Business
Intelligence & Data
Analytics
- an introductory perspective
Presenter: Leigh Franklin, Partner KPMG Hobart
TAO – Client Information Session
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
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?
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© 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?
“The process of
inspecting, cleaning,
transforming, and
modelling data with
the goal of
highlighting useful
information,
suggesting
conclusions, and
supporting decision
making.” – Wikipedia
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© 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!
Business Intelligence & Data Analytics – does it need to be
complex?
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)
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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© 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
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?
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© 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
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
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© 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
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?
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© 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"
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%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
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
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© 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
($)
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”.
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© 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.