Transactional Analysis for Effective Fraud Detection

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Transactional Analysis for Effective Fraud
Detection

• Doug Burton
• ACL Services Ltd.

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(No Transcript)
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Todays Objectives

• The magnitude of fraud
• Fraud detection and internal controls
• The role of technology
• Continuous monitoring for fraud

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Occupational Fraud and Abuse

• The use of ones occupation for personal
  enrichment through the deliberate misuse or
  misapplication of the employing organizations
  resources or assets
• Deception brought about by the willful
  misrepresentation of significant material facts,
  or silence when good faith requires expression,
  resulting in material damage to one who relies on
  those facts and has a reasonable right to do so
• An intentional act which is concealed, resulting
  in a personal benefit to the perpetrator and
  resulting in harm to the organization

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What is Your Cost of Fraud?

• U.S. organizations lose about 4,500 per employee
  annually as a result of occupational fraud and
  abuse
• How many employees do you have?

Association of Certified Fraud Examiners, 2002
Report to the Nation on Occupational Fraud and
Abuse
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What is Your Cost of Fraud?

• U.S. organizations, on average, lose 6 of
  revenues to fraud.
• This represents a potential loss of 600 billion
  to fraud annually within the U.S.
• What is your annual gross revenue ?

Association of Certified Fraud Examiners, 2002
Report to the Nation on Occupational Fraud and
Abuse
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What is Your Cost of Fraud?

• In addition to the direct cost of fraud, there
  are significant indirect costs
• Loss of consumer confidence reduced revenues
• Negative PR image lower stock values
• Low employee morale lower productivity
• Inability to retain and attract qualified staff

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Examples Occupational Fraud and Abuse

• Embezzlement/asset misappropriations
• Bribery
• Bid-rigging
• Conflict of interest
• Fraudulent statements

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Other Statistics

• Most commonly detected through tips
• Next most common is by accident
• Only 7 of fraudsters had prior fraud-related
  convictions
• Know your F.A.C.T.S.(Fraud is Always Committed
  by Trusted Souls)
• Average fraud scheme lasts 18 monthsbefore
  detection
• More stats www.cfenet.com/media/statistics.asp

Kate Head University of South Florida
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Fraud Detection and Internal Controls

• These (improper) payments occur for many reasons
  including insufficient oversight or monitoring,
  inadequate eligibility controls, and automated
  system deficiencies. However, one point is clear
  the basic or root cause of improper payments
  can typically be traced to a lack of or breakdown
  in internal controls.
• GAO report on Coordinated Approach Needed to
  Address the Governments Improper Payments
  Problems August 2002

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Sarbanes-Oxley Requirements

• Section 302 - Management certification to
  integrity of Internal Controls must address 4 key
  points
• Statement of managements responsibility for
  establishing and maintaining adequate internal
  controls
• Managements assessment of the effectiveness of
  internal controls to include all fraud involving
  management and employees with significant roles
  in internal control
• A statement identifying the framework used by
  management as a criteria for evaluating control
  effectiveness
• A statement that the independent accountant has
  also issued an attested to managements
  assessment of internal control.

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Commonly Detected Frauds

• Accounts payable
• Phantom vendors
• Purchasing
• Purchase splitting
• Kickbacks
• Purchase cards
• Inappropriate, unauthorized purchases
• Telecom
• Inappropriate use of telephone system

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Data Analysis in Fraud Detection
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Data Analysis in Fraud Detection

• Los Angeles Unified School District - Belmont
  Learning Center
• ACL use resulted in the identification of fraud
  and abuse in excess of 70 million
• Fictitious vendors
• Duplicate payments
• Over-billing
• No competitive bidding
• Policy violations
• Exceeding purchasing limits
• Improper coding

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The Traditional Role of the Auditor in Detecting
Fraud

• Typically a reactive role tips
• Based on examining selected samples of
  transactions
• Testing of existing controls
• ACFE survey says 90 of managers place their
  confidence in internal controls
• Limited use of technology

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The Traditional Role of the Auditor in Detecting
Fraud

• Typically a reactive role

The longer frauds go undetected, the larger the
potential for loss and the smaller the chances of
recovery
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The Traditional Role of the Auditor in Detecting
Fraud

• Based on examining samples of transactions

10,000 Employees
X 26 Pay Periods
260,000 paychecks/transactions
1 check .0004
10 checks .004
100 checks .04
1,000 checks .4
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The Traditional Role of the Auditor in Detecting
Fraud

• Testing of existing controls

46 of frauds occurred because of insufficient
controls An additional 40 of frauds exploited
situations where controls were ignored
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The Traditional Role of the Auditor in Detecting
Fraud

• Limited use of technology

Both the AICPA and the ACFE specifically refer to
the use of data analysis to assist in fraud
detection
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The Role of Technology in Fraud Detection and
Investigation

• Perform risk analysis
• Look for indicators of fraud
• Review 100 of transactions
• Compare data within different databases and
  computer systems
• Determine impact of fraud
• Proactive tests
• Continuous monitoring

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Discovering Fraud Electronically Three
Approaches

• Drill-down Analysis
• Review large population and determine true areas
  of risk
• Isolate red flags and drill down
• Attribute Sampling
• Begin with entire population and filter for
  transaction matching specific criteria
• File Matching
• Compare separate data files and look for
  disparities or matches (e.g. phantom vendors)

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The Role of Technology in Fraud Detection and
Investigation

• Data analysis will provide
• Indication of where to look
• Indication of the depth and scope of the problem
• Direct pointers to critical evidence
• Proof
• Findings

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Examples of Fraud Tests

• Questionable Purchases
• P.O. with blank / zero amount
• P.O. / invoices with amount paid gt amount
  received
• Questionable purchases of consumer items

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Examples of Fraud Tests

• Questionable Invoices
• Invoices without a valid P.O.
• Invoices from vendors not in vendor file
• Invoices for more than P.O. authorization
• Multiple invoices for same item description
• Vendors with duplicate invoice numbers
• High/inconsistent prices

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Examples of Fraud Tests

• Questionable Invoices
• Invoices for same amount on the same date
• Multiple invoices for same P.O. and date
• Sequential invoices
• Invoices with no matching receiving report
• New or non-approved vendors

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Examples of Fraud Tests

• Phantom and other vendor tests
• Vendor/employee name match
• Employee and vendor with same address orphone
  number
• Vendor address is a mail drop
• High number of returns by vendor
• Payment without invoice
• Missing inventory
• Duplicate documents

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Assessing Risk
Measure Impact Based on Expected Occurrences
HIGH
HIGH
MODERATE
Probability of Occurrence
MODERATE
LOW
MODERATE
LOW
HIGH
Financial Impact
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Challenges to Effective Fraud Detection

• Data sampling
• Disparate data sources complex IT systems
• Ad hoc analysis

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Issues With Sampling

• Sampling is only effective with problemsthat are
  relatively consistent throughout a data
  population
• Fraudulent transactions by nature do not occur
  randomly
• Fraudulent transactions often fall within
  bounds for standard testing and therefore do not
  get flagged

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Examine Abnormalities
Random Sample
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Establish Appropriate Parameters
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Benfords Law Testing

• What is it?
• Benfords Law tells us that numbers occur with
  predictable frequency within a natural
  population
• The digits 1 9 appear with declining frequency
• 1 30
• 9 4.6
• This natural rule, applied to a numeric
  population, can point to numbers appearing more
  frequently than normal, thus being suspect

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Benfords Law - Example

• Audit review of physician billings
• Benfords Law testing identified a spike in the
  number 3
• Of these records, 22 percent were submitted by
  one doctor
• Subsequent analysis revealed impossibly high
  daily billings

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Compare Information from Disparate Data Sources
Access data from two or more separate sources
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Compare Information from Disparate Data Sources
Access data from two or more separate sources
Convert/harmonize data into comparable structures
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Compare Information from Disparate Data Sources
Access data from two or more separate sources
Convert/Harmonize data into comparable structures
Combine data into single or related file for
analysis
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Compare Information from Disparate Data Sources
Access data from two or more separate sources
Convert/Harmonize data into comparable structures
Combine data into single or related file for
analysis
Exceptions
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Fraud Detection throughContinuous Monitoring

• Data analysis is used in fraud detection
  investigation to identify document fraudulent
  activities
• Part of overall fraud detection plan
• Investigate and document issues identified
• Continuous monitoring analyzes three key areas
• Identifies anomalies within data
  files/transactions
• Examines 100 of the data (not sampling)
• Timely identification (not suspicious
  transactions)
• Runs automatically (user-defined frequency)
  reports anomalies to designated individuals for
  investigation

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Continuous Monitoring Process

• Other Sources
• Master Files
• Related Data
• Other References

Primary Transaction Data
Data Output
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Data Analysis in Fraud Detection

• A US government agency with 6.5 billion in
  annual procurement card purchases used data
  analysis to monitor expenditures
• Indicators of inappropriate transactions were
  established and compared to actual data
• Data from disparate sources were integrated
  including employee listings, authorizations,
  merchant restrictions, credit limits
• 38 Million in suspect transactions were
  identified
• A timely and cost-effective reporting system was
  created to follow-up with vendors and banks in
  the subsequent recovery process

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Data Analysis in Fraud Detection

• A large healthcare insurer was defrauded of more
  than 25 million in claims
• A routine claims audit identified an abnormal
  number of transactions of a certain value
  (through data analysis)
• By implementing a continuous monitoring
  application, the organization may have identified
  the anomalies earlier in the process
• Fraud exposure would have been reduced
• Process improvements would have been identified

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Benefits of Continuous Monitoring

• Confirms/validates effectiveness of controls
• Mitigates deficient control structures
• Monitors data from disparate systems to provide
  holistic view of transactions
• Provides independent assurance
• Identifies further process improvement
  opportunities
• Identifies suspicious transactions in a timely
  manner
• Reduces waste, enhances recoveries

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Status of Continuous Monitoring

• Fastest growing area within audit and control
  community
• Increasingly more common in organizations
• Organizational challenges for widespread
  implementation
• Technological barriers difficulties of access to
  data
• Assumption that effective application controls
  are in place
• Perception that sampling is an effective control
  assessment methodology
• Lack of detailed understanding of exactly what
  and how to test
• Recommendation seek expert advice

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Implementation of a Fraud Detection Program

1. Build a profile of potential frauds which can
   then be tested
2. Analyze data to identify possible indicators of
   fraud
3. Implement continuous monitoring of high-risk
   business functions to automate the detection
   process
4. Investigate and drill down into patterns which
   emerge via data analysis/detection process

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Thank you!
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For More Information

• Doug Burton
• ACL Services Ltd.
• Doug_burton_at_acl.com
• 604-646-4201