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
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 [email protected]