using indicators and internal loss data to forecast fraud · embezzled aud 45,000,000 between 2004...

Using Indicators and Internal Loss

Data to Forecast Fraud

2012 ACFE European Fraud Conference

© 2003-2012 RiskBusiness International Limited

Getting Started — Common Language

• Definition of fraud

Fraud essentially involves an act or acts of deception

to dishonestly make a personal gain for oneself and/or

create a loss for another, either in cash or kind or by

avoiding an obligation

• Fraudster

Intends to deceive

Has an objective to influence actions and decisions


Getting Started — Common Language

• Definition of operational risk

The risk of loss resulting from inadequate or failed

internal processes, people and systems or from

external events. The definition includes legal risk but

excludes strategic and reputational risk.

• Recognises two forms of loss event types

Internal fraud

External fraud


Common Language

• Taxonomy is the practice and science of

classification.

The word finds its roots in the Greek τάξις, taxis

(meaning “order,” “arrangement”) and νόμος, nomos

(meaning “law” or “science”).

Taxonomy uses taxonomic units, known as taxa

(singular taxon).


Common Language

• In addition, the word is also used as a count noun: a taxonomy, or taxonomic scheme, is a particular classification (“the taxonomy of ...”), arranged in a hierarchical structure. Typically this is organised by subtype-supertype

relationships, also called parent-child relationships.

In such a subtype-supertype relationship the subtype kind of thing has by definition the same constraints as the supertype kind of thing plus one or more additional constraints.

For example, car is a subtype of vehicle. So any car is also a vehicle, but not every vehicle is a car. Therefore, a thing needs to satisfy more constraints to be a car than to be a vehicle.


The Difficulty with Classification


Risk category classifications

• Internal fraud

Unauthorised activity

Internal fraud and theft

Fraudulent activity

Theft

• External fraud

Hacking and system intrusion

External fraud and theft

Fraudulent activity

Theft and robbery


Understanding Loss Event Data


Detective Controls

Internal causes

External causes Oversight Controls

EVENT

Preventive Controls

Defined Business Process

Market and Sell

Products and

Services

Trading and/or

Investment

Management

Trade Settlement

Processes

Glob Serv Inv Mgmt Sec Lend

Org’l Hierarchy

Card - Retail FX Swap Lockbox

Products

Expected Result

Defined Business Process

Risk Category

Mining Loss Event Data


• Lehman Brothers and Marubeni:

March 2008, Lehman Brothers filed lawsuit against

Marubeni Corporation in Tokyo District Court.

Lawsuit sought recovery of ¥35 billion/$351 million lent

by Lehman’s to Asclepius/ LTT Bio-Pharma but

misappropriated by two Marubeni employees.

Lehman claims it thought the funds it committed were

backed by Marubeni, based on documents on a

Marubeni letterhead, which the investment bank later

found was forged.

Lehman staff undertook all required and reasonable

counter-fraud measures, post disbursement controls

failed.

Case Study — External Fraud


• ING: Australia’s second largest fraud

40-year-old Rajina Subramaniam worked for ING in

Sydney for 20 years as an accountant.

Embezzled AUD 45,000,000 between 2004 and 2010

by transferring suspense account balances and

unclaimed client money to personal accounts.

Became known throughout Sydney for her lunch-hour

shopping spree’s. In 2009 alone:

Chanel (AUD 98,452)

Bulgari (AUD 3,300,000)

Paspaley – a jewellers (AUD 7,600,000, over and above AUD

16,000,000 in previous years)

Also bought seven properties in her maiden name.

Currently on trial for embezzlement.

Case Study — Internal Fraud


Culture, Human Behaviour, and ….KYP


National Culture...


Forecasting Fraud — Causal Chains

Manager

S’visor A S’visor B

Clerk A Clerk A Clerk A Clerk B Clerk B Clerk B

Trade

Record

Review

and check

details

Correct? Send to

Confirm

Return

to F/O

Yes

No

Annual

holidays

Market

volatility

Complex

trade

Lack of

training

Staff €

problems

Staff

personal

problems

M’ment

offsite

Short

staffed

System

failure


Forecasting Fraud — Using Indicators

• Avoid “backward-looking” indicators

• Use causal drivers as basis for identifying good

indicators

• Where possible, create composite or index-

based indicators

• Monitor delta from a base starting point

• Set thresholds and alert triggers

• Link in root cause assessments from loss data


Questions and Comments

• Contact Details:

• Mike Finlay, Chief Executive, RiskBusiness

Telephone : +44 7721 969 224

E-mail : [email protected]

URL : www.riskbusiness.com and www.KRIeX.org

• Further Information:

• See “Fraud rising to the top”, The Risk Universe

Issue 2, February 2012, www.riskuniverse.com

mailto:[email protected]

http://www.riskbusiness.com/

http://www.kriex.org/

http://www.riskuniverse.com/

“Association of Certified Fraud Examiners,”

“Certified Fraud Examiner,” “CFE,” “ACFE,”

and the ACFE Logo are trademarks owned by

the Association of Certified Fraud Examiners,

Inc. The contents of this paper may not be

transmitted, re-published, modified,

reproduced, distributed, copied, or sold without

the prior consent of the author.

using indicators and internal loss data to forecast fraud · embezzled aud 45,000,000 between 2004...

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