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Business

Intelligence & Data

Analytics

- an introductory perspective

Presenter: Leigh Franklin, Partner KPMG Hobart

TAO – Client Information Session

(2)

1

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Agenda

Business intelligence

Why?

What is it?

Does it need to be complex?

Does it require special tools?

Questions

Example routines

KPMG presenter’s

contact information:

Leigh Franklin

Partner, Hobart

Tel: 03 6230 4033

Mob: 0407 304 002

lcfranklin@kpmg.com.au

(3)

Business Intelligence & Data Analytics – why?

"Every minute the world generates 1.7 million

billion bytes of data, equivalent to 360,000 standard

DVDs. More digitised data was created in the last

two years than in the rest of human history. This

trend and the mountains of data it produces is what

we call 'Big Data'. The big data sector is growing at

a rate of 40 percent a year."

7 November 2013 European Commission Fact

Sheet, What is data?

(4)

3

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

(5)

Business Intelligence & Data Analytics – what is it?

“The process of

inspecting, cleaning,

transforming, and

modelling data with

the goal of

highlighting useful

information,

suggesting

conclusions, and

supporting decision

making.” – Wikipedia

(6)

5

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data analytics - what is it?

“...highlighting useful information, suggesting conclusions, and supporting

decision making.”

• Consider this extract of the definition as it relates to your organisation. It

provides the context that DA needs to be conducted in

“useful information” to who? Board, Management, Auditors (internal & financial

statement), Regulators, all of the above

“supporting decision making in relation to what? Strategic insight, business

performance, KPI / “Red Flag” monitoring, compliance, control continuous

monitoring, forensic investigation, internal analysis (of the organisation), market

segment analysis

Not all information is useful information – make sure you think about what you’re

trying to achieve before you start the journey and remember the context!

(7)

Business Intelligence & Data Analytics – does it need to be

complex?

(8)

7

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – does it need to be complex?

It can be, but an organisation doesn’t need to start at “the top of the mountain” to achieve

value add from DA

Things to consider:

Value – making sure the findings are insightful and can be "used" as opposed to just

'interesting'.

Veracity – the accuracy of that data and how it may relate to business value (remember that

'bad data in means bad data out')

Variety – the different types of data

• structured (databases, spreadsheets, etc)

• unstructured (emails, social media, SMS, etc)

Volume – the amount of data (remember you need not use everything, just the right bits)

(9)

Business Intelligence & Data Analytics – does it require special tools?

Insight

Analysis

TIME

V

al

ue

1

4

3

2

Continuous auditing and monitoring

Using real-time, or near real-time, analysis of data, anomalies

can be flagged immediately and investigated. Analytical

performance can be constantly improved through analysis of

false positives.

Rules based testing

Historical analytics. Using historical data, and a series of simple

and complex analytical tests, significant value can be gained by

the analysis of past performance.

Predictive analytics

Using advanced statistical techniques, future risks

can be determined. Coupled with a historical rules

based analysis, this combination of analytics is an

immensely powerful tool.

Big Data

This can be a paradigm shift in the scope of data

included within the risk review and in the way data

is leveraged. New techniques make it possible to

analyse large data volumes and data from disparate

and unstructured sources

KAAP

KAAP

... because there are plenty available

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9

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – does it require special tools?

It can do, but you also don’t need to crack a nut with a sledge hammer!

Things to consider:

Complexity of what you’re trying to achieve

Capacity & capability of your existing information management systems – don’t over look the

untapped potential of your existing systems

Capability & capacity of your in-house resources

Privacy & data security

(11)

Business Intelligence & Data Analytics – so the questions are ...

... how many of your organisations are making

the best of what you’ve got?

Are you using data analytics to identify and

extract any valuable information and insights?

(12)

11

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – questions & discussion

(13)

Sales analysis

Utilise routines to identify duplicate sales,

sales which exceed credit limits, irregular

sales, etc.

Identify unusual items and movements

Business Intelligence & Data Analytics – example routines

1

3

(14)

13

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – example routines

Receivables movements:

Identify top 20 receivables balances by customer and “join” this with prior year database

and compare movements.

Identify significant movements/anomalies

Significant increase in balance

New debtor

(15)

Business Intelligence & Data Analytics – example routines

Interest rate Risk:

Plot average interest rate against average risk grade by product

Identify potential products which are priced incorrectly

Pricing methodology

inconsistent?

(16)

15

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – example routines

Loan book stress testing:

• Utilise Tableau to plot mortgage exposure based on post codes

• Compare against industry data to see whether there is any indication of loan / debtor book

default or impairment risk.

ABS Published “Big Data"

(17)

Business Intelligence & Data Analytics – example routines

Expenditure delegation analysis:

• Analysis conducted to reflect on whether delegation authorisation levels established by the

Board facilitate efficient procurement whilst providing desired control.

78% 14%

4% 3% 1% 0%

# of payments at each authorisation level

< $2,000

<$20,000

<$50,000

<$200,000

<$2,000,00

0

<$5,000,00

0

< $2,000 2% <$20,000 10% <$50,000 11% <$200,000 30% <$2,000,000 36% <$5,000,000 11%

(18)

17

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – example routines

Expenditure delegation analysis:

• Does it appear that expenditure delegation levels are being manipulated?

1% of -< $2,000 37% 1% of -<$20,000 25% 1% of -<$50,000 25% 1% of -<$200,000 13% 1% of -<$2,000,000 0% 1% of -<$5,000,000 0%

# of payments within 1% of authorisation limit

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1% of -<

$2,000

1% of

-<$20,000

1% of

-<$50,000

1% of

-<$200,000

1% of

-<$2,000,000

1% of

-<$5,000,000

%

of

t

ot

al

num

ber

of

pay

m

ent

s

m

ade

(19)

Business Intelligence & Data Analytics – example routines

Expenditure delegation analysis:

• Are the delegations capturing the right types of expenditure?

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

< $2,000

<$20,000

<$50,000

<$200,000

<$2,000,000

<$5,000,000

Value of expenditure by type and delegation category

(20)

19

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – example routines

Credit card expenditure analysis:

• Analysis shows the average spend per card for the 6 month period under consideration. The

number of cards is on the horizontal access and the average dollar value of transactions on the

vertical axis. This demonstrates that the vast majority of cardholders regularly spend $500 or

less per transaction, but that there are a number of cards where the average transaction is of a

higher value

-200

-

200

400

600

800

1,000

0

100

200

300

400

500

600

Average spend per Corporate Credit Card ($)

Average

spend per

Corporate

Credit Card

($)

(21)

Business Intelligence & Data Analytics – example routines

Credit card expenditure analysis:

• Analysis of credit card expenditure against pre-determined criteria (policy, legislative

compliance)

Transaction

description

includes:

# Trans.

Total $ value of

identified

transactions

Discussion

Fuel

46

7,538 Section 5.3.4 of the Policy discusses the purchase of fuel on the Corporate Credit Card (CCC). It expressly states

“The CCC should not be used for the purchase of fuel as there is already a separate contract card available under a

common use/whole-of-government contract”. We note that there are limited exceptions based on remote locations.

Purchase of fuel for hire cars, Department owned vehicles and vessels is also disallowed. In 25 instances the

description for indicates the fuel was purchased for a hire car, or a government vehicle.

Insurance

20

408 The Travel Payment and Allowance Policy disallows the purchase of travel insurance. Of the 20 transactions noted

with ‘insurance’ in the description, 18 appear to be travel related, and 1 is for windscreen insurance.

Gift

6

1,211 The CCC Policy states that the purchase of gifts is only permissible in very limited circumstances, such as the

purchase of bereavement flowers. In each of the 6 transactions identified, the description and vendor names

indicate purchases of chocolates, picture frames and books.

Reimburse

19

1,222 The CCC Policy states that the card must not be used for personal transactions, even if it is the cardholder’s

intention to immediately reimburse the private expenses. We searched for the terms ‘reimburse,’ ‘personal’ and

‘private’. For ‘reimburse’ we noted 13 transactions that appeared to be awaiting reimbursement from another

organisation, and the remaining 6 included 5 personal expenses to be reimbursed (didn’t appear to have occurred

during the period), and 1 reimbursement from a vendor.

Personal

8

773 Of the 8 transactions noted, 4 offset each other as reimbursed personal transactions, the remaining 4 included 3

identified also through ‘reimburse’ above, and 1 transaction for $587 entitled “Personal Airfare”.

(22)

21

© 2014 KPMG, an Australian partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

KPMG and the KPMG logo are registered trademarks of KPMG International.

Business Intelligence & Data Analytics – example routines

Fraud red flags:

Establish comparative data analysis and look for

unusual and unexpected correlations

• Does it make sense that there 3 instances where

the same bank account details are used by 5

different creditors?

• Match employee bank account data against

creditor data – does it makes sense that there are

matches?

(23)

Business Intelligence & Data Analytics – example routines

Employee related practices

Establish comparative data analysis and

trends to look for unusual and unexpected

correlations

• Does it appear that leave policies are being

contravened?

• Monitor excessive leave balances

• Monitor instances of allowances –

extended duration, repetitive, etc

(24)

Thank you

KPMG presenter’s contact information:

Leigh Franklin

Partner, Hobart

Tel: 03 6230 4033

Mob: 0407 304 002

lcfranklin@kpmg.com.au

KPMG Business Intelligence & Data

Analytics specialist contact information

Anthony Coops

Partner, Melbourne

Tel: 03 9288 6451

Mob: 0412 291 782

(25)

The KPMG name, logo and “cutting through

complexity” are registered trademarks or trademarks

of KPMG International.

© 2014 KPMG, an Australian partnership and a

member firm of the KPMG network of independent

member firms affiliated with KPMG International

Cooperative (“KPMG International”), a Swiss entity. All

rights reserved.

KPMG and the KPMG logo are registered trademarks

of KPMG International.

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