Audit Automation and Data Analytics PwC’s Digital …€™s Digital Services Audit Automation and Data Analytics ... • Provides IT risk consulting services to a wide range of

PwC’s Digital Services

Audit Automation and Data Analytics

www.pwc.com/digitalStrictly private and confidential


Introduction and background

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Introduction

Background• Director and Chartered Accountant leading Data Assurance and Insights for PwC in

the Middle East• Provides IT risk consulting services to a wide range of global and local clients• Knowledge and experience of multiple industries, including utilities, petrochemicals,

oil & gas, logistics and automotive• Experience in business operations, data management and assurance activities, as well

as data analytics program delivery

Area of Expertise and Skills• Data analytics programs• ERP and GRC solutions with a focus on security and controls• Data analysis such as process mining and process utilization• Data visualisation and BI reporting

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Twitter – @thomaspulling

Mobile – +971 (0)56 9930880

Email – [email protected]


DRIVERS

500mtweets are sent every day

The power of digital and data grows every day.

Unlocking it is vital to stay relevant, and now 68%

of CEOs see the greatest return on investment is

in tools to do this.

Embedding independent and

meaningful data analytics into

every component of the audit

cycle to enhance the coverage,

efficiency and effectiveness of

audits, gives Internal Audit

more time to focus on

enterprise value and becoming

critical advisors to the

business.

GROWTH & ANALYSIS

90%of data was created in the last 2 years

The amount of data in the digital universe is

doubling every two years, and 85% of this

data is coming from new data sources.

DRIVERS

26bnunits in IoT by 2020

Two thirds of the Internet of Things will be

other things such as sensors, actuators and

new devices that monitor, control, analyse

and optimize our world.

GROWTH & ANALYSIS

0.5%of data is actually analysed

We aren’t making the most of the data we

have available and 30% of executives admit

intuition is still a key source for big decisions.

“

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Where do you want to get to?

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Defining audit automation

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The analytics maturity model represents the different levels for an IA function, with continuous auditing reflecting a position of true audit automation.


What does continuous auditing mean?

Identify

Monitor

Illuminate

Change

Identify key risks across the lifecycle

which should be monitored

Monitor the environment continuously

using relevant metrics and KPIs which

are constantly refined and enhanced

Highlight and review exceptions that

arise from data flows and metrics as

they happen

Change the audit plan to account for

risk changes and remediate issues in

real time

Continuous Auditing

Plan and build

analytics

Connect data

sources

KPIs and

metricsKey audit

risks

Refine risks in

audit planFull

Integration

and visibility

Capture

exceptions

Dynamic

audit plan

Unplanned

auditsRefine false

positives

Assess

impact

of exceptions

Support

remediation of

issues

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How do you get there?

How do you achieve true audit automation and embed data

analytics in everything that you do?

Continuous audits

Enhance and refine the supporting

team structure for analytics and

managing audit exceptions

Select key risks for monitoring and

build appropriate metrics

Manage data flows and links to key

sources to support monitoring

Continuously monitor key risks

through data analytics and ensure

audit plans reflect exceptions

Embed the capability

Develop further analytics to cover

all components of the audit

lifecycle

Share success stories and

demonstrate built capability to raise

awareness and momentum

Support further audits and

empower the Internal Audit team to

operate with a data mindset

Ensure training plans, supporting

teams and technology are sufficient

for the future

Pilot audits

Implement technology to support

some initial analytics and KPIs

Select a controlled number of

audits to perform data analytics

Identify key learning from pilot

audits and ensure audit

programmes are updated

Begin developing a suitable

support team

Strategy and support

Build the strategy, roadmap and

plan to achieve the target state

Circularise the strategy and get buy

in from key stakeholders

Define executive ownership and

sponsorship for the programme

Assess and define

Assess the current capability of the

team and supporting technology

Understand key risks and linked

data sources

Define the vision for a target state

PwC’s Digital Services 8


What benefits can you expect?

InsightsGreater insights – you can

reposition IA as a value add

function and drive change!

CoverageIncreased coverage provides

opportunities for IA to identify

inefficiencies

PlanningEnables strategic plans to be more

real time and proactive, rather than

fixed schedule

ThinkingProviding more time to think,

aiding the shift from auditor to

business advisor

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Where should you start?

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Develop the roadmap for the future

Define the timeline and

roadmap to achieve

success

How do we achieve our vision?

What do we do and when?

How do we keep momentum?

Expected effort – 3 weeks

Articulate targets across

People, Processes and

Technology

What do we want to achieve?

Why do we want to do this?

How long will it take?


Analyse the “as is” of the

team with data analytics

in mind

Where are we now?

What are we capable of?

Where might issues arise?


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Analyse the right data in the right way

While it is important to be able to find, access and connect the data, it’s vital to prioritise what is most important

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Start Here

Then work that way

Don’t start here or you’ll create a “data swamp” no one can or wants to use

Strategicobjectives / goals

Stakeholderpersonas

Stakeholderneeds

Data visualisations / KPIs Metrics

Standarddata model

Data sources(aggregate / root)

Source dataattributes


What steps do you need to take?

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Steps to take – People

One vision. One plan.

• Modify the existing team structure to include a data analytics team

• Recruit data analytics specialists with the right “coding” capability

• Identify data champions in the team to “bridge the gap”

• Develop a data focused training plan

• Focus attention on change management

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Steps to take – Processes


• Develop appropriate policies and procedures that align to those in the business

• Determine appropriate audits for data analytics to be embedded into

• Understand and update the existing audit programs to incorporate data tests

• Identify relevant data analytics for all parts of the audit lifecycle

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Steps to take – Technology


• Identify, evaluate and implement the appropriate tools for analyzing data for audits

• Define and implement a well controlled, independent architecture for hosting and analyzing all business data

• Understand and connect to key data sources that are required for data analytics across the audit lifecycle

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What problems might you encounter?

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Analytics programmes – why do they fail?

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The introduction of data analytics to the Internal Audit function needs to be viewed as a programme. This means it represents a significant period of change, and so there are clear risks to the success of the initiative.


Common challenges in deploying data analytics

These are the typical challenges and issues you

can expect to face when embarking upon a data

analytics implementation for Internal Audit.

No. 1Change

Resistance to change from the Internal Audit team

members

No. 2IT support

Lack of support from IT in obtaining data

No. 3Momentum

Focusing time and resources to maintain

momentum

No. 4Understanding

Lack of understanding of the purpose, intention or

approach

No. 5Skills

Insufficient skills to sustain the change in the long

term

No. 6Data quality

Poor quality data that leads to difficult or unreliable

analysis impacting user confidence

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Questions and answers

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06


Data is the new oil… there is significant value and competitive power locked inside it. Only those organisations who have effective data analytics functions will be able to manage, control, transform

and analyse their data to harness its potential.

PwC’s Digital ServicesPwC’s Digital Services 21


Thank you!

© 2016 PwC. All rights reserved. Not for further distribution without the permission of PwC. “PwC” refers to the network of member firms of

PricewaterhouseCoopers International Limited (PwCIL), or, as the context requires, individual member firms of the PwC network. Each

member firm is a separate legal entity and does not act as agent of PwCIL or any other member firm. PwCIL does not provide any services

to clients. PwCIL is not responsible or liable for the acts or omissions of any of its member firms nor can it control the exercise of their

professional judgment or bind them in any way. No member firm is responsible or liable for the acts or omissions of any other member firm

nor can it control the exercise of another member firm’s professional judgment or bind another member firm or PwCIL in any way.

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Audit Automation and Data Analytics PwC’s Digital …€™s Digital Services Audit Automation and Data Analytics ... • Provides IT risk consulting services to a wide range of