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A Primary Matters Total Cost of Ownership/ROI Analysis . . .

The Impact of a Next Generation Voice Recognition Solution on Credit Union and Banking IVR Applications

August 10, 2002

Primary Matters, Inc.
(902) 794-7095
www.primarymatters.com

 

Table of Contents

Executive Summary
Impact on the Customer Base and Financial Performance of a Small Financial Service’s Retail Banking Business
Assumptions Used in the Small to Medium Financial Service Company Analysis
Benefits of Voice Recognition to Financial Service Companies using IVR Applications
Quantifying Benefit 1: Time Savings due to simpler, faster entry of information using voice recognition
Quantifying Benefit 2: Higher Use of IVR Scripts for Customer Service and Fewer Transfers to Customer Service Agents during IVR Usage
Quantifying Benefit 3: Changes in Customer Satisfaction and Customer Life Cycle
The Cost of the Voice Recognition: An ASP Service Costing $0.10 per Minute of Usage
Financial Implications: Cost Savings by Quarter
Financial Implications: Comparison of Cumulative TCO and Cost Savings
Financial Implications: Increase in Revenue Due to Higher Customer Satisfaction
Assumptions about Customer Contact Center Agents, Supervisors and Operations Personnel
Assumptions and Profile of the Financial Services Company’s Retail Banking Products
Contact Centers Annual Operating Budget Before and After the Addition of Voice Recognition
Baseline (Before Voice Recognition Solution) Operations Budget
ROI Based Only on Operations Cost (Contact Center Cost Savings)
ROI Based on Total Impact, Including Operations Costs, Revenues and Product Cost Changes

 

Executive Summary

Voice Recognition solutions continue to evolve in quality and ease of use. This analysis focuses on the approach offered by the next generation of voice recognition applications, which may be developed using the emerging application development platforms from a variety of companies. Typically, the companies developing these platforms are beginning to offer XML-based scripting languages ready for building packaged applications. They also use underlying voice technology from companies such as Nuance and Speechworks.

The goal of these platforms is to make it easier for an organization to include voice recognition in a company’s portfolio of customer service options. The goal being a significant impact on both cost savings and increased customer satisfaction.

Just as Touch-Tone based Integrated Voice Response (IVR) has revolutionized the interface to customer service centers over the last 10 years, voice recognition solutions are likely to do the same. Those companies, who embrace the technology making it a seamless part of their service environment, will find their costs per customer decreased. These companies will also find greater customer loyalty and increased new customer attraction. This will increase their market share.

This analysis describes the financial and customer relationship impact of replacing a classic banking Touch-Tone IVR application with voice recognition. The usage data describing the Touch-Tone application is based on actual data. The post-voice recognition changes are based on analyzing the impact that voice recognition would have on the use of touch-tone applications. In this analysis the bank receives 100,000 calls a month from a base of 200,000 customers. The impact of voice recognition can be summarized as:

  • Over a 16-month phase-in, use of the IVR grows significantly because of ease and speed.
  • The average duration of each IVR usage declines to almost half of the time used during a Touch-Tone interface.
  • Calls transferred to Agents decline by about a third saving major labor expenses.
  • Customer satisfaction increases lengthening the average customer life cycle by about 20%.
  • Profits and revenues of the financial institution increase significantly over the three-year period due to heightened customer satisfaction.

Impact on the Customer Base and Financial Performance of a Small Financial Service’s Retail Banking Business

The following table and graph summarize the impact of voice recognition. The customer base grows, and revenues and profits increase significantly. The product costs increase due to the larger number of customers remaining with the bank longer.

 

This graph illustrates the impact on the major financial measures of the bank.

Impact of Voice Recognition on Bank’s Financial Performance

 

Assumptions Used in the Small to Medium Financial Service Company Analysis

The information in this document is based on a small financial services company offering retail banking, loans and credit card services to its customers. A Touch-Tone based IVR application is used as the first point of contact to all callers. They can choose to go directly to Contact Center Agents, or to use the IVR application to receive the information and service they need.

The basis of the data and estimates in this document are:

  • The analysis of caller usage, call lengths and transfer rates are based on research data from a small financial service’s IVR application.
  • Data supporting the costs of personnel, technology and telecommunications services are based on research across multiple organizations.
  • The revenue and product costs for the banking products are estimates.
  • The contact ratio per customer (one time every two months) is also an estimate.
  • The scenario data describing the impact of voice recognition on these applications is based on estimates.
  • This model uses a phase-in schedule of 16 months for the changes in caller behavior and consequent financial benefit of adding the voice recognition solution to its user interface.

The Call Model

A simple call model is used in this analysis:

  • Calls arrive at the IVR Application where the primary Greeting Menu is played to the caller.
  • A proportion of Callers who are familiar with the IVR Application immediately enter the number they need to go to the next menu bypassing the IVR Application.
  • Callers listening to the Greeting Menu choose to either go into the Banking IVR Application, or choose to go directly to agents for service.
  • When Callers transfer to Agents:
    • The caller is in queue for 30 seconds, and on average 2% of the calls drop out of the queue.
    • The caller is transferred to an available Agent, who on average, talks with the customer for 3 minutes.
    • At call termination, the agent does ‘after-call work’ which averages 30 seconds per call, and is required for half of the calls.
  • Those using the IVR Application go through the menus obtaining the information they need. Some percentage of these callers will also opt out to Agents during their interaction with the IVR Application.

The following table illustrates the major flow of calls into the organization (based on actual data). It also provides estimates of the impact of voice recognition on call flow.

 

Benefits of Voice Recognition to Financial Service Companies using IVR Applications

BENEFIT 1: Shorter period of time using IVR due to simpler, faster entry of information using verbal responses instead of Touch-Tone responses

  • Fast, information requests, bypassing traditional IVR Menu structures

    With a voice recognition solution, users will no longer be restrained by a structured menu approach. For instance, after the caller is authenticated, they will be able to state their interest. A caller can state “Checking Balance”, and two menus will be bypassed saving between 40 and 100 seconds.

    After receiving this, the caller might state, “VISA Balance,” bypassing the traditional IVR menu tree (going up and back down) to get their VISA balance. In a traditional environment, the callers opt to the customer service representative to obtain the information to avoid the annoying IVR navigation at a much higher cost to the bank.
  • Faster and more accurate numeric data entry

    Even if the caller does use the menu structure, it takes less time to speak the entry and there is more accuracy than attempting to enter 12 and 16 digit numbers using Touch-Tone.

These changes in the IVR usage time and the reduction in call transfers to Agents are quantified in the next several pages of this document.

BENEFIT 2: Higher Use of IVR Scripts for Customer Service and Fewer Transfers to Customer Service Agents During IVR Usage

Two major themes are present in the increased IVR productivity from voice recognition technologies when compared to Touch-Tone based IVR applications:

  • Fewer Users Dial ‘0’ to go immediately to agents

    Studies comparing voice recognition with the traditional Touch-Tone approach show that there is a higher usage of the IVR applications. This is due to the ease of speJune 3, 2005are not able to use Touch-Tone, for instance while in automobiles using cell phones.

    The impact of this varies by application but it can be assumed that as users become acclimated and know that they can ‘speak’ instead of using Touch-Tone there can be a reduction anywhere from 25% to 75% in the use of Agents for those roles which are supported by the IVR applications.
  • Fewer Users transfer to Agents in the middle of the IVR Scripts due to frustration

    Users often become frustrated with IVR solutions. This leads to 3% of the users, who have already started the IVR application, giving up in frustration and requesting an Agent.

    Voice recognition reduces both the frustration factor and the mistake factor, which leads to the Agent Transfer request.

BENEFIT 3: Higher Customer Satisfaction reducing churn and increasing new customer acquisition rates

For those financial institutions that successfully incorporate voice recognition into their organizations, customers will increase their usage of IVR applications due to their increased satisfaction with the interface. Noting that the IVR handles more than 50% of the calls into smaller credit union and bank contact centers and 80% of calls into larger banks, the importance of customer satisfaction with the IVR applications is paramount.

Quantifying Benefit 1: Time Savings due to simpler, faster entry of information using voice recognition

The following tables outline the usage of the most important of the IVR menus, and compare a Touch-Tone IVR Application environment with a Voice Recognition Application environment. The duration of a session using voice recognition is 54% shorter, 52 seconds less per caller, than using Touch Tone. This benefit takes about 16 months to phase in, as the Caller’s become accustomed to Voice Recognition and begin to use it more. The impact of upgrading to voice recognition is summarized in the following table.

This analysis highlights the impact of voice recognition on the four menu choices that account for 70% to 80% of the typical IVR application usage in a credit union or small bank. These choices are the ‘Greeting Menu’, ‘Caller Authentication’, ‘Retail Banking Menu’, and ‘Checking Account Status’ menu.

Usage Patterns and Durations, by Prompt, for Touch-Tone and Voice Recognition-based IVR Application

 

Analysis of Calls Transferring to Agents Comparing a Touch-Tone Interface with a Voice Recognition User Interface

 

Guide to the IVR Application Menu Analysis Tables

The following terms define the table headers that follow.

 

The Initial Greeting Menu

Current IVR Application:

This example IVR menu typically greets each caller to a financial services company when their main number is called. Of the new call arrivals 75% of the callers go through this menu and 25% immediately make their choice, either by dialing ‘0’ to go directly to an agent or by choosing another option going directly to the next IVR application menu.

With a Touch-Tone User Interface:

Under the Touch-Tone IVR Applications approach, the average time spent on this menu is 43.8 seconds.

With a Voice Recognition User Interface:

Most callers to a small bank or credit union are reasonably familiar with the IVR application content and know why they are calling. These callers will be able to state “I want to talk to an Agent.” or “I want my checking balance.” and the application will pass them to the next step, for instance, requesting a User Authentication, saving time.

The following chart provides an example of the new timing associated with a menu using Voice Recognition

With Voice Recognition, the average time per contact for using this menu is 27.2 seconds a savings of about 12.8 seconds per caller.

The number of callers transferring to Agents declines, since more callers will use the Voice Recognition interface. They don’t have to remember their Account ID and PIN, and the interface is easier when driving and using cell phones.

Percent immediately transferring to Agents with Touch Tone User Interface 25%
Percent immediately transferring to Agents with Voice Recognition User Interface 15%

The number of callers listening to this menu declines significantly with voice response, since a caller can state, “Checking Balance” and bypass this menu without having to know what to key into the telephone set. The estimates of use of this menu are:

Percent using this menu with Touch Tone User Interface 75%
Percent using this menu with Voice Recognition Interface(declines due to bypassing menu) 41%

The User Authentication Menu

Whenever a user chooses to go for the IVR Banking application menu or they immediately choose to talk to an Agent, they are requested to enter their Account Number and PIN for Identification. Of the calls arriving at the bank’s main number, this typically represents about 75% of the callers.

Current IVR Application:

With Voice Recognition

This Voice Recognition solution is based on the emerging voice authentication recognition standards that can provide highly secure caller identification by requesting the caller’s name, and then asking them to repeat three words. This approach has been proven to be as, or more, accurate in authenticating callers than the current approach used with Touch-Tone.

There will be a slightly higher usage rate since those that cannot remember their account number and PIN will be able to fully identify themselves, and the time required to accomplish the identification is about half of that required by the traditional touch-tone user interface.

Percent using this menu with Touch Tone User Interface 75%
Percent using this menu with Voice Recognition Interface 85%

The IVR Retail Banking Main Menu

After successfully being identified by the system, this example menu is typical of the IVR menu that customers use to acquire account information or do other simple services, such as activating banking cards or re-setting their Personal Identification Numbers (PINs):

Current IVR Application:

With Voice Recognition

With the Voice Recognition solution users will no longer be restrained by a structured menu approach. For instance, after the caller’s authentication is passed, they will state their interest (as described above) bypassing this menu entirely.

 

The Checking Account Status Menu

This example is typical of the menu of the IVR applications that customers use to acquire account information or do other simple services:

Current IVR Application:

With Voice Recognition

 

Quantifying Benefit 2: Higher Use of IVR Scripts for Customer Service and Fewer Transfers to Customer Service Agents during IVR Usage

Two factors affect the calls transferred to Agents:

  • Users immediately transfer to Agents because they do not want to use a Touch-Tone based IVR Application. In this model, it is assumed there is an immediate 25% transfer to Agents using the Touch-Tone based IVR Application. This is reduced to 15% with the voice recognition user interface.
  • Fewer users who begin using the IVR Application consequently transfer to Agents in mid-stream. Research shows that the mid-stream transfers account for about 24% of calls for small to mid-sized banks. This is anticipated to go down to 17% with voice response applications.
  • In total, the voice recognition user interface will reduce the percent of calls going to agents from 49.5% to 32%.

These impacts are detailed in the tables presented under Quantifying Benefit 1.

 

Quantifying Benefit 3: Changes in Customer Satisfaction and Customer Life Cycle

A financial institution that increases its IVR platforms ease of use and shortens the time it takes for a user to receive benefits will increase customer satisfaction. Changes to customer churn, especially in the credit card industry, may have a material impact on financial results.

In this document, the initial customer life cycle is assumed to be 48 months. We assume that the average customer life cycle lengthens by 20% to 60 months due to the major improvements in communicating with the financial institution. This phases-in over a sixteen-month period, as the users become familiar with the voice recognition user interface, and then become dependent on voice recognition!

 

 

The Cost of the Voice Recognition: An ASP Service Costing $0.10 per Minute of Usage

The voice recognition solution is presented as an ASP service, as opposed to a customer-installed option. Voice technologies are evolving quickly, and such an approach enables the solution provider to continuously upgrade to further improve customer service.

This is an expensive approach costing $400,000 per year. (See the detailed table below.) The return due to this solution justifies such a major increase in costs.

 

 

Financial Implications: Cost Savings by Quarter

This graph shows the Total Cost of Ownership (investment, expenses, operations and personnel costs) associated with implementing the voice recognition solution compared to the cost savings obtained by the financial services company. Break even is reached in three quarters, leading to a positive Return on Investment in the first year.

The increase in revenues, not accounted for in this cash flow and breakeven analysis, is the most important benefit. However, it is not necessary to include this benefit to justify the investment in a Voice-Recognition Solution.

 

Financial Implications: Comparison of Cumulative TCO and Cost Savings

This chart shows that the cumulative Total Cost of Ownership of the voice recognition solution, and the cost savings to the small retail bank cross into positive territory in the fifth quarter after deployment.

The break-even is based on a 16-month phase-in for the bank’s callers to become familiar with the voice recognition solution and change their usage patterns. If this change is faster, the financial benefits to the bank will be accrued more quickly.

 

Financial Implications: Return on Investment, Based on Internal Cost Savings Only

The Return on Investment for voice recognition applications is positive in the first year, increasing significantly in years two and three. This chart does not include the benefits of the revenue increases, which provides a much more compelling case for voice recognition solution.

 

Financial Implications: Increase in Revenue Due to Higher Customer Satisfaction

This chart shows the annual profit increase due to voice recognition’s impact on the customer life cycle. A dominant part of the increase is available in the later years as the impact of lengthening the average customer life cycle begins to increase revenues.

 

Financial Implications: Increase in Profits Due to Higher Customer Satisfaction

This chart shows the annual profit increase due to voice recognition’s impact on the customer life cycle. A dominant part of the increase is available in the later years as the impact of lengthening the average customer life cycle begins to increase profits.

 

Summary of Assumptions and Methods

The model used is of a generic, smaller financial institution. Although specific banks may differ, such differences can easily be accounted for to better understand the specific impact of Voice Recognition on an individual bank. 

In providing this Business Impact Analysis, Primary Matters has:

  • Created a model of a typical small financial institution with 200,000 customers.
  • Assumed that each customer contacts the center one time every two months.
  • Modeled the likely impact of a voice response solution on the customer contact centers as well as its potential impact on the customer base.
  • Linked this to a simple revenue model for the example line of business.
  • Created a Baseline and Scenario representing the before and after conditions.

The financial institution has customers using Credit Card and Retail banking services. In this study, the voice recognition solution affects these businesses in several ways. Details of the calls, volumes and changes in these due to the solution are provided later in this document.

For the revenue and product cost analysis, it is assumed that the improvements in customer satisfaction from better service will lead to:

  • The average customer life cycle lengthens for each line of business due to better customer service from 48 months to 60 months.
  • Increasing the average customer life cycle changes each line of business in the following ways:
    • The installed base of active customers becomes larger since customers are churning at a slower rate.
    • The revenues increase in line with the increase in the installed base.
    • The monthly product cost increases because there are more products to support in the installed base.
    • Profitability of the bank increases as most profits are made in the latter part of the customer life cycle. The ‘new customer acquisition’ costs are covered in the first part of the life cycle.

 

Assumptions about Customer Contact Center Agents, Supervisors and Operations Personnel

Contact Center Agents Compensation and Benefits

Customer service agents receive an average compensation of $13.00 per hour and work a 40-hour workweek. They are provided full benefits, two weeks of vacation, 10 holiday days and require three weeks of new agent training at the start of their employment. There is one week per year of ongoing agent training. The average job duration is 24 months.

Contact Center Supervisors Compensation and Benefits

Supervisors receive an average compensation of $17.00 per hour and work a 40-hour workweek. They are provided full benefits, two weeks of vacation, 10 holiday days and require three weeks of new agent training at the start of their employment. There is one week per year of ongoing agent training. The average job duration is 30 months.

Operations Personnel Compensation and Benefits

Operations personnel are those who manage, maintain and run the technology for the bank or credit union. Operations personnel receive an average compensation of $55,000 per year and work a 40-hour workweek. They are provided full benefits, two weeks of vacation, 10 holiday days and require three weeks of new agent training at the start of their employment. There is one week per year of ongoing agent training. The average job duration is 30 months.

 

Assumptions and Profile of the Financial Services Company’s Retail Banking Products

A simple, installed base and per customer revenue model is used in this analysis. Each customer has a Retail Banking account, offering checking, savings and money market services, and a credit card account. The average revenue and costs of supplying each of these accounts, excluding the costs of the customer contact center and IVR applications follows: 

 
Summary of Monthly, Per Customer, Services Revenues and Product Costs to the Bank
Revenue Product Costs Contribution
Basic Checking and Savings Accounts $ 1.67 $ 1.00 $ 0.67
Loans $ 12.50 $ 8.83 $ 3.67
Credit Cards $ 9.75 $ 2.00 $ 7.75
_______ _______ _______
TOTAL $ 23.92 $ 11.83 $ 12.09
 

The details underlying the revenues and costs per customer are detailed below.

New Customer Acquisition Costs and Average Active Customer Life Cycle

The average cost to obtain a new customer is $120. This cost includes marketing and sales-related costs as well as new account set-up costs. The average customer life cycle - the time that the individual is a customer and that their accounts are actively used (thus creating revenues and profits for the bank) is 48 months.

Detailed Assumptions: Credit Card Account Revenue & Product Costs

 
Summary of Credit Card Revenue and Product Costs to a Bank
Monthly Revenue per Customer $ 9.75
Monthly Cost per Customer $ 2.00
Monthly Contribution to the Bank per Customer $ 7.75
 

 

Credit Card Revenue Components to a Bank:
Revenue for Credit Card Purchases
Average credit card purchases per month $500
Percent of Average Transaction Value going to the financial institution 0.75%
Monthly Revenue per Account $3.75
Revenue for Credit Card ‘Loan’ Balances
Average Credit Card Balance per Month $300
Annual Interest Rate Percentage 15%
Monthly Revenue per Account $4.50
Annual Fee $18.00
TOTAL Monthly Revenue per Credit Card $9.75
Credit Card Product Cost Components to a Bank
Monthly Account Product Costs $2.00

 

Detailed Assumptions: Summary of Banking Account and Loan Revenues and Product Costs

Summary of Banking Account and Loan Banking Revenue and Product Costs per Customer
Monthly Revenue per Customer $14.17
Monthly Cost per Customer $ 8.83
Monthly Contribution to the Bank per Customer $ 7.34

 

Revenue Components for a Customer
Account Balance Interest Revenue
Average account balance per month $500
Annual percent interest income to the financial institution 4.00%
Annual Revenue per Account $20.00
Monthly Revenue per Account $1.67
Loan Revenue per Customer
Average Loan Balance per Month $1,200
Annual Interest Rate Percentage 10%
Monthly Loan Revenue per Account $10.00
Loan Processing Fee Revenue per New Loan $150.00
Percent of Customer Base getting new loans per year 20%
Monthly Average New Loan Processing Fee/Customer $2.50
TOTAL Monthly Retail Banking Revenue per Customer $14.17

 

Product Cost Components (exclusive of the contact center IVR and Agent Costs) for a Retail Banking Customer
Account Balance Costs per Customer
Monthly Product Costs $1.00
Loan Costs per Customer
Average Annual percent Cost of Funds to Bank 5.5%
Monthly Cost of Funds for Loans $5.50
Monthly Loan Product Costs $1.50
Average New Loan Processing Fee Cost to Bank $50.00
Monthly Average New Loan Processing Fee Cost per Customer $0.83
Total Monthly Loan Product Costs per Customer $7.83
TOTAL Monthly Retail Banking Cost per Customer $8.83

 

Contact Centers Annual Operating Budget Before and After the Addition of Voice Recognition

This budget comparison shows the pre- and post- voice recognition contact center budget. There is a material impact on the cost side of a bank’s major lines of business.

 

Baseline (Before Voice Recognition Solution) Operations Budget

 

Scenario (After Voice Recognition Solution) Operations Budget

 

ROI Based Only on Operations Cost (Contact Center Cost Savings)

This chart shows the ROI for the voice recognition solution based only on the cost savings in the Contact Center. The investment is justified solely on the cost savings, even though the most material benefits are the revenue and profitability increases to the Bank.

NOTE: For ROI Analyses a Cash Budget is used. The annual and other budget figures differ from other charts in this report since this is a cash-based budget, and the others capitalize the investment.

 

ROI Based on Total Impact, Including Operations Costs, Revenues and Product Cost Changes

 

System Investment, Systems Integration, Maintenance and Operations Personnel Expense Details

 

Headcount Comparison

This Full Time Equivalent Agent Headcount comparison shows the pre- and post- voice recognition Contact Center staffing for Agents, Supervisors, and Operations Personnel.

 

 


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