Big data Analytics & Machine learning Next Gen Audit … · • The advantage you have yesterday, ... BI Platforms Cognos Micro- ... Created Date: 1/28/2017 2:56:17 AM

Big data Analytics & Machine learning – Next Gen

Audit approach.

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The Knowledge that we have

NO FULL Knowledge is the

GREATEST Knowledge of All


Agenda

• Check in

• The Nokia Syndrome

• Who Moved my cheese!!!

• Understanding Big Data Analytics landscape & audit Impact

• Machine learning & its Impact on Audit

• Approach toward Analytics- Baby Step

• Check out


Statement by Nokia CEO

During the press conference to announce Nokia’s

smartphone division being acquired by Microsoft,

Nokia CEO ended his speech saying this “we

didn’t do anything wrong, but somehow, we lost”.

Upon saying that, all his management team,

himself included, teared sadly.


Why it happened at Nokia !!!

• The advantage you have yesterday, will be replaced by the trends of

tomorrow.

• To change and improve yourself is giving yourself a second chance……….

To be forced by others to change, is like being discarded.

• Those who refuse to learn & improve, will definitely one day become

redundant & not relevant to the industry. They will learn the lesson in a hard

& expensive way


5%(3.7 Trillion USD)

of annual revenues of organizations are lost to fraud* ACFE

Why to understand Big Data & Machine

learning?


7

Initial Detection of Occupational Frauds- Audit is failing the business!!


Deloitte has been ordered to pay damages to the theatre company’s creditors after

an Ontario judge ruled the accounting firm failed to detect fraud at the company,

even though there were plenty of warning signs that something fishy was going on

in the 1990s.

The judgment is a very rare situation. For years creditors and investors have been

looking for ways to sue corporate auditors.

Latest…in the news!

Livent’ Auditor Deloitte ordered to pay $ 84.8 million for failing to detect fraud


Fraud’s are nothing new!!!!!

Forty Possible frauds were listed in “ The Arthashastra by Kautilya”


Check in :The Bits & Bytes

· 1 Bit = Binary Digit

· 8 Bits = 1 Byte

· 1024 Bytes = 1 Kilobyte

· 1024 Kilobytes = 1 Megabyte

· 1024 Megabytes = 1 Gigabyte

· 1024 Gigabytes = 1 Terabyte

· 1024 Terabytes = 1 Petabyte

· 1024 Petabytes = 1 Exabyte

· 1024 Exabytes = 1 Zettabyte

· 1024 Zettabytes = 1 Yottabyte

· 1024 Yottabytes = 1 Brontobyte

· 1024 Brontobytes = 1 Geopbyte


Explosion of digital data: 90% of the world’s data created in the last

2 years


tools & technologies

• Large volume of data

• External data

• Un-structured data

• Statistical modeling

• Machine Learning

• Real-time analysis

• Interactive visualization


And then the BigData…


And then the Big Data…

• What is BIG DATA?

Big Data refers to datasets that grow so large that it is difficult to

capture, store, manage, share, analyze and visualize with the

typical database software tools.

It is “massive (Volume)” data, in “different (Variety)” format, from

“different” sources, growing at “lightning(Velocity)” speed!!!


We have to transform Unstructured Data into meaningful

insights

Flash Files

Images,

Archives

PDF Files

Log Files

Text Data

Transaction

Systems,

CRM, ERP,

BI, EPM,

DWH

Websites,

URLs,

Social

Media’s,

Forums,

Blogs,

Messengers

News Portals

E-Commerce

Transactional Data

Unstructured Data

Semi Structured Data

Structured Data

World Wide Web & Social Media


Why business analytics?

Five big trends are driving the adoption of new approaches to business analytics. Taken together they

underscore an unforgiving demand for improved performance and a wake-up call for more disciplined risk

management.

Data Volumes & Technology Capacity

Regulations

Cost reduction

New Signals

Hidden Sight


Machine learning

Aspect of AI: creates knowledge

Definition:

“changes in [a] system that ... enable [it] to do the same task or tasks drawn from the same population more efficiently and more effectively the next time.'' (Simon 1983)

There are two ways that a system can improve:

1. By acquiring new knowledge

acquiring new facts

acquiring new skills

2. By adapting its behavior

solving problems more accurately

solving problems more efficiently


Opportunity for Machine learning within Audit & risk management

• Data supports fact-based analysis in investigation

• Automated techniques can cover up to 100% of the Data populations of the assesse.

• Regression Analysis based Machine learning for Audit population review

Data analytics has significant potential to be

Exploited in the Assessment & investigation Space


Analytics In Investigation : Key Technology features

Pattern analysis

External data analysis

Machine Learning

Log MiningBehavioral

analysisInteractive

Visuals

Unstructured data

Real-time event

monitoring


What type of questions analytics can answer

Hindsight Insight Foresight

What happened?

Where is the

problem?

What actions are

needed?

Why is this

happening?

What if these

trends continue?

What will happen

next?

What’s the best

that can happen?


Tools and Technology

Representative analytical tools are outlined below — deciding which tool is best for the situation is key.

Excel/

AccessProductivity/Database SQL

ACLTraditional Audit Idea

SASStatistical/Analytics SPSS

TableauVisualization/Self

Organizing MapsViscovery

CognosBI Platforms Micro-strategy

• Most organizations use a combination of traditional audit and

statistical/analytics tools.

• Many of these tools may be available via existing ELA’s with key

vendors that IA can leverage.

• Engineer and deploy the necessary infrastructure and

accelerators (with appropriate IT support) such that the IA

teams can focus on analytics vs. routine tasks.

• Multiple ways to source the data — feeds, secure ftp, read only

access to views, etc.

• Acknowledge gaps with data — but with some diligence it is

possible to work through the data quality issues


Six guiding principles – getting started with Advanced Analytics

Link your Goals and

objectives with Clear

Business Drivers

Know your data

Start Simple

Leverage Existing

Insights

Make it Actionable

and Measurable

Test and Learn

Establish a clear understanding of expected benefits from Analytics and ensure linkage to audit planning.

This will translate into clear objectives that drive the strategy, long term vision and surface the near term

opportunities.

Data is the key ingredient. It drives the insights that fuel the benefits from any Analytics program. It

is critical to understand both the data you have and the data you don’t have when determining how

and where you should begin. This knowledge also prioritizes efforts to collect what’s missing for

future analyses and enhancements to your Analytics program.

There is no need to boil the ocean at the outset. Starting with a targeted, ad hoc analytic program

will yield greater benefits in terms of speed to insights, learning and value. Take the time to learn

first and then deploy necessary capabilities across the enterprise later.

When possible, leverage existing analytics capabilities (look within the business) to jump-start the

program and build consistency with prior initiatives. These insights should also provide clues

related to the risks and business areas to start with.

Develop a plan to take action and measure results accurately early in the game. The organization,

systems and process that support execution must be able to take action with the insights that are

generated recommendations.

Be willing to test different approaches and areas of the business. Learn from results and try new

approaches based on what is learned.


Expect the Unexpected…

Be Prepared!!!

Questions and

Thank YouCA ANAND PRAKASH JANGID

+91 9620233516

[email protected]

www.quadrisk.com

mailto:[email protected]

Documents

Big data Analytics & Machine learning Next Gen Audit … · • The advantage you have yesterday, ... BI Platforms Cognos Micro- ... Created Date: 1/28/2017 2:56:17 AM