accenture robotics platform - our public service 2020
TRANSCRIPT
Applied Intelligence
Observations on the use of RPA
and AI in the Public Sector
Copyright © 2021 Accenture All rights reserved. 2
AI – CORE COMPONENTS
See
Computer Vision
Read
Natural Language Processing
Hear
Audio Processing
Make Connections
Graph Analysis
Decision Support
Analyse, Predict, Recommend
Physical Support
Robotics
SENSE COMPREHEND ACT LEARN
Structured decision making
Machine learning
Unstructured decision making
Deep learning
Automate
Robotic process automation
Applied Intelligence
Observations on the use of RPA
and AI in the Public Sector
Copyright © 2021 Accenture All rights reserved. 4
AI-Powered Virtual Workforce
What if a virtual workforce could
run part of your operations?
An AI-powered, virtual workforce, able to emulate many types of human worker
activities, can complement the human workforce by:
- automating high-volume complex* repetitive tasks,
- augmenting decision-making with collective experience and data insights,
- scaling new, innovative business services.
* Involving semi-structured or unstructured content, interactions, judgement calls
Copyright © 2021 Accenture All rights reserved. 55
DIALOGUE
Interact by using natural language
speech and text
Understand context and ask
follow-up questions
AI-Powered Bots have an Increasing Number of Human-Like Skills
INTEGRATE IN ENTERPRISE
OPERATIONS
Schedule and execute multiple
robots
Monitor performance and
escalations, provide full auditability
DISCOVER AND
AUTOMATE PROCESSES
Record, edit and replay processes
by having a robot interact with
applications’ graphical user
interfaces
Mimic human interactions
Applicable on any system
READ AND UNDERSTAND
CONTENT
Interpret the content of a
document, image or video
Group documents by category
Recognize text and visual
markings in content
Extract and validate key
informationROBOT
Copyright © 2021 Accenture All rights reserved. 6
SVA – AUSTRIAN
SOCIAL SECURITY
Classification of scanned letters
For this client, 500,000 letters are categorized
manually each year. The letters are scanned into
PDFs, and with OCR the corresponding text is
extracted. This text is classified into one of 56
categories. Based on this categorization, further
processing is carried out by the responsible
employees.
• 500,000 LETTERS
• AUTOMATED TEXT CLASSIFICATION
• AVERAGE ACCURACIES OF 83%
Copyright © 2021 Accenture All rights reserved. 7
MAJOR INSURANCE
COMPANY
Classification of emails with high
precision requirements
Client required classification of 4M annual incoming
customer emails 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
400,000 emails. Language was detected, and OCR
was applied on the email’s attachments. This enables
fully automatic classification of 4M emails each
year, with high accuracy.
• 3 DIFFERENT LANGUAGES WITH
AUTOMATIC LANGUAGE DETECTION
• ACCURACY OF 98%+
• 4 MILLION MESSAGES CAN BE
PROCESSED EACH YEAR
Copyright © 2021 Accenture All rights reserved. 8
Uncovered OVER€6 MILLION in tax revenues
OVER 90% ACCURACY
spotting undocumented changes
AUTOMATION
of 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
Clinical chart review solution overview
Multiple Data
Files & Formats
JPEG
PNG
Labs
XPS
PDFs
Claims
Auths
XPS
Medical Records
CCD-A
Optical Character
Recognition
Machine Learning
Platform
Converts unstructured
documents (e.g. PDFs, JPEG,
TXT, etc.) to a structured
format that computer
applications can read
Leverages admin & clinical
knowledge libraries with 1B
clinical combinations to
identify key words / phrases
such as names, diagnoses, etc.
A human reviews the
output, validates the
results, and creates
actions for operations
teams if necessary
Text Analytics &
Natural Language
Processing
Provides feedback loops to machine
learning to enhance the model based on
human validation
Interactive User
Interface1 2 3 4
Deduces the correct
answer and continually
adapts the algorithm based
on patterns of successes
and failures
Sense Comprehend Act
Learn
Copyright © 2021 Accenture All rights reserved. 10
Taking a Holistic Approach to Augment Employees
Center of Excellence
Automation
Strategy
Discovery Implementation Run
Change Management
Program Governance
Technology Innovation
Identifying right approach:
1. Have an organisation-wide strategy for AI. Don’t do it
piecemeal.
2. Think of the downstream impacts.
3. What benefits will be achieved?
4. What processes do I target to achieve maximum benefit?
5. Should those process be transformed or tweaked before
automation?
6. What are the technical and data protection implications?
7. What are the optical and change management implications
of using AI?
Intelligent Technology+ Human Ingenuity
Scaling Responsible AI
AI Virtual Workforce