Track 1 - 1.30pm to 2.30pm (Achieving Automation through Cognitive Technologies)

1. Achieving Automation
through Cognitive
Technologies
Timothy Ho
Deloitte

2. Technology is the key driver of change in
finance

3. Cloud Process Visualization
Robotics
Cognitive
Computing
In-Memory
Computing
BlockchainAdvanced Analytics
Seven technologies have growing relevance
for how the work of finance gets done.
Core Modernization
Exponentials

4. Finance is expected to deliver in four key roles,
however the balance of responsibilities is changing
Operator
StrategistCatalyst
Steward
How much time (in %)
is your finance
organization spending
in top half vs lower
half?

5. Definition : Automation Spectrum

6. The future of operational Finance is the
establishment of a Finance factory; a fully automated
control center with process visualizations tools
Monitoring of processes on a
continuous basis to provide
insight
Process Automation to drive
greater productivity and quality

7. Robotic Process Automation (RPA)
Opening email and
attachments
Logging into web/
enterprise applications
Moving files and folders
Copying and pasting
Filling in forms
Reading and writing to databases
Making calculations
Scraping data
from the web
Connecting to
system APIs
Extracting structured data from
documents
Collecting social media statistics
Following “if/then” decisions/rules
RPA is… RPA is not…
Computer-coded software
Programs that replace humans
performing repetitive rules-based
tasks
Cross-functional and cross-
application macros
Walking, talking auto-bots
Physically existing machines
processing paper
Artificial intelligence or voice recognition
and reply software
What itcan do

8. RPA Demo Video
Process automation - generate billing in the
system
Process steps:
1. Receive email with attachment (in pdf – standard
format)
2. Convert data into an excel file – Copy and paste
from pdf
3. Log in to system
4. Go to generate billing screen and input billing
request – Copy and paste from excel file
5. Send email to requestor to confirm process is
completed
Video Link: https://youtu.be/FV8lM9SIFQ8

9. RPA Benefits

10. Risk Analytics – Deloitte Analytics Platform
Use more data, quickly
• Unleash enterprise data, including
internal and 3rd Party sources
• Quickly cleanse and map data for
analysis
• Enhance data quality and
completeness
Produce better insights
• Leverage proven risk models across
business processes Procure-to-Pay,
Payroll, Travel & Expense, and P-Cards
• Identify emerging patterns driving
anomalous behaviors through trending
and benchmarking
• Aggregate risk and use historical results
to reduce false positives
Understand business
impact
• Easy-to-use dashboards enable users to
investigate and report results
• Review historical results of similar risks
identified to predict potential
outcomes
Analytics
Platform
Understand the risk universe
• Deliver predictive risk modeling and risk
sensing capabilities
Develop the audit plan
• Perform dynamic risk assessments
• Generate dynamic audit plans
Design the audit programs
• Continuously audit / monitor risk & controls
• Enable remote auditing
• Conduct exception-based audits
Deliver results & insights
• Automated advanced dashboards

11. Sample Risk Analytics

12. “Weare drowning in
information but starvedfor
knowledge”- JohnNaisbitt1

13. What is analytics?
Predictive modeling/
optimization
Scenario/tradeoff simulation
Pushed exceptions and alerts
Company and individual performance
visibility
Operational reporting
Hindsight
Enterprise data management
Foresight
Insight
Industrialized
Dashboards
and KPIs
Bespoke
Traditional
Analytics
Cognitive
Computing and
Machine
Learning at
Scale

14. Analytics is evolving
Drivers & disruptors Evolution of analytics
IN-MEMORY
PROCESSING
INTERNET
OF THINGS
INTELLIGENT
AGENTS
TEXT
ANALYTICS MACHINE LEARNING
CROWD-SOURCING
& COMPETITIONS
ADVANCED HUMAN
COMPUTER INTERFACE
EXPONENTIALS
CYBER
SECURITY
ARTIFICIAL INTELLIGENCE
& COGNITIVE ANALYTICS
CLOUD VISUALIZATIONS DATA LAKES BIG DATA &
PREDICTIVE
ANALYTICS
TABLE STAKES
Data
proliferation
New data
sources
Technology
disruption
Innovative
Science
DATA
WAREHOUSING
& DATA BUSINESS
MODELING INTELLIGENCE
LEVELOFENTERPRISE-WIDEADOPTION

15. Data Extraction - Argus
Argus

16. CognitiveSpend retains human intelligence to
get smarter as more data is processed
How the Tool Learns
Feedback Portal
Dynamic in-tool pivot table to capture human input
Initial
Training Data
Initial
Classification
Additional
Feedback
Previous feedback from other projects
totaling ~$50B of spend across 100M
line items
250 most meaningful line items
(identified using data science) classified
by user to jumpstart classification
Additional amendments by user are
retained for learning purposes
+
+
How the Tool Classifies
CognitiveSpend leverages previous
classifications to predict
classifications for data it has never
seen before
Example Classification
Line Item Description:
“SEM”
Rules-Based
Unknown
Cognitive
Search Engine
Marketing
95%+=Accuracy
through
Automation

17. Analytics
Cognitive
Insights
Statistical
Modelling
Visualization

18. Cognitive Insights
➢ Extract concepts and
relationships from various data
streams, text sources and social
media and generate new insights
including market threats and
opportunities through cognitive
analysis and correlation of data
➢ Deliver applications that
intelligently “understand” the
context and provide the right
insight at the right time
explaining why it is relevant and
important

19. Statistical Modelling
$0
$50
$100
$250
$200
$150
$300
$350
Revenue(millions)
2008 2009 2010 2011 2012 2013 2014 2015 2016
Year
$0
$50
$100
$150
$200
$250
$300
$350
Revenue(millions)
2008 2009 2010 2011 2012 2013 2014 2015 2016
Year
Traditional Approach: Linear Projection Predictive Approach: Multiple Linear Regression
Forecast Forecast
Year 08 09 10 11 12 13 14 15 16
Revenue
$150 $155 $202 $193 $210 $280 $293 $311 $336
Year 08 09 10 11 12 13 14 15 16
Revenue
$150 $155 $202 $193 $210 $280 $293 $266 $254
Var A* 2 3 5 4 6 7 8 2 3
Var B* 7 6 5 6 4 4 3 4 5
Var C* 1 1 4 5 3 7 8 5 7
R2 = .95
Standard error = 16.42
R2 = .99
Standard error = 3.52
Outcome for two different forecasting approaches
•1 More accurate model,
illustrated by the higher R2
and lower standard error
•2 Can highlight problems
based on nuanced changes
before they have a negative
impact on the company
•3 Allows executives to see
which drivers have the
greatest impact on revenue
forecasts
•4 Enables better and quicker
decision-making in order to
take action and enhance
future performance

20. Visualization
Visualization
• Multi Dimensional
reporting, and ability to
drill down to details
• Real time information
• Dashboard for
management

21. Natural Language Generation
Data Audience
ANALYZE INFER GENERATE
INSIGHTS
Natural Language Generation
Produces an analysis and text automatically
Generates standardized text from the same domain knowledge
base
Tailors the text to the user’s expertise level and context
Drives actionable insights, increases productivity, and
operational efficiency

22. Natural Language Generation LinktoYoutube

23. Integrating NLG with Robotics can
significantly automate Decision Support
activities, enabling a greater focus on analysis
Report
Submission
Data
Collection
Data
Manipulation
Insights
Generation
Commentary
Generation
Driver
Analysis
Report
Submission
Data
Collection
Data
Manipulation
Insights
Generation
Commentary
Generation
Driver
Analysis
Legend: Manual Process RPA Tool NLG Tool
Current
State
Desired
State
Illustrative Business Partnering support process

24. The CFO is the logical position to oversee predictive
analytics capabilities and to partner with the business

25. Getting Started
THINK BIG
Immerse Yourself in Innovation
Join an immersive experience
(e.g., Digital Finance Lab) to
explore the “art of the possible”
and determine a future state
vision, goals, and benefits
Build Your Ecosystem
Evolve your Finance organisation
by collaborating with other
business functions,, and vendors
ESTABLISH A DIGITAL LEADERSHIP TEAM
Identify a visionary program leader and assemble a team to accelerate your digital goals.
Determine a governance model and policies that might need to be adapted to execute
successful change management and ensure the solution is absorbed into the business.
START SMALL
Scaling the Edges
Disconnect from the core business
and set up a digital leadership
team to assess disruptive
opportunities within the
organisation
Pick One or Two Plays
Prioritise your desired tactics
and pick just one or two to get
started in order to establish
proof of concept
ACT FAST
Prove it Works (Quickly)
Use an agile, iterative piloting
approach to move from strategy to
prototyping as quickly as possible –
“fail fast” and achieve rapid results
Market Your Own Success
Seek opportunities to share digital
experiences with other functions –
knowledge share

26. Crunch Time Series
Crunch
Time:
Finance in a
Digital
World
Crunch
Time, too.
CFOs talk off
the record
about
Finance in a
digital world
Crunch Time
IV:
Blockchain
for Finance
– What CFOs
Need to
Know
Crunch Time
III: The
CFO’s guide
to cognitive
technology
Crunch Time
V: Finance
2025
Link toreports: https://www2.deloitte.com/sg/en/pages/finance-transformation/articles/finance-digital-
transformation-for-cfos.html

27. Contact : kwho@deloitte.com
Contact Details