MAXIMUS and Artificial Intelligence Harry Sundberg, MAXIMUS Federal Services October 5, 2018

Many MAXIMUS Tasks Require Manual Operation Call Center manages high volumes and seasonal surges Payment Center, Back Office and Non-Financial Operations highly manual System updates

High Call Center Volumes Surge Surge

Artificial Intelligence Implementation Improving Call Center productivity Deploy Virtual Assistant Artificial Intelligent agent handles calls Virtual Assistant learns from interaction with customers over various situations Intelligent Assistant assists where Virtual Assistant can’t understand Significantly reduces Call Center agent time while maintaining real agent experience Implement Robotic Process Automation Gathers data from various systems and presents consolidated data to an Agent Desktop Presents information needed to support call with customer, eliminating delay

The Evolution of the Virtual Assistant The NEXT Generation of citizen service has arrived! Achieving world class citizen engagement and lower overall program costs. Deployment is fast and less invasive to deliver quick wins for Agencies. Provides the foundation to go deeper into citizen intent than ever possible! Customer Satisfaction “Press 1 for Billing; Press 2 for Sales, Press 3 for Hours of operations, Press 4 for ….” “Press or Say “1” for Billing, Press or Say “2” for Sales, Press of Say “3” for…” “Please tell me why you are calling today?”, followed by: “I am sorry could you be more specific and say things like account balance”, “I am having trouble understanding you, let me connect you to an agent” “Hello, I am a Virtual Assistant. Speak to me like you would a real human being. How may I help you today?” The Modern Virtual Assistant evolved from the older Interactive Voice Response (IVR) technologies, which were revolutionary when first adopted. IVR’s meant citizens no longer could speak with agents immediately, and citizens must learn government menu trees to get assistance, citizens soon learn pressing zero gets agent assistance. Natural Speech Recognition was incorporated into the IVR solutions to create the Pioneer Virtual assistants. Citizens still struggled with programmed menu trees and fight these new technologies by pressing zero or saying “representative!” to quickly get assistance. However, call centers take away this option to force citizen to listen to menu. Siri and Alexa arrive on the scene and Virtual Assistants and can have expensive integration with legacy systems. However, limits of the Artificial Intelligence (AI) get tripped up by complex requests, heavy accents and background noises which make a difficult citizen experience. High number of calls still going to Live Agents and misrouted calls are common. Extended deployments limit the business case outcomes. The NEXT Generation IVR has arrived, achieving world class citizen engagement and lower overall program costs. Deployment is fast and less invasive to deliver quick wins for Agencies. Additionally, the platform provides the foundation to go deeper into citizen intent than ever possible! 1st Gen “Touch Tone IVR” 80’s & 90’s 2nd Gen “Virtual Assistant Pioneers” 2000’s 3rd Gen “Birth of SIRI, Watson and ALEXA Virtual Assistants” TODAY Next Gen “Human Assisted Virtual Assistants” TOMORROW

Human Intelligence Supports the Virtual Assistant “I was in an accident….. …and I would like to check on….. the status of my claim.” HUMAN ASSISTED UNDERSTANDING iProxy Claim Status The MAXIMUS Intelligent Assistant introduces Human Assisted Understanding (HAU), which is briefly called upon when the AI fails to recognize the speech. A short speech utterance is sent to a human, who interprets and sends the data back to the Virtual Assistant and the citizen never detects the human interaction. Voice Automatic Speech Recognition (ASR)

Time Required for Tuning is Transformational HUMAN ASSISTED UNDERSTANDING CONTINUOUS TRAINING AND TUNING iProxy Deployment and Tuning of the Virtual Assistant is done in days instead of months. Rollouts start with small call volume to ensure the application is accomplishing the goals established and more call volume is added as outcomes are realized. The unique human aspect of validating voice utterances increases the rate of tuning beyond normal AI programming. Voice Automatic Speech Recognition (ASR)

The Problem: Manual Processing Display as much data as possible Agent left to make sense of it all Months of training No consistent flow Cut-copy-paste Manual notes

Artificial Intelligence Implementation Deploy Robotic Processing Assistant to improve Business and Financial processing productivity Many operations have a large manual processing component Mail correspondence response Manage Treasury Offset hearing requests Refund Processing Manual Payment Entries (~800k a month) Loan Intake processing (volume peaks at 250k in a given month) Volume peaks difficult to anticipate Resource ramps require 60 days to ensure security clearance Onboarding/Off boarding costly

RPA Overview – The purpose of Automation Improve human performance Improve efficiency and accuracy – results Lower cost Reduce risk Increase job satisfaction

Evolution of a manual process using RPA Automated process Robot Process Automation

What is RPA? RPA can: Robotic Process Automation (RPA) Business process software that performs rules-based, repeatable processes typically performed by people today RPA can: Be trained to perform simple to very complex processes Interact with any existing system and application currently used by people (i.e. email, spreadsheets, mainframe, etc.) Easily integrate into existing business processes and workflows with limited development effort

Which Tasks Must a Human Perform?

Which Tasks Must a Human Perform?

RPA Delivers Unique Benefits to Organizations When Successfully Incorporated into Operations Increased efficiency Improved employee productivity and morale Reduction of errors/increased quality Increased regulatory compliance Improved audit reporting Decreased operational expenses Not all processes are created equal; organizations must creatively and diligently identify operations that are ideal for RPA application. RPA is best suited for processes and sub processes with key characteristics.