/
October 26, 2017 Using Data Analytics to Enhance Your Anti-Corruption October 26, 2017 Using Data Analytics to Enhance Your Anti-Corruption

October 26, 2017 Using Data Analytics to Enhance Your Anti-Corruption - PowerPoint Presentation

trish-goza
trish-goza . @trish-goza
Follow
366 views
Uploaded On 2018-03-11

October 26, 2017 Using Data Analytics to Enhance Your Anti-Corruption - PPT Presentation

Sharon J Zealey Introduction to analytics review for IFBEC AP Transactions Pcard payments TampL expenses Petty Cash transactions Third party payments Charity Political contributions ID: 647379

transactions amp identifies expenses amp transactions expenses identifies payments card review analytics identify data company compliance charges expense suspicious

Share:

Link:

Embed:

Download Presentation from below link

Download Presentation The PPT/PDF document "October 26, 2017 Using Data Analytics to..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.


Presentation Transcript

Slide1

October 26, 2017

Using Data Analytics to Enhance Your Anti-Corruption

Sharon J. ZealeySlide2

Introduction to analytics review for IFBEC

AP Transactions

P-card payments

T&L expenses Petty Cash transactions

Third party payments

Charity

Political contributions

Gifts

Entertainment Sponsorships Education support Facilitating paymentsGovernment contracts Segregation of Duties Sales and Marketing Education support Export/Import

Non-compliance to Regulations & Company PoliciesFraudulent/Improper/duplicate payments Segregation of Duty conflictsIneffective review and approval mechanism

Development of Policies and ProceduresTraining and AwarenessTransaction testing and review

Various laws worldwide prohibit corrupt payments to foreign officials for the purpose of “obtaining or retaining business.” Corporations are required to make and keep books and records that accurately and fairly reflect transactions. Non-compliance could lead to civil and criminal penalties, including imprisonment.

Fraud and regulatory analytics

approach

should cover

review of all payment

methods, potential passive

bribery and both government and private party contracts /transactions . Slide3

Use a methodology that is in line with

regulatory expectations as outlined by SEC & DOJ to implement a continuous monitoring framework for all payables and expenses with focus on expenses incurred on government and other high risk third

parties. Methodology

Highlights

Data Analytics Methodology

Review Big Data from disparate sources

Data can be ingested from disparate ERP and T&E systems

like

SAP, Oracle, Concur etc.

Identification and flagging of

repeat red flags, ensuring false positives

are saved in system and

do not reappear in subsequent red flags

Machine Learning & Domain

Expertise

Digitally

Enabled- (

smart workflows and advance visualization)

Wider coverage with linkage to external Databases

like OFAC sanctions, SDN sanctions,

World

Bank sanctions across 50+ countries.

Smart Workflows and Integrated Dashboards with drill-down

capability

Inbuilt workflow for sample review and substantive testing – audit trail

and comments can be stored in the WF

Based on

common trends, market insights

, etc. the

rules are continuously modified

Key learning

from analytics is used to

update the compliance policy

and

program

of the companySlide4

Anti

Bribery Analytics (AP and T&E) by Genpact

No

Test performed

Analytic

objective

T&E

AP

1

Key

word search test

Identify transactions that could indicate Policy/FCPA/ regulatory violations including gifts, political contributions, entertainment and charitable contributions

2

Suspicious MCC

Identifies

potentially-improper

charges submitted

by

flagging merchants having a suspicious Merchant Classification Code (MCC)

3

Prohibited vendors

Identify transactions with sanctioned/ prohibited vendors using external data sources

4

Unusual Expenses

Identifies

suspicious transactions where the report contains

potential

conflicting claims like

T

ransactions on weekends and repetitive

expenses with same vendor

5

Policy Compliance

Identifies

non

reimbursable

expenses / prohibited expenses

in accordance with

applicable

Company

policies.

6

Top Transactions

Identifies

both the largest spenders and largest transactions in each expense category

like meals,

events, etc

7

Suspicious

Mileage

Conflicting

travel expense claims submitted for same day such as both air travel & car; fuel, taxi & car rental etc.

8

Duplicate Payments

Identify employees charging on T&E-Card the same expense twice/ routing same expense through

cash & card

9

Threshold Limit

Identifies

employees who consistently claim amounts just below approval thresholds, or attempt to use a large number of small currency charges to hide spending

activity

10

Even Dollar Transactions

Identifies

all individual charges evenly divisible by a specified parameter value (e.g. 100

).

Even-dollar charges usually represent the purchase of gift cards, vendor advances, or other similar purchases.

11

AP Expenses

Identifies T&E

c

ard

expenses that should have processed through

AP

and AP expenses charged to T&E cards

12

Cash

Transactions

Identifies

T&L where the employee did not use the Corporate Business

Card.

14

Split

Transactions

Identifies employees charging amounts to the card more than once to circumvent the spending limits or hide large expenses. Splitting transactions could occur within the same employee card, with more than one card

15

Transactions with High Risk Countries

Identify High risk payments to Government entities / corruption prone countries per CPI Index

16

Flip-Flop Bank Accounts / Alternate Payee Name

Identify vendors with more than one change to bank account number / alternate payee name within a specified time period (if details available)

17

Payments to individuals

Identify payments

made directly to

individuals of a company instead of the company name