Internal Audit and Technology Sustainable Analytics Audit and Technology Sustainable Analytics Neil...

Internal Audit and TechnologySustainable Analytics

Neil While, Partner, Internal Audit Analytics

Deloitte Advisory | December 14, 2015

0

1 Copyright © 2015 Deloitte Development LLC. All rights reserved.

The Four Faces of the Chief Auditor


Survey of Internal Audit Analytics & Adapt or disappear

“Available at www.Deloitte.com”, search for the title.

http://www.deloitte.com/

Survey Results74 organizations were included in the survey, predominantly in UK.

3


Maturity of internal audit analyticsIs the profession fully developed, or is it still early days?

74% of firms surveyed are in limited and developing maturities categories


Maturity of internal audit analyticsWhat proportions of audits are supported by analytics?

• An average of 24% of audits are supported by analytics across participants

• Advanced firms are supporting 43% of the audit plan, whilst developing firms are supporting 21%

• Advanced firms are using statistical platforms such as SaS, SPSS and R


Maturity of internal audit analyticsHow much budget is spent on analytics?

Advanced analytics teams are on average 3% of the total internal audit function cost, whilst developing are on average 6%


Aligning delivery approach to strategyWhat are analytics teams striving for?

Two strategy outcomes for analytics were identified from survey participants:

• To create efficiencies for internal audit through automation; or

• Analytics driven insights


Leading PracticesWhat do the leading companies do well?

• Buy-in from senior stakeholders

• Analytics team integrated in to internal audit function

• Investment in skills of the analytics team

• Identify solution to data issues

• Leveraging analytics capabilities across the business


Future ambitionWhat are the ambitions of the leading firms?

• Analytics to be a core element of internal audit process

• Driving the audit plan through continuous risk assessment

• Targets of 70% of audits to be supported by analytics

• Big Data

• Research and development teams

• Developing basic analytics capability of core business auditors


Sustainable AnalyticsBased on a strong foundation of people, process, and technology, sustainable analytics will drive value for internal audit


Planning the journey, cont.Key Questions to Ask

Strategy

People

Process

Technology

Data

Analytics vision for audit servicesIdentifies key projects/programs, stakeholders and metricsAligned with corporate and information technology strategies

Organizational structure and program sponsor/managerCapability / competency acquisition or developmentCollaboration and communication planning

Operating model for developing and consuming insightsAnalytics prioritization and project management Methodologies and approaches for analytics

Solution requirements, evaluation, selection and set-upTechnology vendor / license managementTechnology architecture and solution optimization

Data acquisition and enrichmentData model architectureData governance and security

S

P

P

D

T

Building Blocks

Building a sustainable analytics function requires a foundation of the fundamental building blocks of People Process, Data and Technology, informed by an Analytics Strategy.

Who is the accountable IA owner? What organisational structure do we need to put in place to support our analytical strategy? Who do we need to engage in other departments and what are their roles? What other talents do we need and what is the plan for getting them?

How do we identify the right projects on which to focus our efforts? What are the steps we need to take to ensure that these projects are a success? How will we comply with relevant regulations? What are the risks and how do we mitigate them? How will we measure our progress and test the validity of the insight?

What data do we need to answer the business questions? From where is it sourced – internal, external, licensed, open? How do we bring it together and what are the challenges in transforming, linking and publishing it? What about quality and accuracy?

What tools do we need to process the data? How do we scale up the technology when we need to roll out our solution to the rest of the business?

Key Questions to Consider


“Purple People”Te

chni

cal s

kills

Testing Defining, developing and implementing quality assurance practices and procedures for technical solutions and validating hypotheses.

Reporting software Understanding of the underlying theory and application of key reporting software

Data analysis skillsEvaluating data using analytical and logical reasoning for the discovery of insight, e.g. predictive modelling

Data modellingStructuring data to enable the analysis of information, both internal and external to the organization

SQL queryingQuerying and manipulating data to facilitate the solving of more complex problems

Technology alignmentUnderstanding how technology can be leveraged to solve business problems

Soft skillsCommunication and interpersonal skills are necessary to articulate insight gained from analysis

Business commentary Articulation of insight to explain current and forecasted trends, their impact and opportunities for the organization

Business knowledgeUnderstanding of business measurement of key performance indicators and business frameworks.

Macro-perspectiveUnderstanding of the organization strategy, current issues and priorities and current trends

Dat

a an

alys

isB

usiness acumen

Storytelling


Operating Models

De-centralised

Centralised

CoE modelFunctional driven with overlap of analytics requirements across functions and the need to drive standardisation

Centralised modelA group of analysts, acting as a core unit, serve the entire company cross functional boundaries.

Dispersed modelDepartment driven for organisations with minimal overlap of analytics requirements across departments

Corporate centre

Analytics project

Analytics project

Function unit

Business area

Corporate centre

Analytics project

Function unitCoE Business

area

Corporate centre

Analytics project

Function unit

Analytics unit

Business area

= Analytics capability


ActPutting it all into action


“Pick battles big enough to matter, small enough to win.”

— Jonathan Kozol

Presenter

Presentation Notes


Selecting the right areas to focus on

High risk with too Low value to be prioritized

Reasonable return on investment and should

be prioritized

High value and Low risk should be top priority

Reasonable return on investment should be

prioritized

Identify risk

Protect brand

Capability build

Strategicrisk alignment

Cost reduction

Understandingthe Data

Risk

Valu

e

Value drivers Assessment framework

Presenter

Presentation Notes

Selecting the right areas to focus on


Question Insight Action

“There is nothing so terrible as activity without insight”

— Wolfgang von Goethe


Model maturity development

“A noticeable ROI from advanced analytic techniques is the reduction in cost, time and effort, to review transactions and assess

if they are truly of concern”

Fals

e po

sitiv

e ra

te

Unusual transactions identified per period

Random SamplingGeneral Rules

Tailored Rules

Risk Aggregation

Machine Learning

Profile Risk Aggregation

99.99%99.5%

99.25%

60%

30%25%

0.01 400.5 0.75 60 75 100


Data visualisation focuses on presenting data in the most meaningful way, for quick delivery of insight to support decision making or convey a message.

It involves making best use of graphical means to reinforce the message and facilitate understanding of insight.

With technological advances that make it easier to routinely collect enormous amounts of data, there is an ever increasing need to understand large volumes of information at once.

As Internal Auditors we need to find ways to communicate to garner greater business support and help the business transform and better manage risk.

Data Visualization

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Internal Audit and Technology Sustainable Analytics Audit and Technology Sustainable Analytics Neil...

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