Advanced Analytics in Internal Audit and Compliance

April, 23 2014

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Today’s Discussion

Key Trends in Risk Analytics Today

Trends we are seeing in the market, and defining the value proposition for Advanced Analytics in Internal Audit and Compliance

Analytics in Action

Retail case study and live demonstration of analytics through data visualization

Implementing a Successful Program

Key success factors to develop and sustain a data analytics program

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Key Trends in Risk Analytics Today

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Characteristics of analytics today

Visualization

Dashboarding

Trending & comparisons

Data

Financial, Operational

Structured, Unstructured,

Internal, External

Analytics; discovery and communication of meaningful patterns in data

Big data; collection of large and complex data sets

Speed and portability; available anytime, anywhere

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Major themes we’re seeing at our most successful clients

Data Connectivity

Direct access into enterprise-level data resources

Balanced Talent Mix Strong analytics capability at the core, with training for audit, shared service and business users

Self Service Capabilities w/ Visualization

Approachable and intuitive technology that can be used by the business

Collaboration

Integrated working environment with analysts and business stakeholders

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Quantifiable but not Always Tracked to Amounts:

• Improve operational

effectiveness • Reduce regulatory and

compliance risk exposure

• New policies and procedures enacted

Value Proposition

Qualitative: • Higher quality management

conversations • Risk focused testing • Visual focus on trends and

outliers • Adoption of analytics by

business users • Strengthened relationships

Quantifiable: • Reduce costs • Increase

revenue/profitability • Reduced BI

development cost by leveraging data visualization tools

• Reduced hours (for internal audit)

1. Increase risk coverage, quality, and business impact

2. Greater efficiency through ‘right time’ analytics

3. Better understanding of the business through analytics

4. Cultivate business relationships and drive deeper discussion on issues and opportunities

What are the benefits?

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Analytics in Action

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Case Study: Internal Audit Data Analytics – Retail Pricing Audit

Client Challenges Action Value Delivered

• A large retailer needed to

assess key risks and controls related to product pricing.

• Internal Audit incorporated the

use of data analytics into each phase of the audit life cycle.

• Gained an understanding of

potential anomalies and trends related to pricing.

• Identified key risk indicators (KRI)

• Developed targeted analytics around those KRIs that would identify potential exceptions.

• Developed dashboard’s to interact with the data and ‘audit by sight”

• Enabled Internal Audit to approach

audit of pricing process using a risk based approach, focused on risk indicators within the data.

• Collaboration with the business enabled by visual analytics

• Identified potential issues and

trends relating to pricing that were not initially apparent at the onset of the audit.

• Positively impacted perception of

Internal Audit by the business.

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Auditing Approach Leveraging Data Analytics

Business Development

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5

4

2

3

Foundation

Fieldwork

Quality

Reporting Planning

1. Foundation: Leverage data to identify key risks to be addressed through the Audit Plan

2. Planning: Plan and scope the audit to focus on high risk areas and newly identified risks

3. Fieldwork: Develop risk based and value added analytics for the audit

4. Reporting: Analyze results to quantify impact, and report findings utilizing data visualization

5. Quality: Monitor managements responses through Dashboards

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Issue

Action

I. Foundation: Risk Assessment

Annual quarter over quarter revenue decline

Analyze financial data to gain insight over declines in net revenue.

Internal audit identified product pricing as a key risk area

Impact Analyze key financial data and adjust their audit plan to address their high risk areas.

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Issue

Action

II. Planning: Project Risk Assessment

Varying gross margins across 3 retail channels

Utilized data visualization software to analyze the stores by retail channel.

Impact Identified limited controls around product price overrides/adjustments have been identified

Unexpected spikes in price overrides

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Issue

Action

II. Planning: Audit Scoping

Identify high risk stores affecting gross profit through the use of overrides

Utilized data visualization software to analyze the total price override amounts against gross profit to identify outliers and anomalies

Impact Identified stores that had negative gross profits or negative overrides Discovered that products can have price overrides that result in losses

Negative gross profit due to price

overrides

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III. Fieldwork: Targeted Analytics Testing

Instances where the override amount is less than the cost of the item.

Total amount and frequency of overrides by store and sales associate.

Total amount and frequency of overrides by override code.

Trending of overrides by store over the audit time period.

Override reason codes leading to negative gross

profit

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IV. Reporting: Confirm and Report Results

Internal Audit team determined there were no controls around overrides of product prices

Sales associates overriding to negative gross profit

Sales associates entering in negative override

amounts

Outlier of sales associate with potential unusual

activity

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Gross Profit vs. Override Amount by Sales associate

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Issue

Action

V. Quality: Remediation Follow Up

Monitor managements response to the findings of the pricing audit

Utilized data visualization software to leverage the analytics and dashboards created during the assessment, scoping, and testing phases

Impact Ability to continuously monitor the compliance in a consistent manner with minimal manual effort

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Implementing a Successful Program

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Core components of a data analytics strategy

There are five core components to consider when developing a data analytics strategy

• Consistent • Sustainable • Efficient

• Financial, Operational • Structured, Unstructured • Internal, External

Change

People

Data

Process Infrastructure & Tools

Business Value

• Ownership • Accountability • Talent Development

• Maintainable • Intuitive • Adaptable

• Collaborative • Timely • Relevant

Vision Acceptance

Mandate Funding

Relationships

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Measure your success

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Audit and business impact

Data

An

aly

tics

Ma

turi

ty

Low

High

Level 0

Initial / Developing

Level 1

Relevant

Level 2

Consistent

Level 3

Integrated

Level 4

Embedded

Level 5

Transformational

• Limited but growing

capabilities

• Ad hoc activities

resulting in

unpredictable and

inefficient

performance

• Success based on

individual

competence

• Capabilities

developed and

adopted

• Capabilities used to

drive audits

• Defined goals and

standardized

processes and tools

• Capabilities are well

developed and

practiced with

appropriate

governance

• Data sources are

readily available

• Activities begin to

become repeatable

and key metrics are

developed

• Core analytics

skillsets within 5-

10% of department

• Scale is achieved for

department specific

teams

• Improvement

methodologies are

implemented

• Monitoring occurring

for metrics and

controls

• Analytics risk models

being adopted by the

business

• Analytics changing

auditor behaviors

• New value

propositions

• Alignment to

consistent platform

that can be

leveraged across

lines of defense

• Game changing to

audit delivery and

value

• Capability limited

to very few

individuals

• Inconsistent

effectiveness

• Limited audit or

business value

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A phased approach

An iterative deployment methodology ensures stakeholder value is achieved and business needs are meet as conditions change

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Define a clear ,

strategic vision

Develop roadmap Execute pilot

Phased Roll- out

Assess solution

Analyze current/

future state

Refine & execute plan

Financial

• Expense reports

• pCard analytics

• P2P analytics

• Revenue financial controls

• Store risk and performance analytics

• Cost Allocation Re-performance

• FCPA/OFAC

• Country Risk Assessment

• Audit Planning

• Price Changes / overrides

• Inventory shrink analytics

• High risk product identification

• Trends by store, items, override category

• Supply Chain Movement ($ & Time)

• Inventory vs Sales

• Procurement / working capital analysis

Areas we commonly see client leveraging advanced data analytics…

Operational

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Key Considerations

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• Start small, think big, and evolve over time

• It’s not about the tool, it’s about capabilities

• Don’t underestimate the complexity of the data

• Analytics is an iterative process

• Need a strong analytics center

• Strong relationship and reputation are crucial

• Don’t underestimate change

• Stakeholder value can be enormous

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Thank You!

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