INTELLIGENT AUTOMATION FOR CREDIT UNIONS

Jesse McGannon, Vice President Advisory ServicesStrategic Resource Management

Learning Objectives:1. Understand the value proposition of various intelligent automation technologies.2. Explore the top use cases for credit unions.3. Learn how these technologies can be implemented effectively based on the scale

of your organization.

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INTELLIGENT AUTOMATIONFOR CREDIT UNIONSWhat, How, and How Much?

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Strategic Resource Management Established in 1992 Helps credit unions improve their performance through benchmarks, data,

strategy, and analytics $2.2 billion+ in implemented cost savings, revenue growth and efficiencies

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Jesse McGannon VP, Intelligent Automation 10+ years in financial services consulting

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“YOU’RE EITHER THE ONE THAT CREATES THE AUTOMATION,

…OR YOU’RE THE ONE GETTING AUTOMATED.”-Tom Preston-Werner, American Billionaire, Entrepreneur, GitHub Founder

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1900s Mechanical Computing Era

Calculation tasks, e.g. recording population data, evaluating corporate financial performance. (Hollerith Tabulating Machine)

1950s Programming Era

2000s Cognitive Era

2020s AI Expansion Era

Programmable systems and the digital revolution – e.g. development of the internet and space exploration. continue to form the backbone of computing. (FORTRAN, Windows OS)

Computers doing cognitive tasks inspired by the human brain, fuelled by ever-growing capacity and data availability. (Watson, Level 2 Autonomous Vehicles, Google Duplex, GPT-2)

AI systems continue learning to perform tasks formerly the sole province of humans

Progression of Technological Intelligence

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Why Credit Unions Should Embrace Intelligent Automation

Improve the Member Experience

Reduce Costs Empower Your Staff

Reduce Risk

Greater than 80% of the time, credit unions do not reduce headcount as a result of implementing IA

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Mature

Emerging

RPA

Intelligent Automation

Narrow AI

General AI

Rules-based Automation Text Analytics

Optical Character Recognition

Intelligent Word Recognition

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

Natural Language Processing

Machine Learning Enabled Analytics

Sentiment Analysis

Speech Recognition

Image Recognition

Computer Vision

Natural Language Generation

Generative Adversarial Networks

Digital Assistants

Intelligent Advisors Zero Knowledge Systems

SingularityAdaptive Knowledge Representation

Reasoning

Robotic Process Automation Automates rules-based digital tasks

Intelligent AutomationAutomates Digital Workflows

Narrow AIMimics Human Intelligence

General AIAutomates Human Intelligence

Artificial Intelligence Maturity Spectrum

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Three Technologies Most Impactful for Credit Unions

Robotic Process Automation

Conversational AI

AI Based Underwriting

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RPA is… RPA is not…

What RPA is good at

Moving files and folders

Scraping data from the web

Filling in forms

Reading and writing to databasesExtracting structured data from documents

Performing calculations

Connecting to system APIs

Following “if/then” decisions/rules

Logging into web/enterprise applications

Reading and sending email and attachments

Copying and pasting

Processing 24/7 to handle high volume

Computer-scripted software AI or virtual assistants (e.g. Alexa, Siri)

Capable of interacting at the UI layer or via APIs Tied to specialized physical machines (e.g. scanners)

Programs that replace or augment humans performing rules-based digital tasks

Capable of ‘learning’ new tasks outside the boundaries of its programming

Cross-functional and cross-application macros Walking, talking robots

RPA: What it is, what it isn’t, and what it’s good at

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Credit Union RPA Use Cases

• Loan Origination and Onboarding

• Loan Processing/ Funding

• Loan Servicing• Mortgage Defaults

• Remote Deposit Capture

• Wire Transfers• Check

Adjustment Processing

• Check Holds

• Change of Address

• Payment Processing

• Password Resets• Data Entry Across

Applications

• New Account Opening

• Loan Application Processing

• Data Entry• Reconciliations• Wire Entry

• Employee Onboarding

• Employee Offboarding

• Accounts Payable• Accounting Daily

Balancing • IT Daily

Processing

LOAN/MORTGAGE OPERATIONS

DEPOSIT OPERATIONS CONTACT CENTER BRANCH OTHER

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Conversational AI can simplify the member/user interaction

Simple

Example

Respond to questions like “What isthe guest wifi password” or “Whatis our policy about accepting gifts”

Medium

Example

Tasks needing back and forthinteraction – some integration withother systems – “reset my password” or “Update my tax withholdings”

Complex

Example

Complex tasks with business process spanning multiple systems over a period – “Onboard a new employee” or “I need to apply for maternity leave”

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Customer

Sales

ServiceWeb Portal

Email

Phone

Virtual Assistant

Who is the customer?

What is their intent?

Can I help them?

Meta Data

Knowledgebase/FAQs

Federated KM Sources

CRM Systems

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AI Based Underwriting Enables Credit Unions to Make Smarter Decisions

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Disparity in the American Dream, Traditional Underwriting is Biased

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AI Based Underwriting Produces Better Financial Results

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So….are we all going to be replaced by robots?

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Automation Potential and Impact

In Banking: “An estimated 200,000 U.S. banking jobs could be cut in the next 10 years and replaced by robots and other tech, according to a report by Wells Fargo analyst.”

Technicalautomationpotential

Impact of adoption by 2030

of current work activities are technically automatable by adapting currently demonstrated technologies

~50%Current occupations have more than 30% of activities that are technically automatable

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Work potentially displaced by adoption of automation, by adoption scenario, % of workers (FTEs1)

Workforce that could need to change occupational category, by adoption scenario,2 % of workers (FTEs)

Slowest Midpoint Fastest

0%(10 million)

15%(400 million)

30%(800 million)

Slowest Midpoint Fastest

0%(<10 million)

3%(75 million)

14%(375 million)

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Questions?

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Thank You

Jesse McGannonVice President630-302-1104jmcgannon@srmcorp.comwww.srmcorp.com