deducted.
7. Payments to employees which do not appear in the Employee Master File (by
employee number and bank details information).
NB: In the event the Employee Master File is maintained real time such that only
the latest bank details are captured, a historical listing of bank accounts is
required to eliminate false positives from theresults.
8. Identify round payroll payments to employees.
9. Identify payments to employees with unusual dates of birth:
• Aged 17 years or less
• Aged 65 and over.
10. Identify duplicate payroll payments based on employee number and pay run
number.
11. Identify payments to employees where the bank account name differs to the
employees’ name.
12.Payroll transactions dated on weekend dates.
13.Identify payments made to employees employed for 10 days or less.
14.Excessive number of payments per period.
15. Identify employees with high amounts of gross pay (e.g. over $80,000).
16. Identify incorrect payroll payments by comparing the gross amount in the
Employee Master File to the actual amount paid to theemployee.
17. Identify annual leave and long service leave taken prior to approval.
18. Employees sharing information (either bank details, address or telephone) but
not name with different employees. Identify payroll payments to these
employees.
19. Identify payroll payments to employees where the bank account name differs
from the employee’s name.
5 Suspicious Transaction Analysis Executive SummaryExecutive SummaryExecutive SummaryAgenda
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What can you do?
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There are many ways to avoid or mitigate fraud
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Action Comment
Code of Conduct Tone at the top is key!
Back ground due diligence Know who you’re dealing with
Segregation of duties Don’t give people the opportunity to commit fraud
Delegation of Authority The CFO does not need to approve everything
Data Analytics/Suspicious Transaction Analysis
To be performed periodically
Fraud Risk Analysis Know where your risks lie, and make sure you mitigate exposures
Whistle blower hotline Follow up on reports
Forensic investigation Follow up on indications of fraud
PwC Forensics Service Offerings
Without an effective fraud risk
management strategy, a company
is exposed to fraud for which the
Board and management may be
legally and financially liable for
failure to establish a pro-active
fraud risk framework.
PwC’s Forensic Services practice
specialises in establishing fraud
risk and control frameworks
which help to identify relevant
fraud risks and the associated
controls.
We assist clients to understand
and meet their obligations in
fraud control in accordance with
both private and public sector
Standards such as AS 8001-2008
Fraud and Corruption Control,
various Fraud Control Guidelines
and other requirements. We
divide our fraud risk frameworks
into three headings: Prevent,
Detect and Investigate.
• Fraud risk policies and procedures• Fraud control plans• Annual declarations• Pre and post employment screening of employees• Fraud awareness training• “Whistle blower” hotline procedures
• Investigative Intelligence & Analysis • Procurement Fraud ManagementJakarta Business Networkers
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• Fraud risk assessments• Facilitated workshops
to identify fraud risk
• Proactive internal and
external audit
procedures
• Data analytics
(“suspicious
transactions analysis”)
• Fraud investigations• Forensic Accounting• Electronic Discovery Services
• Anti-Money Laundering (AML) & Sanctions• Anti-Bribery & Corruption• Licensing Management Services