Cognitive computing for automated internal fraud detection

June 2020

Internal fraud – the biggest competitor you didn’t know you had

1 in 2organizations

fall victim to fraud every year

52%of fraud cases

are insider fraud

32%of fraud cases committed by

business partners

2

*PWC 2018 Report: Pulling Fraud Out Of The Shadows. Global Economic Crime And Fraud Survey.

30

25

20

15

10

5

0

IT controls

Surveillancemonitoring

Account reconciliation

Internal audit

Managementreview

Documentexamination

Tip Externalaudit

By accident

Confession Notified bypolice

Med

ian

mon

ths t

o de

tect

ion

5months

6months

11 months

12months

14months

18months

18months

23months

24months

24months

24months

3

IT controls are the most efficient way to detect internal fraud*ACFE 2020 report to the nations: Global study on occupational fraud and abuse (Pg. 19)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

TipInternalaudit

Managementreview

Byaccident

Accountreconciliation

Documentexamination

Externalaudit

Surveillancemonitoring

Notified by lawenforcement

IT controlsConfession

4

Yet they are hardly used*ACFE 2020 report to the nations: Global study on occupational fraud and abuse (Pg. 20)

5

Existing technologies are inadequate for purposeDeep learning or rules-based engines analyzing the single transaction are limited in their ability to distinguish a fraud from legitimate business transaction

Truly automating fraud detection requires a new approachMoving from examination of anomalies

to detecting actual fraud by understanding the context in which transactions take place

WHY IS THIS?

An automated and customizable platform that utilizes cognitive computing technology to continuously monitor organizational IT systems and detect business transactions/events that correspond to high risk fraud patterns.

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COGNITIVE COMPUTING FOR INTERNAL FRAUD DETECTION

The advantages of cognitive computing

Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain.

Valire applies these cognitive principles to the identification of high-risk, potentially improper or fraudulent financial transactions.

01.

02.

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How Valire’s fraud detection works

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IT system

Track transactionsIn real-time

Put transactionin context

Analyze

Map tablesModel business

processes

!Alert!

Fraud scenariodata set

Fraud schemes vary widely, but they all reflect human concepts

Internal fraud requires a business process circumvention, created by a fraudster

Fraud schemes are often disguised as legitimate, normal transactions

Anticipate what a fraudster could do

Identify events that corresponds to fraud risk scenarios

Provide actionable alerts on suspicious transactions and entities

How cognitive fraud detection works

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Understand the context and the relationship of each single transaction

Guide the machine to learn the business processes

Embed human logic & anti-fraud expertise into pre-configured algorithms

Fraud scenarios vary widely, but they all reflect human concepts

Embed human logic & anti-fraud expertise into pre-configured algorithms

Anticipate what a fraudster could do

Internal fraud requires a business process circumvention, committed by a fraudster

Guide the machine to learn the business processes

Identify events that corresponds to fraud risk scenarios

Fraud scenarios are often disguised as legitimate, normal transactions

Understand the context and the relationship of each single transaction

Provide actionable alerts on suspicious transactions and entities

Fraud Attributes Cognitive InsightCognitive Computing

Fraud scheme examples

Collusion in procurement cycle

Shell or high-risk companies

Bribery and corruption, kickback schemes

Conflicts of interest

Segregation of duty schemes, e.g., requestor / approver conflicts

Vendor's overbilling

Ghost employees

10

Vendor created inmaster data

01.

Vendor’sInvoicerecorded

02.

Vendor’sInvoiceapproved

03.

Payment

04.

B

ACTIVE VENDOR USER B

How does context detection look?

LEGITIMATEPROCESSA

USER A

How does fraud detection look in context?

Vendor’sInvoiceapproved

How does fraud detection look in context?

Vendor’sInvoiceapproved

Trigger activating

Valire’sdetector

Vendor filecreated inmaster data

01.

Vendor’sInvoicerecorded

02.Change of Vendor’sbank account details

03.

Payment

05.

B

USER B

How does fraud detection look in context?

Vendor’sInvoiceapproved

04.

VENDOR

A

USER A

Track invoice history

Vendor filecreated inmaster data

01.

Vendor’sInvoicerecorded

02.Change of Vendor’sbank account details

05.

B

DORMANT VENDOR USER B

How does fraud detection look in context?

Vendor’sInvoiceapproved

04.03.

A

USER A

Reveal context &

connections

Payment

Vendor filecreated inmaster data

01.

Vendor’sInvoicerecorded

02.Change of Vendor’sbank account details

05.

B

DORMANT VENDOR USER B

How does fraud detection look in context?

Vendor’sInvoiceapproved

04.03.

A

USER A

POSSIBLEFRAUD!

• Dormant vendor• Change of vendor

bank account • Same user change

bank & approved invoice

• No purchase order

Payment

VALIRE’S OPERATIONAL FEATURES

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Data analysis portal Vulnerability test

Single casedrill down

Fine tune parameters as you go

Access to source documentation

Real timealerts

Adjustable risk scoring

Case management

Data analysisportal

Risk level monitoring

Real timealerts

Data analysisportal Vulnerability test

Single casedrill down

Adjustable risk scoring

Case management

Access to source documentation

Fine tune parameters as you go

Risk level monitoring

Valire’s Edge

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Avoid false positive alarms by fine tuning the system to your unique

business processes

Leave no corner unchecked by monitoring 100% of transactions,

business events, data entries and entities

Reveal complex fraud scenarios by examining the entire process and the

context in which transactions are performed

Dramatically enhance auditing and monitoring capacity

thanks to hands free operation

Minimize corporate risk and financial losses

with continuous surveillance and real-time, specific, actionable alerts

Maximize corporate compliance through active

fraud risk monitoring

The entire data remains within the

enterprise IT system

Short deployment and configuration

Proof of Concept on historical data including

a vulnerability test

Off-the-shelfpre-configured library

of fraud scenarios

Tailored solutions to client’s unique needs

SaaS model with ongoing upgrades

VALIRE’S OFFERING

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Where do you see your primary fraud risk areas?

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Uri Tyroler – VP Business Development

• CEO, VP BD, VP Sales & Marketing in mid-size & public companies • 30 years experience in business development in foreign markets• Education – BA Economics, MBA Finance & Marketing

Amir Weinberg – CEO• R&D director in Mercury Interactive • Founder & President of Orsus Solutions • Education – BA Mathematics, Computer Science

Founders

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Leaders

Leonard Vona, CPAHead of Fraud Risk

Assessment

Gal Amir, CPAHead of SAP

solutions

Max Kholmyansky, M.ScVP R&D

Vadim Levin,Product Dev.

Manager

Oren Gavish,Customer Solutions

Manager

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THANK YOU!

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