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Applied IntelligenceRESPONSIBLEAITRANSFORMATION
Copyright © 2019 Accenture All rights reserved. 2
Copyright © 2019 Accenture All rights reserved. 3
Improving the Way the World Works and Lives
Source: https://www.un.org/sustainabledevelopment/sustainable-development-goals/
https://www.un.org/sustainabledevelopment/sustainable-development-goals/
Copyright © 2019 Accenture All rights reserved. 4
What is Applied Intelligence?
Applied Intelligence is how Accenture uses Artificial Intelligence (AI), automation, and analytics to reimagine business—enabling our clients to do things differently and do different things…
It's about embedding intelligence at the core of business to drive transformative outcomes. We help businesses power their ambitions with our blueprint for success, a human-centric, data-led, technology-driven approach.
AUTOMATION
+
ANALYTICS
+
ARTIFICIAL
INTELLIGENCE
It's our unique approach to combining AI with data, analytics and automation under a bold strategic vision to transform your business—not in silos, but across every function and every process, at scale.
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3 AI Myths
Robots are coming for us
Machines will take our jobs
Current approaches will still apply
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AI-Powered Virtual Workforce
What could you achievewith an infinite workforce?
What if you couldaugment every employee?
An AI-powered, cloud-based virtual workforce is able to emulate many types of human worker activities, that complements the human workforce by automating high-volume complex* repetitive tasks, augmenting decision-making with collective experience and data insight, and scaling new, disruptive business services.
* Involving semi-structured or unstructured content, interactions, judgement calls
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With AI, we can Reimagine BusinessDoing Things Differently and Doing Different Things
INTELLIGENT
AUTOMATIONCreates growth through a set of features enhancing traditional automation solutions.
▪ Ability to automate complex physical world tasks that require adaptability and agility
▪ Ability to learn by experience and improve, enabled by repeatability at scale
LABOR & CAPITAL
AUGMENTATIONGrowth will come from enabling resources to be used much more effectively and valuably
▪ Enable humans to focus on parts of their role that add the most value
▪ Improve capital efficiency—a crucial factor in Industries where it represents a large sunk cost
INNOVATIONDIFFUSION
Ability to propel innovations as AI diffuses through the economy.
▪ Innovation begets innovation, the potential impact of an AI solution expands to new products/industries
▪ Opens new business models and opportunities
Copyright © 2019 Accenture All rights reserved. 8
Case Study: International Oil CompanyAutomation of Managed Services Operations
Opportunity
Accenture is providing a managed service to the client in several areas. A cross service area team has been established to introduce RPA and bring automation benefits. A sample of the target use-cases are:➢ User access management ticket Approval Attachment
➢ SharePoint Site Monitoring
➢ System Health Checks
➢ EAM Rouge Account Checks
➢ EAM Ticket Creation
➢ Trading Checklist Attachment
Solution
Solution delivered using Accenture Robotics Platform in a combination of standalone mode and distributed mode.✓ Hosted partly on cloud based solution, partly on premise and partly side-by-side of human
agents.✓ Integration with email system
Results
20 FTE Realized Benefits
30 FTE Projected Benefits
57% Reduction monitoring effort
80% Reduction in average ticket creation time
81 Use cases in production, 61 in pipeline
Processes Automated
Sample Use-Case: Monitoring
Managed Services
Engineering Finance & HR Trading
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MAJOR INSURANCE COMPANY
Classification of emails with high precision requirements
Client required classification of incoming customer emails and letters in 3 different languages. Because of far-reaching consequences in case of error, the client required a precision of 98%. The model was trained on more than 100,000 emails. Language was detected, and OCR was applied on the email’s attachments. This enables automatic classification of 4 million emails and 2 million letters each year, with high accuracy.
• 3 DIFFERENT LANGUAGES WITH AUTOMATIC LANGUAGE DETECTION
• ACCURACY OF 98%+• OVER 6 MILLION MESSAGES CAN BE
PROCESSED EACH YEAR
Copyright © 2019 Accenture All rights reserved. 10
Case Study: Major Technology Company
Automate case processing with machine-learning based text analytics and AI-powered robotics
Client has outsourced the handling of all their globalpayroll requests to Accenture. AI is leveraged to automateservice desk processes.
• 65’000 TICKETS ANNUALLY• 100 COUNTRIES• 4 DELIVERY CENTERS• 5 DIFFERENT LANGUAGES • 3 HIERARCHIES OF CATEGORIZATION• UP TO 53 CATEGORIES PER HIERARCHY
• AUTO-FILL FORM AND AUTO-RESPOND• 93% ACCURACY AT 95% AUTOMATION
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SVA – AUSTRIAN SOCIAL SECURITY
Classification of scanned letters
For this client, 500,000 letters are categorized manuallyeach year. The letters are scanned into PDFs, and with OCRthe corresponding text is extracted. This text is classifiedinto one of 56 categories. Based on this categorization,further processing is carried out by the responsibleemployees.
• 500,000 LETTERS
• AUTOMATED TEXT CLASSIFICATION
• AVERAGE ACCURACIES OF 83%
Copyright © 2019 Accenture All rights reserved. 12
International Shipping CompanyTrade compliance validation
Opportunity
The automation program (circa 800 FTEs) runs under a number of compliance requirements, one of which is for the Export Control process automation to guarantee adherence to the US laws. Given the scale of the target deployment the existing COTS products become prohibitive from cost perspective and lack the flexibility of constantly monitoring the desktop screens for patterns.
Solution
The Accenture Robotics Platform has been configured to monitor the operations through amainframe terminal. The robot would detect if an agent enters or copies/pastes consignment numberand validated them through call to a dedicated web service. In addition the robot would detect thedestination and origin countries that are under trade embargo and alert the agent through adedicated notification mechanism not to process the corresponding consignments.
Results
70% increased compliance
Reduced time taken for validation process
Processes Automated
Compliance
Export Control
Copyright © 2019 Accenture All rights reserved. 13
Uncovered OVER€6 MILLION in tax revenues
OVER 90% ACCURACY spotting undocumented changes
AUTOMATIONof annual surveys
We helped a European land registry build a proof of concept to show how deep learning could help their surveyors transform the laborious process of updating land records. By applying advanced deep learning algorithms to satellite imagery, we were able to train a model capable of alerting surveyors to undocumented changes with over 90% accuracy—in close to real time. In a single pilot study it uncovered over 16 extensions and over 22 structures the authorities knew nothing about—amounting to over €6 million in uncharged land tax.
DEEP LEARNING PROVES IT’S THE SMART WAY TO SEE HOW THE LAND LIES
EUROPEAN LAND REGISTRY
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Step 1Claim received
Corporate client or individual member fills out a web form to request claim
Step 3Auto-request information
Letters automatically sent to NAV and doctor for relevant cases, then scanned
Step 5Automatic evaluation
Text analytics trained on historic data evaluates the cases
Step 2Automatic pre-evaluation
Segment the cases and automatically send them to the right next step
Step 4Automatic understandingPhysical responses are converted to
structured data with computer vision
Step 6Automatic fraud check
Machine learning checks for fraud; if flagged, case handler takes over
Step 7Auto-process (most) claims
Approve or reject the claim automatically or manual processing by case handler
Rule Engine &
Machine Learning
Optical Character
RecognitionText Analytics Machine Learning
Easy cases
• Does not require additional information
Medium cases
• Requires additional information, but can be solved automatically
Complex cases
• Must be solved manually, but received information is digitalized
Fully automated processing
Automatic processing or given to case handler with decision making support
Manual processing by case handler, but with decision making support
Fast-tracked
Goes through each step or is fast-tracked
Goes through each step
RPA
Case Study: AI-Based Automation of Insurance Claims
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Raising your AI Solutions to be Responsible Citizens
Accountability
PROCEEDRESPONSIBLYBUILDTRUST
5 Key Principles
Honesty
Transparency
Fairness
Supportive ofpeople andsociety
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Articulating the Right Business CaseShifting Operational Spend towards Strategic Initiatives
Reduce costs
Increase outcomes
Elevate jobs
Create new value
Use automation tofuel growth by reinvesting savingsinto the workforce
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Think 10x, not 10%
Further light reading: ‘Accenture: How automation, augmentation and innovation will mean success in AI initiatives’https://www.artificialintelligence-news.com/
https://www.artificialintelligence-news.com/