Understanding, Establishing and Maintaining a Lockbox System System

Richard Richardson, Phoenix-Hecht

Organizations are frequently faced with the need to review their collection systems. Of prime concern in such reviews are the level of float the company experiences, the costs incurred, and the quality of service obtained from the processing vendor. Many times a collection system review results in what is known as a lockbox study.

A lockbox study identifies the optimum number of lockbox sites for a corporation to have, the best locations for these sites, the most efficient assignment of customers to the selected sites and the amount of float in the lockbox system. The study also can be used to evaluate the current performance of an existing lockbox system or fine tune an existing system by reassigning customers among lockbox sites. In recent years, the focus of many lockbox studies has been to downsize overgrown banking networks and to evaluate lockbox networks offered by a single bank provider.

The primary consideration in almost every lockbox decision is minimizing float, the amount of time funds are in the collection process. When evaluating float it is critical to consider only total float (mail time plus availability) rather than drawing conclusions based on either mail time or on funds availability alone.

In a lockbox environment the cash manager can only identify the mail date, deposit date and date of available funds. The time line appears as two segments: mail float and availability float. (Exhibit 1) Mail time is measured from the calendar day of mailing to the banking day of deposit (as long as the mail meets the post office mailing deadline for the day – typically 5 or 6 p.m.). Availability float is measured from the banking day of deposit until the banking day when collected funds are made available to the depositor.

Exhibit 1

The Payment Time Line

Deposit Ticket
Ledger Entry
Postmark Balances
[———- Mail Float ———-][———- Availability Float———-]

Calendar days, business days and banking days do not always coincide. A banking day may end as early as 1 p.m. Deposits made earlier than that time are credited on that calendar day while deposits made after that time will bear a ledger credit date of the following business day.

How Lockbox Mail Differs From Other Mail

Every day the United States Postal Service handles in excess of 300 million pieces of first-class mail. Lockbox mail is included in first-class mail and is referred to as wholesale remittance mail. Wholesale remittance mail represents less than 1/4 of 1% of the total first-class mail volume. Because of the nature of business mail and the special services which most lockbox banks buy from the U.S. Postal Service, this 1/4 of 1% of mail receives very special, expedited treatment.

Most business-to-business mail is sent in standard #10 size envelopes with a machine printed address. This makes a high percentage of it readable on the post office’s most automated equipment, the Optical Character Reader. OCR’s, capable of reading 36,000 envelopes per hour, speed the delivery of mail over less automated processing (about 3,300 envelopes per hour) used to sort handwritten and non-standard mail.

Most lockbox banks have unique five-digit zip codes used only for their lockbox mail. Mail destined for a unique five-digit zip code is sorted out on the first pass at the destination Area Distribution Center (ADC) or Sectional Center Facility (SCF), where banks can immediately pick it up through “caller box service.” Most lockbox mail never goes farther in the postal system than the ADC or similar high level processing facility.

The mail we receive at home or at our offices will undergo one or more additional sorts and be transported one or more additional times before being given to the carrier serving our route or being placed in our local post office box in the early morning. If it doesn’t make that early morning sort deadline, we receive it 24 hours later (possibly 48 hours later over a weekend). Lockbox mail with unique zip codes, caller box service and weekend bank processing should never sit at the receiving post office for more than a few hours.

The Lockbox Study

An organization may undertake a lockbox study by itself or as part of a larger study, frequently called a treasury review, covering any or all components of the cash flow time line. A lockbox study is well suited to a stand-alone analysis, since lockbox sites can be added, deleted or changed without affecting the basic structure of a cash management system.

Lockbox studies are conducted for any of the following reasons:

  • The company is not using lockboxes and receives large dollar checks (averaging $1,500 or more) from its customers.
  • The company’s current lockbox(es) was chosen without performing any type lockbox study.
  • Two or three years have elapsed since the company’s last lockbox study.
  • The company’s remittance pattern has changed since the last lockbox study. Changes can occur due to:
    • Sales growth (or contraction)
    • Changing customer base
    • Acquisition or divestiture of subsidiaries, divisions or product lines
    • Changes at the lockbox bank, in the postal system or in the check collection process
    • The company wishes, for administrative and control reasons, to reduce the size of its banking network
    • A lockbox network offered by a single bank provider is being evaluated as a substitute for an existing multi-bank lockbox network.

Defining the Scope and Objectives

An evaluation of the current system is usually considered part of a lockbox study in that it serves as the benchmark for comparing any alternatives. Evaluating the current system can also be part of an ongoing monitoring program. Fine tuning the system does not change the existing lockbox banks but, rather, changes the customers assigned to mail to each existing lockbox. The result of the study is usually modest volume shifts among the existing lockboxes.

A lockbox optimization study is a complete realignment of the lockbox system. This may be required if the organization has experienced an acquisition, divestiture, or other deterioration in the current system due to major changes in customer payment practices. Customers moving disbursement facilities, changing mailing locations or converting to electronic payments are a few examples.

How To Conduct the Study

Computer models have become an integral part of cash management. They are used to plan investment strategies, forecast cash flows and locate lockbox and disbursement facilities. When one constructs a model, one takes a “snapshot” in time. One examines the real system by taking a data sample over a brief but representative period of time. In a lockbox study this usually takes the form of a sample of the corporation’s receivables over one complete billing cycle, generally one month.

Real systems, however, are not static. They change constantly. Unless great care is taken in the original data collection, the dynamic nature of the system cannot be accurately replicated. The check sample taken in the month of April may be an accurate reflection of that month but it may not reflect what happens to the company during the rest of the year.

The remittance sample is one of the most important aspects of a lockbox study. The improper selection or design of the sample is the largest single cause of error in a lockbox study. It can far overshadow errors relating to the measurement of mail and availability times. The cost of collecting a sample (encoding the envelopes and checks that make up the sample) may represent one of the largest costs in doing a study. Given these observations, here are some important points to consider in selecting a sample:

  • The sample should be reviewed to determine that an accurate, dollar-weighted, geographic distribution has been obtained. If the sample does not accurately represent the major dollar locations from which customers are mailing their remittances, it will invalidate the study. The geographic distribution of the sample is much more important than whether the month or period had high or low sales. If the sales were either unusually high or low, this can be corrected in the model.
  • All large dollar remittances should be accurately accounted for in the sample. Two possible errors can occur here. First, some large customers may have been left out because none of their remittances happened to be received in the period. If this occurs, additional items from another time period should be selected and added to the sample. Second, some customers may be over-represented, in that their items were unusually large or received with greater frequency during the sample period. This source of bias can be adjusted by deleting or adjusting the size of the items.
  • The time period during which a sample is taken should be carefully selected. The period chosen for obtaining the remittance sample does not have to be continuous. A portion of the sample can be taken from the fall and another part from the spring, if the customer base tends to shift due to seasonality. As a general rule, the industry uses a sample period of one calendar month. However, this is not a limitation or constraint of the modeling technology. Sample periods that are longer or broken into intervals should be used if they will make the remittance sample more accurately reflect the geographic distribution of the entire customer base.
  • Given the cost of encoding a check sample, it is not necessary to include every item in the analysis. A stratified sample will provide an unbiased analysis while controlling costs. In a stratified sample the company segregates the largest dollar items and fully represents them in the study. If the larger items represent a significant majority of the dollars (80%), then the remainder of the items may be safely discarded. If the smaller items represent, in the aggregate, a significant number of dollars, the items should be sampled and the sample included in the study. The use of this stratified approach in creating the remittance data will usually reduce the sample encoding costs.
  • The number of items encoded in the sample should reflect the size of the company. That is, the larger the total dollar value of the remittances being analyzed, the greater the number of items that should be in the sample. The reason for this is that as a company grows, the lockbox system grows larger and marginal decisions will be made on smaller differences in float. Given that remittance sample error is one of the principal causes of error in the study, increasing the percentage of dollars included in the sample by increasing the sample size provides more accurate float measurement.

What Data should be Gathered

The following data should be collected from the sample:

  • Dollar amount of the remittance
  • Zip code of the mailing location
  • Routing Transit Number (RTN) of the check
  • Customer Name
  • Postmark date
  • Date deposited
  • Division

Understanding Mail and Availability Times

The heart of all lockbox location models is the estimation of mail and availability float. In order to accurately estimate float, lockbox models depend on surveys of mail times and on bank availability schedules. It is of the utmost importance that these two separate sources of information be considered and dealt with together in order to closely approximate potential lockbox performance.

The mail times used by the computer models come from data measured by Phoenix-Hecht in its Postal Survey. The availability is from a database of corporate availability schedules that interfaces directly with the measured mail times. Each bank’s entire corporate availability schedule and the schedules of the Federal Reserve Banks are encoded and verified in the database. If a schedule quotes fractional availability, e.g. 95% immediate and 5% deferred one day, the fractional portion is ignored. This is done to preserve comparability between banks quoting fractional availability and banks who simply apply chargebacks or adjustments against the account. Some banks use neither charge-backs nor fractional availability. This should be taken into account as a positive factor that improves the relative availability for such banks.

The next step in the process of building an availability database is to create availability times consistent with the measurement of mail times. Availability for lockbox items is dependent upon both the check clearing deadlines and the times at which the envelopes arrive at the lockbox and are processed. For each lockbox a mail arrival pattern is developed, as measured by the Postal Survey, and a schedule of deposits supplied by each bank to the availability schedule. The arrival pattern simply indicates when envelopes were received by the lockbox during the survey by hour of day and by day of week. The deposit schedule simply indicates the earliest possible deposit incoming mail can achieve.

When the model assigns availability for an item, both the drawee point and mail point are considered. For example, an item mailed from New York, received in Atlanta, and drawn on a San Francisco bank can receive a different expected availability assignment than if that same item was mailed from Atlanta. The difference occurs because of the difference between national (New York) and local (Atlanta) mail arrival patterns for Atlanta.

As in the case of mail time, availability is also sensitive to ledger credit deadline of the individual bank. In particular, the percentage of items that are assumed to make the various availability cutoffs shown on the bank’s availability schedule are computed based on the percentage of items that have arrived since the beginning of the ledger credit day. For example, suppose the ledger cutoff is 5:00 p.m. and the availability deadline for immediate credit is 11:00 p.m. Let us assume in this interval of six hours, 23% of the envelopes are received. The availability computed would be .23 times “zero day” funds plus .77 times one day funds, since these items missed the deadline. (zero days = funds available now). Availability is always computed in calendar days. Mail received and processed by the lockbox on the weekend can have a dramatic impact on mail and availability times.

The underlying intent of all this is to make the computation of availability correspond as closely as possible to what a corporation would see on its monthly account analysis statement. However, in order for availability to closely match, several important assumptions must be fulfilled. First, the corporation must be granted the same availability schedule that was used in computing its times. Second, a “processing deposit” must be made to the corporation’s account at the scheduled times reported by the bank. Third, the bank must have processed, for the customer’s benefit, all items received at least four hours prior to each deposit cutoff.

What to Look for in the Analysis

After creating and verifying the remittance sample, the next step in the analysis is the actual optimization process. Generally, this part of the process is almost invisible to the corporation. Of great importance is the analyst or consultant understanding not only the scope and objectives of the study but also the customer’s payment practices, the company’s bank selection criteria and any other special requirements which may influence the analysis.

The actual optimization runs will usually proceed in a stepwise fashion. Each step should narrow the focus so that the most time consuming (expensive) computer runs will be done only for those institutions which are seriously being considered. The usual stages a consultant will follow during the optimization process are:

  • Selection of cities that would be appropriate for lockbox sites using city-average mail and availability data.
  • Individual bank analysis within each selected city to determine float differences and to make adjustments for differences in deposit timing at each bank.
  • Analysis of lockbox networks, if desired, to determine whether they can provide a float or cost advantage. Networks should be compared only to the best system that can be obtained using a traditional lockbox system approach.

How Accurate is the Study?

A lockbox study represents a combination of several assumptions and measurements, each of which can contribute to errors in the final float estimates. The quality and accuracy of the remittance sample is one of the most important aspects of a lockbox study. A small amount of error can also come from statistical variations relating to the mail time and availability databases. The second most important source of inaccuracy arises from differences between actual bank operating procedures and the way such procedures are modeled within the databases. For instance, if a company is receiving only one processing deposit per day and this was not taken into account, the lockbox study’s float estimate may be off by as much as .4 days or more.

As a general rule, typical studies have a “model accuracy level” of approximately .1 day. This implies that if one were to find two solutions whose float times differ by less than .1 day, the float could be considered equal and the selection should be based on criteria other than the float difference. This rule is only a general guideline. Differences of less than .1 day can be meaningful for lockbox systems involving multiple sites. For example, suppose a lockbox is deleted from a solution and the float change is .1 day. If a specific customer area (zip code/routing transit number combination) affected by the site change shows a float change greater than .1 day, the improvement meets the .1 day test and is meaningful. However, if only a few customer areas are affected or the number of remittances coming from these areas is small, then the .1 day rule should be supplemented by a float/cost ratio approach. Specifically, one should look to find anywhere from $1.50 to $3.00 in float value before one would be willing to spend one additional hard dollar in cost.

Monitoring Lockbox Performance

Once a set of lockbox sites has been selected and the company’s customers notified of the new remittance address, a company will want to have some measures with which to monitor the collection performance of the lockbox sites. It may also want to set up a monitoring system for measuring the quality of service, as well.

Many companies set up “report cards” summarizing such factors as processing errors, reporting errors, timeliness of reporting, quality of remittance detail, condition of photocopy package, etc. Each month they track these items, perhaps assign weights to each, and then rank the banks relative to each other or to some established standard. In combination with quality assessments of other bank services, this can be an effective basis upon which to conduct an annual review of bank operating services with each bank.

Tracking Float

Since minimizing float is such an important factor in lockbox service, companies usually develop some simple measures to monitor collection float and other quantitative factors.

Some companies go to the expense of having the bank capture the postmark date and receipt date of each remittance envelope in order to track mail times. While this can be a useful, though expensive, measure over time, it is likely that the mail times will not correlate precisely to the mail times in the model. Postmarks should not be relied on to determine mailing day because postmarks and backdated meter marks can be in error. A better method is to capture date of receipt, and use the time of receipt relative to the bank’s ledger credit cutoff to determine banking day of receipt. Tracking postmark to receipt date (or deposit date) over time can help detect changes caused by customer changes in mailing practices, post office changes, or bank processing changes.

Companies can also monitor total deposits by day of week. If mail or processing slows, it could show up as more dollars being deposited later in the week. Simple calculations from account analyses over time can detect increasing or decreasing float performance. A company can track such figures as average float, average collected balances, or average float as a percentage of ledger balance as long as the account contains only lockbox activity.

The combination of account analysis and bank statement can produce a measure of “average days to collect” by dividing total float for the month by total deposits for the month (or average daily float by average daily deposits). One can calculate this in business days or calendar days as long as the same type of month is used consistently in the calculations.

An endpoint analysis can also be used to calculate average days to collect. Most endpoint analyses will have a summary of dollars by days of float. (Exhibit 2) By obtaining total float from this report and total deposits for the same time period from the bank statement, one can calculate average days to collect.

Exhibit 2

Average Days to Collect



Float ($ – days) 1



x 0 Days = $


1,968,556 x 1 Days = 1,968,556
413,930 x 2 Days = 827,860
31,712 x 3 Days = 95,136
$ 2,599,805

Total Float $ 2,891,552
Total Deposits 2
$ 2,891,552
= 1.11 calendar days รท 1.4 3 = .79 business days
  1. From Endpoint Analysis
  2. From Bank Statement
  3. 1.4 is derived by taking the percent that the “float dollars” for each day are to the “total float dollars”, times the number of days for each number of float dollars.
    (example: ($1,968,556 รท $2,891,552 x 1) + ($821,860 รท $2,891,552 x 2) + ($95,136 รท $2,891,552 x 3) = 1.4

All of these calculations and observed figures can be used to track a bank over a period of time but the difference in ledger credit cutoff times prevents these measures from being valid for bank-to-bank comparisons.

The Lockbox Profile

Another way to track your lockbox performance is through the Lockbox Profile. The Lockbox Profile, which is available directly from the bank, is produced semiannually and should be an integral part of a company’s performance measurement system. The profile includes four report sections: Total Float Comparison, Deposit Impact, Operational Features and Nationwide Comparison.

The Total Float Comparison Report lists the sending states for which the bank shows a float advantage of .1 day or greater than the national average. (Exhibit 3) Float times are stated in calendar days. The assumptions about float calculations (processing scenario) and availability deadlines which the bank can make are also detailed on the report. The comparison is a quick snapshot of the bank’s processing and how it compares to the rest of the country. If compared over time or to other banks, this can reveal strengths and weaknesses of individual banks. Effective lockbox banks should perform better than, or at least at the same level as, the national averages for the areas from which customers send their remittances. If a lockbox is not performing as well as the national averages it is probably time for an optimization study.

Exhibit 3

Total Float Comparison Report

Smoothed Total Float Comparison
(mail plus availability in calendar days)

Sending Bank All Bank
State Results Banks Advantage
NC 2.38 4.43 2.05
SC 2.93 4.66 1.73
VA 3.14 4.35 1.21
TN 3.37 4.39 1.02
GA 2.96 4.28 1.32
MD 3.00 3.92 0.92
KY 3.20 4.13 0.93
DE 3.36 4.26 0.90
AL 3.39 4.56 1.17
FL 3.39 4.46 1.07

The results have been computed for the following processing scenario:

  • Time required to prepare deposit of customers’ items: 4 hours
  • Deposit deadline for same-day ledger credit: 5:00 p.m.
  • Checks are drawn on banks local to the sending state or zip
  • Availability schedule published: 2/92; verified 5/93
    Deposits are assumed to be made:

Deposits are assumed to be made:

Mon. Tues. Wed. Thurs. Fri. Sat. Sun.
4:00 a.m. 1:00 a.m. 1:00 a.m. 1:00 a.m. 1:00 a.m. None 2:00 p.m.
2:00 p.m. 4:00 a.m. 4:00 a.m. 4:00 a.m. 4:00 a.m.
5:00 p.m 2:00 p.m. 2:00 p.m. 2:00 p.m. 2:00 p.m.

The Deposit Impact Report shows results of different deposit schedules on the availability of checks coming into the lockbox. (Exhibit 4) The impact report illustrates the effects of alternative deposit times on a local, regional, and national customer remittance distribution pattern. Often, due to accounting needs, low item volume, deposit costs, concentration deadlines, or other non-treasury factors, the number and timing of deposits are limited. This report helps the financial manager quantify the financial impact of these actions.

Exhibit 4

Deposit Impact on Total Float *

Deposit Schedules Remittances From
Local Regional National
Three per day, plus weekend Base Base Base
Three per day, no weekend +0.18 +0.27 +0.35
Two per day, plus weekend +0.45 +0.18 +0.05
    Mon – Fri
1:00 a.m.
4:00 a.m.
2:00 p.m.
Two per day, no weekend +0.69 +0.49 +0.41
One per day, plus weekend +0.54 +0.41 +0.31
    Mon – Fri
4:00 a.m.
2:00 p.m.
One per day, no weekend +0.79 +0.71 +0.68

The above table shows the increase in total float that occurs when fewer deposits are made than the base assumption. Increases are reported for several alternative deposit schedules and for remittances received from three geographical areas:


Charlotte NC; Winston-Salem, NC; Raleigh, NC; Columbia, SC; Charleston, SC; Greenville, SC;


Alabama, Georgia, North Carolina, South Carolina, Tennessee, Virginia;


All 50 states and the District of Columbia

* The timing and number of deposits, and the characteristics of your corporation’s remittances can cause the total float impact to be different than the example report displayed above.

The last section of the Lockbox Profile, the Nationwide Comparison, compares float results for the lockbox bank to national average float results and calculates the difference (faster or slower for each mail origination point (zip code). (Exhibit 5) Total float, in calendar days, is broken down into mail and availability components.

A number of approaches for monitoring a lockbox have been developed by financial managers. As with any monitoring system, the most successful always include a defined set of criteria to be evaluated, the time frame for the evaluation and a dialogue between the purchaser and service provider.

Exhibit 5

Nationwide Comparison

Comparison of Bank with National Average Smoothed Results (calendar days)

Bank’s Results National Average Bank is:

Zip Codes

Mail Avail Total Mail Avail Total Fast Slow
Ohio 2.94 1.00 3.94 2.94 1.11 4.05 0.11
432 Columbus 2.88 0.98 3.86 2.93 0.97 3.90 0.04
436 Toledo 3.11 1.22 4.33 2.96 1.37 4.33 0.00
437 Zanesville 2.86 1.22 4.08 2.92 1.45 4.37 0.29
441 Cleveland 2.98 0.78 3.76 2.93 0.75 3.68 0.08


The establishment and maintenance of an efficient collection system involves many elements. While pricing, service quality, information needs, and other product features are important, the primary consideration in almost every lockbox decision remains to minimize float. Data and computer models have been developed over the years to help cash managers identify the most favorable number and location of lockbox sites. There is not, however, a single best way for corporations to pursue a lockbox study. Each analysis must be carefully designed and executed to meet the individual circumstances of each company. Special care must be taken to choose the appropriate sample period and sample size, the appropriate modeling technology and assumptions, and the correct interpretation of results.

Cash managers should thoroughly understand the lockbox processing environment of current and prospective service providers, in which ways it is consistent or inconsistent with assumptions made in the analysis, and what impact the inconsistencies will have. Once a system is in place, it should be monitored for float performance, as well as for the timeliness and accuracy of processing. The account analysis, bank statement, end point analysis and daily balance reports can be used to track some fairly simple indicators of float trends within a bank.

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