www.nicsa.org

De-Mystifying Robotic Process Automation

2017 NICSA

Midwest Regional Meeting

#NICSAMWRM

THANK YOU TO OUR SPONSORS!

Platinum Sponsor

www.nicsa.org

Agenda

Welcome• Lisa Shea, Co-Chair, NICSA Midwest Regional Committee

Panelists • Amber Krueger, Moderator, US Bancorp Fund Services, LLC

• John Sjosten, Senior Manager, Deloitte & Touche LLP

• Randy Guy, Chief Technology Officer, FIS Global

• Andy Curtis, Data Analytics Manager, Northern Trust

Q&A

Roundtable Discussions

#NICSAMWRM

www.nicsa.org

Robotics & Cognitive Intelligence John Sjosten, Senior Manager, Deloitte & Touche LLP

#NICSAMWRM

www.nicsa.org

Digitization of white collar jobs via RPA & CI, and advances in data science have sparked the Business 4.0 revolution

We are on the cusp of “Business 4.0”

BPMSystems

Early RPA

Early cognitive

Widespread RPA

Widespread cognitive

Ubiquitous global horizontal MLPs

Business 4.0

• This revolution redefines what it means to be a professional

• RPA has commenced deployment in most large businesses

• RPA & Cognitive will be ubiquitous in business by 2020

• Horizontal machine learning platforms (MLPs) become ubiquitous by 2025

Industrial revolution

1-3

4.0

2017 Within 10 years

$5bn 2020 RPA market 1

$31bn 2019 Cognitive spending 2

2nd most important strategic priority

3.09

2.59

4.75

3.9

4.14

4.5

5.12

2.05

3.36

3.91

4.24

4.27

4.89

5.05

GBS model

Geo. scope

Analytics…

Increased func.…

Func. Proc.…

Automation

Contin.…

Today In ten yearsSource: Deloitte Global Shared Service Survey, 2015

Interest in automation is increasing at a rapid rate

1 http://www.transparencymarketresearch.com/pressrelease/it-robotic-automation-market.htm2 http://www.idc.com/getdoc.jsp?containerId=prUS410722163 https://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research/8

Growing use of Deep Learning at Google3

What’s changed: Convergence of 20+ years of AI

research, Cloud Computing, Big Data and increased

computing power

Copyright © 2017 Deloitte Development LLC. Allrights reserved.

#NICSAMWRM

www.nicsa.org

Robotic and cognitive automation solutions can increase capacity and extend the capabilities of organizations

Criteria

Rules-based, standard, repeatable processes

Structured / digital inputs and outputs

Human interaction with multiple systems

Limited decision-making or interpretation

Criteria

Unstructured inputs and outputs, including documents, forms, handwriting, audio, etc.

Customized, context-sensitive information

Feedback through training or data to improve algorithms over time (machine learning)

Sample Use Cases

Opening e-mails and attachments

Accessing web/enterprise applications

Moving files and folders

Extracting structured data from documents

Filling in and validating forms

Aggregating, validating/reconciling, transforming and calculating data

Sample Use Cases Generating insights based on customer activity

Developing fact-sheets and investment summaries

Improving the effectiveness of electronic communications monitoring

Guidance through complicated workflow with the use of intelligent agents

Machine-learning-based exception management and root-cause analysis

Cognitive Intelligence

Robotic Process

Automation

Software that can be configured to undertake rules-based tasks, replicating

human action

Algorithms which can interpret, learn and communicate, replicating human thought

Robotic Process Automation

(RPA)

Cognitive Intelligence

(CI)

By leveraging these capabilities, firms have begun to realize significant improvements leading to enhanced quality, reduced cost and efficiency gains

Copyright © 2017 Deloitte Development LLC. All rights reserved.

#NICSAMWRM

www.nicsa.org

Demo: Data Management & Reporting

What we will see

Using RPA to automate the FR-Y9C report production process using Excel, internal document management systems and databases

Automating the data acquisition, reconciliation, aggregation, transformation and validation activities, and using tools to generate exception reports and audit logs

Eliminating up to 80% of manual processing, enabling analysts to focus solely on managing exceptions and performing quality control checks

Securities

Lending

Security Master

& Pricing

Corporate

Actions

Regulatory

Reporting

Automating the report production process for financial and non-financial reporting

Aggregating overnight loan reports from external counterparties and balancing vs. stock record

Identifying discrepancies between data providers or internal sources and generating exception reports

Reconciling across pre- and post-payment data

Where this applies

Copyright © 2017 Deloitte DevelopmentLLC. All rights reserved.

#NICSAMWRM

www.nicsa.org

Robotics, Machine Learning, Cognitive Computing

Andy Curtis, Data Analytics Manager, Northern Trust

#NICSAMWRM

www.nicsa.org

WHAT DOES ARTIFICIAL INTELLIGENCE DO?

Value to Financial Services Industry

Smart Automation

(Learnt patterns)

AI Automation

(Cognitive ability)

AI

Ca

pa

bil

ity L

eve

ls

Basic Automation

(Rules based)

Research

PoV & Prototyping

Production Rollout• Document analysis – auto trade capture

• Transaction reconciliations

• Intelligent wealth advisory assistant

• Compliance surveillance & reporting

• Portfolio analytics and management

• Advanced client personalisation

Industry research and adoption is gaining pace as AI moves to mainstream

#NICSAMWRM

www.nicsa.org

WHAT ARE THE OBJECTIVES OF AUTOMATION?#NICSAMWRM

www.nicsa.org

WHAT ARE SMART MACHINES?

Smart Machine

Automation

AdvancedBasic• Technology is making great strides

in Smart Machines and Artificial

Intelligence

• The Fourth Industrial Revolution is

underway:

• Self-driving vehicles

• IBM Watson Jeopardy

champion

• Google DeepMind Go

champion

• Still a long way from true artificial

intelligent machine (i.e. the

Terminator)

• Basic process automation is the

simplest form of smart machine

automation

#NICSAMWRM

www.nicsa.org

ROBOTIC PROCESS AUTOMATION

Robotic Process Automation (RPA) refers to area of configuring “software” or “robots” to capture and interpret existing applications in order to perform a repeatable set of activities in an automated fashion.

Features

• Virtual workers

• Faster setup

• Uses existing systems/applications

Benefits

• Quick wins and faster ROI

• Reduced risk and error rates

• Respond faster to business peaks and

troughs

• Enable users to do other cognitive tasks

#NICSAMWRM

www.nicsa.org

COGNITIVE + RPA DOCUMENT INJECTION

Documents arrive to centralized ops center First several documents are unrecognized and must be “trained” via ML (classify + snap name/value) After training documents are auto classified, text and meta data extracted Passed on to RPA for business process completion

#NICSAMWRM

www.nicsa.org

ROBOTIC PROCESS AUTOMATION

Why Automation Projects Fail And How To Avoid This?

Randy Guy, Chief Technology Officer, Asset Management

www.nicsa.org

KEY THOUGHTS

Think strategic

and not tactical

RPA investment

continues to grow

“One size does not fit all”

– Don’t lock into a single

technology

14

www.nicsa.org 15

Top 5 Reasons RPA Projects Fail

Buying a tool in place of creating a strategy

Not setting up the proper organizational structures

Run as a project instead of a program

Process being automated is not well understood

Bringing in an RPA tool and ignoring what is in place

www.nicsa.org

Organization Initial Experience New Plan

Global telecom

organization

Automate Account Set-up, Operations and Closing

• RPA tool redundant with other in-house tools.

• Took many months to automate 2 FTEs

• Tool did not have the cognitive processing required

• Reviewed the process – got savings

through streaming the process

• Implementing cognitive solutions,

which will allow them to automate up to

80% of the process

Global

card provider

Automate Dispute processing

• IT purchased an RPA solutions – No prior business buy-in

• Tried to automate everything with workflows given by the

business, but not working as a team with the business – did not

automate the proper flows.

• Set up the proper organization and

realized savings of 1.1M.

Fitness product

provider

Automate fulfilment process

• Did not have expertise in automation – partner used for

fulfilment processing did not have the expertise in cognitive

solutions

• Got stuck with a process they felt could be automated, but did

not know how

• New partner: 30% discount on service

• Took on the risk of automation savings

• Partial automation solutions utilizing

cognitive solutions for processing

emails/ e- forms via NLP.

• Single screen interface for unifying

multiple applications and screens

• Leveraging BOTs to do the actual

processing.

Examples of RPA Failures and Turnarounds

16

#NICSAMWRM

www.nicsa.org

Expected cost based on project complexityC

om

ple

xity

Cost

BASIC

e.g. Update form from 1

app to another

HIGH

Judgement-driven

processes, e.g.

disputes management,

document management,

KYC, etc.

MODERATE

Standardized,

unstructured inputs: e.g.

Name, address change

form processing

$40K – $100K $100K – $175K $300K – $500K

Illustrative costs include software, resources and infrastructure costs.

17

#NICSAMWRM

www.nicsa.org

Questions&

Roundtable Breakout Sessions

#NICSAMWRM