How can you maximize the benefits from RPA and AI in your automation initiatives

RETHINKING
AUTOMATION
FOR
INSURANCE
Using Robotics and
AI for maximum impact
Private and confidential. Copyright (C) 2018, Imaginea Technologies Inc. All rights reserve.

SPEAKERS
Srikanth Vijay M
Senior Product Manager
Srikanth leads the Business Analysis team at Imaginea. He has
spearheaded several strategic automation initiatives for our insurance
customers. Srikanth also has an extensive understanding of the
automation landscape with a focus on emerging areas like Robotic
Process Automation and Artificial Intelligence.
Suresh Babu
Chief Revenue Officer
Suresh drives Imaginea’s business growth through robust sales,
marketing, and business strategies. He is a proven leader with a
successful track record spanning 20 years, and is known for his ability
to build high-performance teams and drive profitability and growth.

The connected future with RPA
THE INDUSTRIAL
REVOLUTION
Mechanization, water and
steam power
MASS
PRODUCTION
Electrical power and
assembly lines
COMPUTERIZATION
Automation and
digitization, Internet and
online
DIGITAL
TRANSFORMATION
The digital economy, IoT,
Cyber and AI, Advanced
robotics and automation
INDUSTRY 1.0
INDUSTRY 2.0
INDUSTRY 3.0
INDUSTRY 4.0

The role of RPA & AI in process automation
RPA
Systems based on rules.
AI
Systems that learn.
Automate easy
tasks, hands over
data to AI
AI learns to mimic and
improve processes
based on data handed
over from RPA
▪ Access legacy system data
▪ Filling in web forms
▪ Copy data from one system
to another
▪ Learn from human decisions
▪ Make fast judgments
▪ Interact with humans
PROCESS
AUTOMATION

AGENDA
RPA & AI: Expectation vs. reality
Planning & implementing automation initiatives
Key success factors
Case study: RPA & AI in action
Summary

Key takeaways
Role of RPA and AI in
automation
Why RPA and AI
implementations don’t
achieve their goals?
Planning and
implementing
automation initiatives
that deliver high ROI
How can you maximize the benefits from RPA
and AI in your automation initiatives?
1 2 3

RPA & AI:
EXPECTATION
VS. REALITY

RPA & AI: Are they delivering on the promise?
Expectation
▪ Automated and
streamlined end-to-end
processes
▪ High ROI through reduction
in manual effort
▪ Improved quality
Reality
▪ 30 to 50% of initial RPA
projects fail
▪ Siloes of automation that
is tactical and not strategic
▪ Costly implementations
with low returns
▪ Service Quality issues due
to automation failure

What is the role of RPA and AI in automation?
1
Expand automation to areas not addressed effectively by traditional approaches
(BPM, Workflows, Business Rules Engines, etc.)
RPA
AI
Reduce overall cost through pre-
defined automation features
Extract information from templated
insurance documents
Automate processes where integra-
tions are expensive or not feasible
Create and email quote from AMS
Automate processes that are prone
to change
Claims processing that is
customized by the state or LOB
Handle process volumes that are
low, medium or high
Handling peak season volumes like
Jan 1 renewals

What is the role of RPA and AI in automation?
1
Expand automation to areas not addressed effectively by traditional approaches
(BPM, Workflows, Business Rules Engines, etc.)
RPA
AI
Processes that require human-like
behavior
Handling customer enquiries
Derive information from
unstructured data
Extract policy and claims
information from policy documents
Automate tasks that require
complex decision making
Property assessment on IoT
devices’ data
Processes that need to adapt to
changing input patterns
Fraud detection of claims

▪ Automation in silos
▪ Wrong process prioritization
▪ Low focus on exception
handling and process
monitoring
▪ Using POCs as the only
benchmark of assessing
opportunities and benefits
▪ ‘One solution fits all’ approach
▪ Aiming at full automation,
ignoring ROI
▪ Lack of business ownership
▪ Managed as multiple individual
projects rather than as a
program
▪ No dedicated maintenance and
change management team
Why RPA and AI implementations don’t
achieve their goals?
2
Poor planning
Inadequate
opportunity
assessment
Ineffective
project structure

PLANNING AND
IMPLEMENTING
AUTOMATION
INITIATIVES
THAT DELIVER
HIGH ROI

AUTOMATION
OPPORTUNITY
ASSESSMENT

Define the ‘Why’  Goals
1
IDENTIFY GOALS DEFINE THE GOALS
Organization
Division
Team
Process
Revenue
Efficiency
and cost
Quality Scalability
Customer
satisfaction
Compliance

Assess the ‘What’  Opportunities
2
IDENTIFY
AUTOMATION
OPPORTUNITIES
QUANTIFY
BENEFITS
AND RANK
OPPORTUNITIES
Granularity can depend
on the level
(organization/division/
team/process) at which
the opportunities are
being assessed
Manual
effort
Multiple
applications
Processing
time
Turn around
time
Quality
Customer
satisfaction
Volume
Business
priority

Define the ‘How’  Automation roadmap (1/2)
3
Prioritize opportunitiesMap approaches to opportunities
Unstructured
data / complex
decision making
AI
Structured data
Integrations
Process
flow
RPA or Traditional Automation
Decision based on
▪ Process maturity
▪ Frequency of
change
▪ Readily available
APIs
▪ Frequency of
change to UI

Define the ‘How’  Automation roadmap (2/2)
3
INPUT FROM EMAILS CLASSIFICATION
▪ Type of information to be extracted
✓ Standard email fields
✓ Attachments
▪ Type of documents
✓ Unstructured
✓ Not templated
▪ Change in document categories
✓ Not frequent
▪ RPA (chosen)
✓ Out-of-the-box feature
▪ Integration with mail application
▪ AI (Chosen)
✓ Large training and test data available
▪ RPA for frequently occurring document
categories
Evaluation
criteria
Solution
approaches

Always know the ‘Status’ (1/2)
4
Include process, RPA and AI governance in the automation roadmap
▪ Process monitoring
▪ Exception handling
▪ Task management
▪ Regulatory compliance
▪ Monitoring
▪ Configuration
▪ Deployment
▪ Exception handling
PROCESS MANAGEMENT ROBOT MANAGEMENT AI MONITORING
▪ Monitoring accuracy
▪ Managing outliers
▪ Error handling
Evaluate RPA orchestrator vs. building custom application with low-code platforms like WaveMaker
GOVERNANCE

Always know the ‘Status’ (2/2)
4
Include process, RPA and AI governance in the automation roadmap
PROCESS GOVERNANCE
ROBOT MANAGEMENT
AI MONITORING
AI Accuracy Report for Document Identification
Total Documents AI Identified Percentage Accuracy
1000 950 95%
# File name Actual Doc Type AI Identified Type
1 File1.pdf Policy Policy
2 File2.pdf Policy Policy
3 File3.pdf Correspondence Correspondence
4 File4.pdf Endorsement Policy

OUR
STORIES

S
Problem statement: Streamline operations
XYZ Insurance Company grew manifold over the last 20 years. Like many
insurance companies of its size, it had focused on revenue generation and
not as much on improving operational efficiencies.
New business/account
management/finance
Operations
Carriers
Clients
▪ Redundant activities
▪ Poor work distribution
▪ Reduced quality resulting in escalations
▪ Low data integrity & security due
▪ Long turn-around times
▪ Lack of visibility to into
operations
▪ Delayed response to
customer queries
Suppliers
DMSAMS

Solution: Automation opportunity assessment
RPA AI Integrations
Database driven workflows and business rules
Dashboards and monitoring functionality
Data warehouse for operational reports and
advanced analytics
Automation
Task management
and work allocation
Process, robot and
AI governance
Analytics

EXAMPLE 1: Document indexing
Documents received through email
Trigger AI Pipeline
Get additional
information
based on policy/
client details
Clients/
Carriers
Robot
1
2
4
8
6
7
Request DB
AMS
Poll mailbox for new emails
OCR
Document
Classification (AI)
Extraction (AI)
Mailbox
Update details
for document
Create request
for document
3
5
Update AMS
details for
document
Manual verification and
update (process
management application)
Document
Library
9
Save document
in DMS with
metadata
STEPS AUTOMATED
▪ Read emails and create
requests in request DB
▪ Classify and extract
information from documents
▪ Get policy and client
information from AMS
▪ Send document to DMS with
metadata
BENEFITS
▪ Achieved 40% gain in efficiency
▪ Classification accuracy of 90%
and Extraction accuracy of 80%
▪ Extracted information like claim
information used for data
analysis

EXAMPLE 2: Accounts Payables Automation
STEPS AUTOMATED
▪ Automatically read invoice
data from emails
▪ Create invoices and issue
payment in financial system
BENEFITS
▪ ~50% of the process
automated
Invoices received through Mailbox
Create invoice
Poll mailbox for email
Extract invoice data
Check database for new item
Fetch payment due
Issue
payment
Suppliers
Robot
1
2
3
4
5
6 7
Temp.
databaseFinance system
Mailbox

EXAMPLE 3: Migration
STEPS AUTOMATED
▪ Migrate policy and claim data
from legacy system to new
AMS
BENEFITS
▪ Migration completed in 80%
lesser time than if done
manually
Get client data
Robot
Read List
Create PoliciesGet policy data
Create Clients
1
2 3
New AMSLegacy DB
List of Clients
and Policies

KEY FACTORS
TO CONSIDER IN
IMPLEMENTATION

Design for scale and performance
1
Growth in transaction volume
No. of emails received as of today is 1,000,000 per
year. Expected to reach 2,000,000 in 2 years
How many transactions should the
solution process in a given time?
1,000 documents have to be processed in 8 hours
How can the solution scale to handle
additional volume?
More robots, more CPU/ GPU

Focus on exceptions:
Leads to a robust implementation
2
▪ Most processes adhere to the Pareto 80:20 rule w.r.t exceptions
▪ Missed exceptions most frequently lead to escalations
▪ Handling the 20% exception can take up 80% of implementation effort
Identify exceptions
Re-engineer process to
reduce exceptions
Automating the exception
processing
Flag exception for manual
handling
Or
BENEFITS
TO DRIVE
THE
DECISION

AI in AI projects is typically the smallest effort
3
AI
Project
Training and
test data
preparation
QA
AI
development
Pre and post
processing
components
Monitoring
and audit
trails
BEST PRACTICES
▪ Define the minimal acceptable
accuracy and target accuracy
▪ Plan a pre-implementation stage for
training and test data preparation
▪ Automate QA and Reporting
▪ Standardize reporting of accuracy
metrics
- Helps project management
- Can be used for monitoring and
audit in the long run

Factor changes to existing applications
4
Handle the re-engineered
process
Automate certain steps
easily e.g. getting
additional fields from an
existing API
Provide data for
automation solutions
Existing applications may need to be changed to …
ENSURE THAT THE CHANGES TO DEPENDENT APPLICATIONS ARE PLANNED
ALONG WITH THE NEW AUTOMATION SOLUTION

Conduct a post implementation assessment
5
MEASURE SOLUTION PERFORMANCE
• Throughput
- Verify automation results manually in production
• Accuracy
- No. of transactions that the solution processes
in a given time
• Exceptions
- Tasks that the solution failed to handle
- Tasks that went through Exception flows
• Utilization
- Percentage of time the BOT is working on tasks
• Adoption
- % of expected transactions handled through the solution
- No. of users
EVALUATE ROI
• Quantitative analysis
- Reduction in manual effort
- Process scalability
- Quality improvement
- Client and user satisfaction
• Qualitative Analysis
- Process governance
- Reporting
- Ease of change management
- Process agility
USE THE FEEDBACK TO FINE TUNE THE OVERALL
AUTOMATION ROADMAP

SUMMARY
 RPA and AI are great enablers of automation; provided
initiatives are planned and executed carefully
 Always start with an Automation Opportunity Assessment;
quantified benefits should drive the roadmap
 Consider features for Governance and changes to existing
applications in the automation roadmap
 Plan for short releases and post implementation
assessment to stay on track

About Imaginea
Pramati’s M&A’s of
leading products
Innovation
enablement
Serving over 200
product companies
Agile
methodology
User-centric
design
Serving from 5
global locations
Products built from
conception-code-cash
Unique
products & services
1300+
engineers

LET’S STAY CONNECTED
Srikanth Vijay M
Senior Product Manager
srikanth.v@imaginea.com
Suresh Babu
Chief Revenue Officer
suresh.babu@imaginea.com

Disclaimer
This document may contain forward-looking statements concerning products and strategies. These statements are based on
management's current expectations and actual results may differ materially from those projected, as a result of certain risks,
uncertainties and assumptions, including but not limited to: the growth of the markets addressed by our products and our customers'
products, the demand for and market acceptance of our products; our ability to successfully compete in the markets in which we do
business; our ability to successfully address the cost structure of our offerings; the ability to develop and implement new technologies
and to obtain protection for the related intellectual property; and our ability to realize financial and strategic benefits of past and future
transactions. These forward-looking statements are made only as of the date indicated, and the company disclaims any obligation to
update or revise the information contained in any forward-looking statements, whether as a result of new information, future events or
otherwise.
All Trademarks and other registered marks belong to their respective owners.
Copyright © 2018, Imaginea Technologies, Inc. and/or its affiliates. All rights reserved.
Credits
Images under Creative Commons Zero license.

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