artificial intelligence/ machine learning (ai/ml)...marketing tax supply chain spend analytics...

Artificial Intelligence/

Machine Learning (AI/ML)

June 6, 2019

© 2019 Crowe LLP 4

Sensitivity: Confidential

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© 2019 Crowe LLP 5


Why have a Data Science BU and CDSO?

“CDSOs (and their team of data scientists) are key to the skill set

needed to apply analytics to their business, explain how to use data to

create a competitive advantage and surpass competitors and

understand how to find true value from data by acting on it.”

- CMS Wire, September 12, 2016

© 2019 Crowe LLP 7


What is AI/MLMachine Learning Build

Inputs Outputs

Program/Rules

“Map”

Data

Answer

(Results)

Machine Learning Use

Inputs Outputs

Program/Rules

“Map”

Data

Answer

(Results)

Software Engineering Build and Use

Inputs Outputs

Program/Rules

“Map”

Human knowledgeAnswer

(Results)

© 2019 Crowe LLP 8


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© 2019 Crowe LLP 9


AI/ML ≠ Software Development

Data Scientist Software Engineer

Education Graduate Degrees in quantitative

fields, often multiple; PhDs

Undergraduate Degree

Tools Open Source languages and tools (R,

Python, C++, Docker, Kubernetes,

etc.)

SQL, Javascript, C/C#/Java, etc.

Hardware HPC Cluster, Unix-based OS.

• Rerouted power lines in Indy office

for ~$100k of hardware for ML work

Standard Laptops

End Product ML Model called through an API to

integrate into an application

Application

Driven By Data End-User Needs

© 2019 Crowe LLP 10


“Brains” to “Hands”…

“Brains”

• Human knowledge

• Intellectual property

• Artificial intelligence

“Hands”

• Humans

• Robotic process

automation (RPA)

• Custom application

developments

RPA

System based on rules

• Filling in web forms

• Copying data from one

form to another

• Easily create a way to

automate repetitive tasks

AI/ML

System based on data

• Learns from historical

actions

• Doesn’t need human

understanding of system



AI/ML, Software Development, and RPA

Daily Data

Database

Ta

sks

Ta

sks

Ta

sks

Ta

sks

MLWeb

Interface

Prioritize Work List in

Client’s System

Key

Software

EngineeringAI/ML RPA



Risks

Tay was an artificial intelligence chatter bot that was

originally released by Microsoft Corporation via Twitter on

March 23, 2016; it caused subsequent controversy when the

bot began to post inflammatory and offensive tweets through

its Twitter account, forcing Microsoft to shut down the

service only 16 hours after its launch. – Wiki

A few headlines:

Microsoft is deleting its AI chatbot's incredibly racist tweets – Business Insider

Facebook and YouTube should have learned from Microsoft's racist chatbot – CNBC

Tay: Microsoft issues apology over racist chatbot fiasco – BBC

Racist, Sexist AI Could Be A Bigger Problem Than Lost Jobs – Forbes

Microsoft’s chatbot gone bad, Tay, makes MIT’s annual list of biggest technology fails – Geekwire



What’s in it for you?

“If You Don’t Like Change, You’re Going to

Hate Extinction”

Potential for dramatic increases in profitability

and growth

Ability to better focus on strengths and value-

added activities for our clients



1515

Crowe Tax Journey



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The Need for Organization

• Funds focused on the biggest & best bets

• Tax Innovation Council & MP Votes

• Project Management Resources

• Feasibility/Opportunity Analysis

• Desired Launch Date

• Data – How Much; Where is it; Structure

• Complexity & Time Frame

• Return on Investment – Revenue/Efficiencies

• BU Strategic Initiative



Operate to innovate

An emerging branch of technology enabling rapid business process automation through the use of disparate data sources, Robotic Software Agents, and Artificial Intelligence.

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62% GrowthIntelligent automation initiatives will experience 62% growth in 2019 and beyond while focusing on: • Efficiency gains• Personalized insights• Automated processes

$14 billionmarket size (Markets and Markets)

Intelligent Automation to continue growth and estimated to be $14 billion by 2023:• Operational efficiency• Improved customer experience• Business process optimizations

Cross industriesOrganizations across all industries are implementing Intelligent Automation across all functions to increase revenue and improve efficiency –examples include:• Finance and Tax• Compliance• Operations



Operate to innovate

Intelligent Automation provides measurable benefits to employees, customers, and the bottom line.

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Soft benefits

Time SavingsProcesses that require several days of manual labor can be completed in minutes

Cost Savings

Tasks completed using pre-defined rules and artificial intelligence eliminate manual error

Reduce the cost of manual labor, human error, and slow processing

Higher Accuracy

Superior Customer Service

Improved Employee Satisfaction

Increased Strategic Activity

With robotics handling the volume of basic queries, staff can focus on resolving complex issues quickly

Employees welcome new technologies that lighten their workload and allow them to perform more valuable work

Free your resources up to do more strategic value-add activity that have real impact on your organization

Hard benefits



The intelligent automation spectrum

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New and Emerging

Technologies

5 Low Code Application PlatformsSolutions created through graphical user interfaces and configuration instead of programming

3 Data Analytics and VisualizationPatterns and visual representation from complex data sets

2 Robotic Process AutomationProcess Automation through the User Interface

1 Intelligent Character RecognitionMachine Learning enhanced character recognition

4 Predictive Analytics and Machine LearningPatterns and visual representation from complex data sets

Natural Processing LanguageAbility to understand, interpret human language

6



Intelligent automation by industry and function

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Procurement

Compliance

Finance & IT

R & D

HRSales &

Marketing

TaxSupply chain

Spend Analytics

Contract Compliance

Leasing

Accts. Payable / Receivable

RevenueRecognition

Recruitment

Onboarding

Churn Analytics

Data Retrieval

RegulatorySubmissions

Fraud Analytics

Internal Audit

Customer Svc. Mgmt.

Product Recommend.

Logistics

Spend AnalyticsDemand Mgmt.

Sales & Use Tax

Property Tax

Tax Provision

Intelligent Automation



© 2017 Grant Thornton LLP | All rights reserved | U.S. member firm of Grant Thornton International Ltd

Intelligent automation service offerings

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Automation assessment and business case

• Assess and identify IA opportunities across the organization including complexity and feasibility analysis

• Determine return on investment and define value proposition

Technology Strategy andvendor selection

• Evolve / Establish portfolio management and solution prioritization framework

• Conduct vendor evaluations ranging from focused use-case-centric to enterprise-wide

IA as a service

• Operate and maintain existing IA solutions

• Provide support, maintenance, and break-fix monitoring

• Execute the full development lifecycle –design to implement

IA technology delivery

• Design, build, test and deploy solutions

• Integrate solutions with existing business processes and technologies

• Perform stability testing and transition to operations team

QA / Audit services

• Establish Controls frameworks for Risk and Internal Audit

• Intelligent Automation internal controls monitoring as-a-service

IA governance and change management

• Establish or evolve your Center of Excellence capabilities with leading practices

• Establish performance and change management framework for deployed solutions



Case studiesIntelligent automation in practice

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A large medical center had thousands of procedures relating to their ERP, EMR, Intranet and SharePoint Systems. Finding the correct procedure was challenging and extremely time consuming. Grant Thornton digitized thousands of documents into one Cognitive Computing platform that used Natural Language Processing and Machine Learning to simplify and expedite the correct procedural identification.

A manufacturing company had experienced significant growth through acquisitions that resulted in multiple disparate systems. Grant Thornton reviewed processes within the Procure to Pay, Order to Cash, Record to Report and Non-Transactional functional areas and identified initial opportunities to automate in 60% of the processes. The RPA implementation increased efficiency, standardized processes, and resulted in a three year ROI of approximately 200%.

A midsize financial institution was facing a reduction in revenue due to rising resource costs and increase in low cost competitors. The organization invested in BPM and OCR tools to automate their loan transaction processing. The automation allowed the organization to process over 50,000 transactions a day, lowering cost per transaction and rates for customers.

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