Business Intelligence & Data Analytics - an introductory perspective

Transcription

1 Business Intelligence & Data Analytics - an introductory perspective Presenter: Leigh Franklin, Partner KPMG Hobart TAO Client Information Session 8 May 2014

2 Agenda KPMG presenter s contact information: Leigh Franklin Partner, Hobart Tel: Mob: lcfranklin@kpmg.com.au Business intelligence Why? What is it? Does it need to be complex? Does it require special tools? Questions Example routines 1

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? 2

4 Business Intelligence & Data Analytics why? 3

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 4

6 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! 5

7 Business Intelligence & Data Analytics does it need to be complex? 6

8 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 ( s, social media, SMS, etc) Volume the amount of data (remember you need not use everything, just the right bits) Velocity how fast it is processed / analysed (both captured and reported) 7

9 Business Intelligence & Data Analytics does it require special tools?... because there are plenty available Value 4 Big Data This can be a paradigm shift in the scope of data Analysis 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 3 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. 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. Insight KAAP 1 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. KAAP TIME 8

10 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 9

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? 10

12 Business Intelligence & Data Analytics questions & discussion Questions? 11

13 Business Intelligence & Data Analytics example routines Sales analysis Utilise routines to identify duplicate sales, sales which exceed credit limits, irregular sales, etc. 1 Identify unusual items and movements

14 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 13

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? A B C D E F G H I 14

16 Business Intelligence & Data Analytics example routines Loan book stress testing: Utilise Tableau to plot mortgage exposure based on post codes ABS Published Big Data" Compare against industry data to see whether there is any indication of loan / debtor book default or impairment risk. Sydney map 15

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. # of payments at each authorisation level 4% 3% 1% 0% < $2,000 <$20,000 $ amount of payments at each authorisation level <$5,000,000 11% < $2,000 2% <$20,000 10% 14% <$50,000 <$200,000 <$50,000 11% <$2,000,00 0 <$5,000, % <$2,000,000 36% <$200,000 30% 16

18 Business Intelligence & Data Analytics example routines Expenditure delegation analysis: Does it appear that expenditure delegation levels are being manipulated? # of payments within 1% of authorisation limit % of total number of payments per authorisation limit within 1% 1% of -<$200,000 13% 1% of - <$2,000,000 <$5,000,000 0% 1% of -< $2,000 37% % of total number of payments made 1.20% 1.00% 0.80% 0.60% 0.40% 0.20% 0.00% 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 1% of -<$50,000 25% 1% of -<$20,000 25% 17

19 Business Intelligence & Data Analytics example routines Expenditure delegation analysis: Are the delegations capturing the right types of expenditure? Value of expenditure by type and delegation category 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% < $2,000 <$20,000 <$50,000 <$200,000 <$2,000,000 <$5,000,000 Other expenditure Capital projects Pre feasability 18

20 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 $500 or less per transaction, but that there are a number of cards where the average transaction is of a higher value 1,000 Average spend per Corporate Credit Card ($) 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: Total $ value of identified transactions # Trans. Discussion Fuel 46 7,538 Section 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 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 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. 20

22 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? 21

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 22

24 Thank you KPMG presenter s contact information: Leigh Franklin Partner, Hobart Tel: Mob: lcfranklin@kpmg.com.au KPMG Business Intelligence & Data Analytics specialist contact information Anthony Coops Partner, Melbourne Tel: Mob: lacoops@kpmg.com.au

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