Post on 19-Aug-2020
How Digital Transformation changes the perspective of an IIA
21 November 2019
Giridhar LS
GIRIDHAR LS Key Experiences
8 years plus of audit experience and 15 years plus of IT consultingexperience
Lead the data Extraction, Transformation and Loading (ETL) acrossMENA
Executed / managed Information Systems Audit of major clients(Banks, Insurance and multinationals) with complex IT environment
Lead MENA innovative projects in the areas of RPA and customanalytics in the audit practice.
Managed various assignments relating to ERP reviews, applicationcontrols, SAS 70 / SSAE16 reviews, IT due diligence and fraudanalytics
Qualifications / Certifications
▪ B.Com▪ Chartered Accountant ▪ ISO 27001 Certified Lead Auditor▪ Certified information Systems Auditor (CISA)▪ Certified risk in information systems and controls (CRISC)▪ RPA UiPath Level 3 Advanced Training Diploma
▪ IMT on Artificial Intelligence and other disruptive technologies
▪ 19 Annual Regional conference in IIA
▪ SEWA Banking conference
▪ ICAI Dubai Chapter
▪ ICAI Abu Dhabi Chapter
▪ Association of National Accountants of Nigeria
Speaker in last 6 months
About me
2
What I will be covering
3
▪ Changing dynamics of an IA function
▪ Why is it important?
▪ Current Challenges for an IA
▪ Understand ML, Analytics and RPA
▪ What can an IA do differently
▪ RPA Audit Considerations
Changing dynamics of an IA function
GOVERNANCE
• Strategic insight aligned
with organization’s
expectations
• Resourcing with
technology & Audit
experience
FUTURE TECHNOLOGIES
• Intelligent automation / RPA
• Artificial Intelligence
• ML driven analytics
APPROACH• Continuous reporting to key stakeholders
• Dynamic auditing
Why is it important?
▪ Stakeholders expectations: Maximizing the use of technology to coverthe population without compromising quality
▪ Peer Pressure: Competitors continue to do more with less resources withthe deployment of technology
▪ Business Partner: Right insights help stakeholders see the key risks thatwill help them make informed decisions
▪ Changing technology landscape: Requirement of IA to be well versedwith better and faster ways to achieve the results
▪ Regulatory Expectations: Requirement of IA to be able to quantify therisk across the population to evaluate the impact under different scenarios
Current Challenges for an IA
Excel predominantly used even in scenarios where there are sophisticated systems in place
Systems not sophisticated enough to provide the right data for analysis
Advanced technology used like machine learning, blockchain etc that are very technology driven
Traditional auditors lack the skillset to do a deep dive using future technologies
Investments in future technologies
Executive Summary of Future of Financial Reporting Survey
50%
POSSIBLE ROOT CAUSE
Sophisticated ERP / systems used in a basic manner and reports are manually created
Datawarehouse stores limited data points
Data from too many systems are they are not integrated
Reporting very manually driven
Multiple sources of truth
SOURCE INPUTS
Responses from 977 international senior finance professionals with 81% from senior roles
23 different industries
Around 14% from the Middle East
Statistics
75% of CFOs are yet to make the move to real-time reporting in the board room.
69% of CFOs rely on spreadsheets to plaster over their reporting process
50% worry that all documents and disclosures have not been updated with latest changes to accounts
40% of respondents were unable to agree that their data is always trustworthy and accurate.
71% of respondents depend on spreadsheets for collecting data across the majority of their business units..
50% of respondents said reporting involved huge amounts of manual checking every time a change is made
40% of boardrooms do not have a complete view of the business.
60% of respondents said they spend too much time cleaning and manipulating data
25% of organizations have reduced their finance headcount over the last three years.
Source: Insights from the FSN Modern Finance Forum on LinkedIn Survey on “Future of Financial Reporting” towards end of 2017
AI & Machine Learning
8
9
ML refresher
Types of Analytics
Deployed across industries
Deployed across data driven industries
Deployed across tech / internet companies
ML Types
Idea of input data / classification and know what to expect but need output on new data sets
Do not know how to classify the data and you want the algorithm to classify the data for you
Have a lot of data but interaction required to reach an objective
Deep Learning
Deep Learning Types
Example ML
Additional searches possible
Analytics
11
12
Analytics and IA
Possibilities
Population Coverage
Possibility of continuous auditing
Reduced timelines and focus on more areas simultaneously
Help to achieve more in the limited budget
Integration with other trends like RPA
Analytics touchpoints
Scripting for repeatability and scalability
Visualizations provides a birds eye view of the potential risk
Significantly reduces audit timelines
Integrating various other data points into the main data like ERP
Helps to make this process autonomous
New risks through discovery
Data Collation
13
Analytics Key Concepts
Different data formats / systems
Limited data dimensions from ERP / accounting systems
Lack of integration to real time happenings i.e. economic index etcMany FTE’s involved i.e. MIS, IT etcERP data usually downloaded in excel and analysis happens from there
Individualistic approach to data i.e. Lack of complete perception
Coping with data bias
Datapredictability
CHALLENGES from data sideTraditional Using Analytics
Risk Assessment
• Understanding obtained at high level
• Interviews drive the approach
• Insights drive the interviews
• Time can then be spent on high risk areas
ControlTesting
• Sample based testing
• Review is limited to the known
• Analyze total population andreview the outliners
• Identify patterns that do not figure out in a traditional testing
Repeatability
• Heavy effort required from execution to reporting
• With RPA and analytics, this can be generated on the fly
▪ Developing an approach or model
▪ Acquiring the right skills on analytics
▪ Selecting the right tools andtechnologies
CHALLENGES for an IA
Case Study Demo
Robotic Process Automation (RPA) / Intelligent AutomationKey Concepts Refresher
15
RPA – Key Concepts in a video
Source: Softmotive Robotic Process Automation from YouTube
ROBOTS making a better place for humans
My Inspiration as a kidQuick Facts
Year 1985TV serial Small WonderROBOT Android RobotAGE 10 years oldName V.I.C.I. (Voice Input Child Identicant)
ROBOTIC PROCESS AUTOMATION / INTELLIGENT AUTOMATIONKEY CONCEPTS IN A NUTSHELL
CRITERIA
• Decision based – Rule based vs
Decision based
• Data source – Unstructured vs
Structured
• Data Type – Image vs Number
• Stability – Frequent releases vs
Few releases
• Complexity – Simple vs
Complex
• Standardization – High vs Low
• Risk – High criticality vs Low
criticality
ACCURACYThe right result, decision
or calculation the first
time.
AUDIT TRAILFully maintained logs
essential for compliance.
RELIABILITYNo sick days, services are
provided 24/7 and 365
days a year.
OFFSHORINGGeographical
independence without
business case impact.
PRODUCTIVITYFreed up human resources
for higher value-added
tasks.
SCALABILITYInstant ramp up/down to
match demand peaks
and troughs.
RETENTIONShifts towards more
stimulating tasks.
CONSISTENCYIdentical processes and
tasks, eliminating output
variations.
LOW RISKNon-invasive technology
RPA can be overlaid on existing
systems, allowing creation of a
platform compatible with
ongoing developments in
sophisticated algorithms and
machine-learning tools.
19
What can an IA do differently
2. Process modifications
Asses the impact of new risks to be introduced
through digital transformations.
Consider the effect of digital transformation on
process, controls, and reliability and accuracy of
data.
1. Effective challenge of digital transformation
Involvement in the digital transformation strategy to assess
impacts on the internal audit plan,
Advise the organization through appropriate risk and control
decisions.
Determine the balance for challenge of new
technologies vs. implementations / controls
New technologies
challenge processes
Continue to have a seat at the table at key forums
Develop a plan for the audit period
We suggest that internal audit organizations continue to be actively involved and have a seat at the table. Digital transformation has the opportunity to provide extensive
value to the firm, and the risk and control experience of internal audit can help highlight the enabling technology and its potential impacts & considerations.
3. Impact to existing audit strategy
Evaluate testing strategy modifications, affect
availability and collection of audit evidence,
Corporate Social Responsibility
“It’s not a faith in technology, It’s faith in people.” -Steve Jobs
Digital Innovation has advanced more in the last 30 years than in the last 2000. And it’sbuilt to continue. I believe that once process efficiency is attained through RPA, theorganisation can spend a lot more time on their greatest asset, people. A globalreimagining of jobs of the future will become a mandate. And, the most important taskon hand is to create something technology can’t – a human culture.
CONTACT US:
+971504146718
www.robotechsolutions.ae
Giridhar.ls@robotechsolutions.ae
Question me about…
• How to identify which processes requireautomation?
• How to implement automation solutions?• What aspects to consider in an RPA cost
benefit analysis?• What is the RPA decision making process?• What aspects to present in Board
Proposals to aid decision making for RPA?