Credit Scores and Credit Reports, by Evan Hendricks

Chapter 8

Making & Mixing Credit Reports

Rumor travels faster, but it don't stay
put as long as truth.

- Will Rogers
"Politics Getting Ready to Jell"
The Illiterate Digest (1924)

Like many caring sons, David Jokinen grew closer to his mother in her final years. Throughout his 40s and 50s, Jokinen had spent a great deal of time traveling to Europe and Canada as a consultant and author on urban affairs, engineering, and architecture.

But as his mother entered her 90s, Jokinen, a self-employed businessman, spent more and more time looking after her affairs. He was a co-signer on her three credit cards. When she died at the age of 95 in April 2001, Jokinen immediately sent his mother's death certificate to the three credit card issuers, one of which was Chase Bank. All three said it was "fine" for Jokinen to now use the card in his own name. A month later, Chase contacted Jokinen and asked for another copy of the death certificate. Jokinen asked what had happened to the copies he had mailed and faxed. The Chase representative said he didn't know, and surmised that it probably was misplaced or lost.⁹²

Several months later, he learned that Equifax and Experian could not calculate a FICO score because - according to their records - Jokinen was "dead." The incident prevented Jokinen from obtaining a mortgage for which he had applied. After some digging, he discovered that Chase had confused his Social Security number with his mother's death.⁹³ In a figurative sense, the linkage was fatal. He had now become the victim of a "mixed file."

Thus began a two-year nightmare in which the credit bureaus were either unable or unwilling to correct an obvious error. Chase Bank employees suggested to Jokinen that it wasn't worth the bank's time to fix such "little" mistakes.

Please, Tell Them I'm Alive

In a scene out of a science fiction movie, Jokinen, after some cajoling, persuaded managers in the Houston office of the U.S. Social Security Administration to write a letter declaring that he was in fact alive, and not dead. As he awaited the all-important letter, word quickly spread through the staff offices and the waiting room. Jokinen's strange request was translated into Spanish, Vietnamese and Chinese for curious onlookers. When SSA officials finally handed him the letter, all those in the waiting room stood and applauded.⁹⁴

Meanwhile, Jokinen said that because of credit report errors, he was spending a minimum of seven hours a week, paying thousands of dollars in higher interest rates, and had lost out on hundreds of thousands in investments from prospective investors who were shocked to see that he was "dead."

⁹² Testimony of David Jokinen, "The Accuracy of Credit Report Information and the Fair Credit Reporting Act," U.S. Senate Committee on Banking, Housing, and Urban Development, July 10, 2003
⁹³ In fact, this can happen even without the reversal of SSNs. If one account holder dies and the account is coded as "deceased," (which sends it to the estate claims division of any credit card operation) the account will report on all account holders as "deceased."
⁹⁴ Id.

Bad as these damages were, he said the worst part was the emotional toll it took on him. As he told the Senate Banking Committee on July 10, 2003:

"I was my mother's only child. We were quite close. My mother had Tuberculosis during the 2nd World War. She was confined to a T.B. sanitarium in Detroit for 3 years. My mother left our house when I was five years old. I never saw her in person again until I was 8 years old. In 1943 the T.B. doctors removed half of my mother's lung. During her recovery, the T.B. doctor told my mother she probably only had 2 to 5 more years to live. That's because she was now living on only half a lung, and it would eventually wear out. That was when she was 39 years old. She actually lived to 95. Because of Chase Bank's stupidity I have now relived her last few painful years over and over again - while trying to get this mess cleared up."⁹⁵

Jokinen said he only began to see action after he found a lawyer and filed suit under the FCRA.⁹⁶ His appearance before the Senate Banking Committee inspired media coverage that put added pressure on Chase and the credit bureaus to clean up his reports.

⁹⁵ Id.
⁹⁶ Jokinen's was initially represented by attorney Russell von Bustring, of Houston, Texas, and later retained the services of The Tien Law Firm and Williams and Bailey, both of Houston. The case settled for a confidential sum.

The System

Many people believe that the three major consumer reporting agencies (CRAs) — Equifax, Experian, and Trans Union — maintain an electronic folder on us, similar to the folders in which we store our documents on our personal computers. As we open and close our accounts and credit grantors furnish monthly updates on our payment performance, the CRAs simply add the updated information to our folders.

In fact, there are notable distinctions among the three. Equifax and Trans Union tend to follow the file-building model, while Experian was said to store information in a more dynamic database. Perhaps most important, the CRAs only pull together an actual credit report or calculate a credit score when either a credit grantor, employer, or some other user asks for your report, or when you ask for your own report. In this sense, it is more accurate to say that credit reports and credit scores are made "on the fly." And, the content of the credit report often depends on what identifying information the credit grantor provides when asking for it.

The credit grantors, or "furnishers," each month provide the CRAs with millions of bits of data on consumers' payment histories. Some major creditors are connected to the bureaus and can report to them online. Many others submit a monthly magnetic tape. An important issue is whether the creditor reports to the bureau using the more modern "Metro 2" format. This format permits the creditor to fill in data fields corresponding to the identifying "Credit Header" and the "Account Column Title Description" we listed in Chapter 5 (e.g., balance, credit limit, account number, type, and status). But many creditors still used the old, less precise Metro I format.⁹⁷

⁹⁷ Trans Union announced that all customers must report using the Metro 2 format by December 31st 2003. According to the Web site of The Service Bureau, "all bureaus will require the Metro 2 format in the near future." http://www.servbur.com/index.html

The three CRAs each store this information in their own massive database. The CRA databases include data on virtually all American adult users of credit-an estimated 205 million people.⁹⁸

A credit report is not fully assembled until the CRAs have a reason to assemble one. For instance, when a consumer applies for credit, the credit grantor or "subscriber" relays to the CRA identifying data from the consumer's credit application, at a minimum, name and address, often the SSN, and sometimes date of birth. (It's worth noting that the CRA can return a credit report to the credit grantor without an SSN.)

This is when the key moment occurs. Applying this identifying or "indicative" data, the CRA's algorithm then decides which information in the database relates to or "matches" that consumer, and then "returns" to the credit grantor (subscriber) a consumer credit report consisting of this information. Thus, it is the algorithm, or "business rule," that decides which data go into your credit report.

The Search Logic/Algorithm

In the Matthew Kirkpatrick trial cited in the previous chapter, Equifax Vice President Phyllis Dorman said that when "building a file" after receiving data from a creditor, or when deciding what data to include on a credit report that will be disclosed to the creditor, the first factor considered by the Equifax system was geographic region.

Then its "matching algorithm," known as L90, relies on 13 matching elements. Two of the elements that constitute a distinct category are: (1) exact Social Security number (SSN) and (2) partial SSN (meaning that most, but not all digits are the same).⁹⁹

⁹⁸ www.experian.com/small_business/knowledge.html, visited 2/18/04
⁹⁹ Testimony of Phyllis Dorman, Matthew Kirkpatrick v. Equifax Credit Information Services, U.S. Dist. Ct., Oregon, CV-02-1197-MO; 1/20/05

The remaining elements are (3) last name, (4) first name, (5) middle name, (6) suffix, (7) age, (8) gender, (9) street number, (10) street name¹⁰⁰, (11) apartment number, (12) City, state and zip, and (13) trade account number.

There is a very important difference in how the system works when you ask to see a copy of your own credit report, as opposed to how it works when a subscriber asks the CRA for your credit report. One reason for this is that the CRAs have a duty to ensure that they do not give your credit report to anyone who does not have a permissible purpose to see it-particularly someone who is trying to impersonate you or otherwise do you harm. Accordingly, when you ask for your own report, you are required to give extensive identifying information to authenticate yourself-to prove that you are really you. This also enables the CRA's algorithm to more concisely assign the proper accounts to your credit report.

However, it can be a very different story when a credit grantor or other subscriber asks for your credit report. For starters, the setting is different. To have instant access to credit reports, subscribers must sign contracts pledging to only use credit reports for permissible purposes, to abide by other restrictions, and comply with the FCRA. CRAs look at their subscribers as members of a trusted circle, who know and play by the rules.

¹⁰⁰ Some algorithms may only use the first 4-to-6 characters of the number-address field, which would mean that "123 Main Street" would match "123 Mainwright Street."

More importantly, the priorities are different. Since the subscriber is buying the credit report in order to decide whether or not to grant you credit, the CRA wants to ensure that it does not leave out anything that could be relevant to that decision. After all, if the CRA failed to include evidence of late payments in your credit report, and you default, the credit grantor is going to blame the CRA. Another factor is the credit grantor might only have limited information about the consumer, like name and address, and no SSN, or its employee might have written down the SSN incorrectly. Therefore, the CRA seeks to maximize disclosure of any possible information that might relate to the consumer about whom a subscriber inquires. This becomes trickier when the CRA conducts the search based upon very limited, or even imperfect, identification information.

To accomplish this, the CRAs' algorithms are designed to accommodate such errors as transposed digits within SSNs, misspellings, nick names, and changed last names (women who marry), and different addresses (people who move), by accepting "partial matches" of SSNs and first names, and in some circumstances, assigning less importance to last names.

Thus, while you must provide an exact match of your SSN to obtain your own credit report, a subscriber can still obtain your credit report even if there is a match of only seven of the nine digits in your SSN. What's more: if the SSN on the credit application exactly matches yours, the CRAs' algorithms often will tolerate major discrepancies in last name, street address, city, and state.

Accordingly, it's quite possible that the "subscriber" credit report sent to the company holding your credit application will have more data than the credit report you obtained directly from the credit bureau. There have been occasions when a subscriber will reject an application for credit based on information in a credit report, but when the consumer gets her own report, the information isn't there. It was only in the subscriber report.

In their defense, credit bureaus argue their systems, more often than not, properly mix data into one consumer's report, thereby increasing accuracy. For example, sometimes Joseph A. Smith applies for credit in his full name, but sometimes he leaves out his middle initial. Other times he only uses "Joe." Then he moves to another state. These cases are common, and the current approach maximizes the likelihood that the full credit history will be passed on to credit grantors.

Multiple Files

Another result of this approach is "multiple files," meaning that the request for one consumer's credit report results in the return to the credit grantor of more than one report. These multiple files, also referred to as fragmented, or "frag" files, often pertain to more than one person; each multiple receives its own credit score. The credit grantor can specify whether he wants the credit bureau to return "multiple files," or just the "best," or most likely, single file. Remember, in their December 2002 study, the Consumer Federation of America and National Credit Reporting Association found that in 10% of the cases, instead of there being three credit reports for each individual (one each for Equifax, Experian and Trans Union), a fourth, or fifth, or even sixth credit report would be returned, most of which had separate credit scores.

These reports were not duplicates. In some cases, the "extra" credit reports clearly were reporting the credit activity of an entirely separate person, as none of the accounts matched with those on the three primary reports. But it was very common for the additional report to contain a mixture of credit data, some of which belonged to the applicant and some of which clearly did not. In still other cases, applicants had split files that appeared to be the result of applying for credit under variations of their name.

Partial Matches

In addition to multiple files, the acceptance of "partial matches" by CRA algorithms is known to cause "mixed files"-the mixing of one consumer's credit history into the credit report of another-as well as other inaccuracies. Such problems became the leading cause of consumer complaints to the FTC in the early 1990s, prompting formal investigations, consent agreements with all three CRAs, and Congressional reform in 1996 and 2003 (see Chapter 10).

Some individual examples help highlight how a consumer's credit report can become mixed with that of a total stranger. Myra Coleman was a longtime resident of Itta Bene, Mississippi. But unbeknownst to her, a woman in Madera, California, named Maria Gaytan, applied for credit, apparently using Ms. Coleman's SSN. Because the use of Ms. Coleman's SSN created an "exact match," Trans Union's algorithm proceeded to disregard virtually all other identifying data. It "concluded" that Ms. Gaytan was in fact Ms. Coleman and allowed Ms. Coleman's credit report to be disclosed in response to the application, thereby enabling Ms. Gaytan to obtain credit. Ms. Gaytan's unpaid bills were then included in Ms. Coleman's credit report.

In pre-trial discovery, Ms. Coleman's attorney, Sylvia Antalis Goldsmith, was able to uncover how the Trans Union algorithm worked in this instance. Trans Union's (TU) officials testified that because of the exact match of the SSN, the algorithm only needed to find enough common letters in the first name to conclude that the two people were the same. Thus, "Myra" and "Maria" both have the letters "M," "R" and "A." TU believed its algorithm needed to accommodate what it considered a common occurrence: women marry and change their last name, and change residences.¹⁰¹

Another example was Jason Turner, a 19-year-old resident of Birmingham, Alabama. He was disappointed when he was rejected by Capital One after applying for his first credit card. When he obtained his Equifax report, Turner, who was born in 1982, was surprised to see that there were several accounts paid late, including one that dated back to when he was 14-years-old. Turns out that Equifax had merged him with another Jason Turner, born several years earlier, who at one point lived in Florida. A key factor was that there were only two digits different in their SSNs.

¹⁰¹ Coleman v. Trans Union (U.S. Dist. Ct. Mississippi). Ms. Coleman won a small jury award. Goldsmith was with the firm of Murray and Murray in Sandusky, Ohio until March 2005.

Thus, it appeared that the seven-out-of-nine digit SSN match, coupled with the identical name and possibly a regional commonality, was sufficient for the Equifax algorithm to disregard date-of-birth and location of residence. Because young Jason Turner was a "newcomer" to Equifax and "didn't have a file," its system kept assuming that the two Jason Turners were one and the same, and repeatedly dumped the older Turner's negative history onto the younger Jason's credit report.¹⁰²

A Never-Ending Mix

Judy Thomas was a realtor in Klamath Falls, Oregon, who, upon discovering errors in her credit report in 1996, sent a dispute letter to Trans Union. Trans Union said it would correct the mistakes. But after applying for a mortgage in 1999, Thomas learned that the 1996 errors, plus new ones, were back on her credit report, delaying approval of her mortgage. Through litigation, Thomas learned that her credit report was polluted with negative information from the credit history of Judith Upton, of Stevenson, Washington, whose SSN was only different by one digit. It appeared the similarity in the SSNs and the first names, (and possibly regions), were enough for the TU algorithm to override all other discrepancies.¹⁰³

These are only four of the thousands upon thousands of the mixed file cases that have occurred since the early 1990s. They illustrate how the use of algorithms that tolerate "partial matches" contributes to the regular mis-merging of data. In all of these cases, the victims only learned about the errors after they had been rejected for credit.

¹⁰² Jason Turner was represented by Christopher Kittell, of Webster Gresham & Kittell, Clarksdale, Miss., and Penny Hays, Birmingham, Ala. The case settled for a confidential sum.
¹⁰³ In 2002, a federal jury in Oregon awarded Thomas $5 million in punitive damages and $350,000 in compensatory damages. The punitive award was reduced to $1 million. Trans Union paid. Thomas was represented by Portland attorneys Robert Sola and Michael Baxter.

How The Algorithm Helps Identity Thieves

In important ways, the CRAs algorithms have helped identity thieves. In "true-name fraud," the key moment occurs when the CRA discloses the innocent victim's credit report to a subscriber holding the identity thief's application for credit. This disclosure enables the fraudster to obtain credit in the name of the innocent victim.

Identity thieves often enter mistaken data when they fraudulently apply for credit. But if they have obtained the victim's SSN, it will help override other discrepancies in the application and convince the CRA algorithm to disclose the victim's credit report. Even if there are mistakes in the SSN, the "partial match" tolerance within the algorithm still gives the fraudster a chance of triggering release of the credit report.

The State of California, a pioneer in identity theft prevention, tried to combat this problem by passing a law that required credit grantors to match at least three identifiers before being allowed to receive the credit report. In 2003, a few years after the law was enacted, at least one CRA complained that the new law was interfering with the granting of instant credit in about 12 percent of the cases. But the CRA had no data indicating what percentage of these might have been identity theft. Some privacy experts felt the law might be accomplishing something positive: even if the applicant was not an identity thief, the incident alerted consumers of possible discrepancies in their credit reports deserving attention.

Reinsertion

Another troubling aspect about these cases is the likelihood that errors will reappear, or be reinserted into the credit report, after they are deleted. This often is caused by flaws in the system. In fact, the consent agreements with the FTC and State Attorneys General, as well as the 1996 Amendments to the FCRA, required that CRAs take specific steps to either prevent reinsertion or to notify consumers that it had occurred and justify it.

The CRAs first defense against reinsertion is a process known as "cloaking" or "suppression." If credit grantors are not careful to delete all inaccurate information from their systems, that information could be re-reported to the CRAs in the course of the routine monthly updates.

Anticipating this problem, the CRAs created cloaking so it could flag previously-deleted trade lines and then, if they were re-reported by the credit grantors, they would be "cloaked" so as not to reappear on the consumer's credit report. In other words, under the current system, it appears that a CRA cannot afford to actually delete inaccurate data from its database because it will lose its ability to flag that data when credit grantors mistakenly re-report them.

But the cloaking system is far from perfect. Many of the major credit grantors have more than one "subscriber number" they use to identify themselves to CRA computers. There have been cases in which the cloaking procedure was only pegged to one subscriber number. So if the credit grant-or reported the data under a different subscriber number, then the cloaking procedure would not be triggered. Moreover, if there are discrepancies or a change in the sub-scriber's name, that too will bypass the cloaking procedure.

A second way that information reappears relates to debt collections. Even when some accounts are the result of a mixed file and are deleted, they still sometimes are sent or sold to collection agencies. Once the collection agency acquires an account, it begins reporting it to the CRAs, usually with a different account number, enabling it to bypass the cloaking system.¹⁰⁴

¹⁰⁴ There is some question whether "cloaking" frustrates legitimate re-scoring. Ruth Koontz, of Lenders' Credit Services, Inc., said there have been times when the only delinquent account on a credit report was removed during a re-scoring, yet the score did not improve. This raised the question as to whether "cloaked accounts" affect scoring and the CRAs don't realize it.

Archived 'Monthly Snapshots'

If previously deleted information were wrongly reinserted into a credit report or there were other inaccuracies dating back months or even years, one of the challenges facing consumers is finding out when the reinsertion occurred. More generally, consumers on their own have no practical way of knowing what their credit reports looked like in the past. If they were denied credit based upon a "subscriber" version of their report, they cannot be sure what information that version contained unless the credit grantor hands over its copy.¹⁰⁵

The fact is that Equifax and Trans Union maintain historical archives that allow them to go back and see what your credit report looked like in times past. However, for the most part they have only produced records from these archives after being sued by consumers for alleged FCRA violations. Attorneys representing those consumers were able to obtain them as part of discovery, which requires companies to disclose internal records that are relevant to a lawsuit. However, in some cases, the CRAs have fiercely resisted having to disclose these records or have tried to charge excessively for producing them.

In essence, these archival records are "monthly snapshots" of the information in the database going back as many as 10 years. At Equifax, they are called "Frozen Data Scans;" and at Trans Union, "Name Scans." (Experian's system does not keep monthly snapshots in the same way.)

¹⁰⁵ For many years, CRA contracts prohibited credit grantors from showing their version of the credit report to the consumer about whom it pertained.

Navigating The Monthly Snapshot

The monthly snapshots are difficult to decipher for the untrained eye. They contain dozens upon dozens of lines of raw data and show how the CRA organizes information into "data fields." According to deposition testimony in Carol Fleischer's case, one Trans Union "Name Scan" showed how data on her and Ms. Cassidy were mixed within the TU database. At the top of Trans Union's Name Scan for April 2000 was Carol Cassidy's name and correct address, and then showed Ms. Fleischer's address as Ms. Cassidy's previous address. It also showed that Ms. Fleischer's SSN was listed as Ms. Cassidy's SSN (only the last digit of the nine SSN digits was different). It then showed many of the derogatory trade lines stemming from Ms. Cassidy's activities. It showed TU had maintained data on Ms. Cassidy ("File Since Date") since November 1985.

Farther below in the TU Name Scan, it showed Ms. Fleischer's correct name, address, and SSN, but a "File Since" Date of January 2000. The testimony indicated that the "new" file on Ms. Fleischer was created by an inquiry from a subscriber who was checking her credit report after Ms. Fleischer had applied for credit. In other words, whenever Ms. Fleischer applied for credit, it would create a "new file" on her (hence the new "File Since Date"). But then the system would proceed to merge all of Ms. Cassidy's and Ms. Fleischer's data together in subsequent months. Despite repeated disputes by Ms. Fleischer, TU's algorithm was unable to see them as different people whose data should be kept apart.

Valuable Snapshots

The monthly scans proved valuable in a class action lawsuit against all three CRAs on behalf of millions of consumers whose credit reports listed an account as "Included in Bankruptcy," even though the consumer never filed for bankruptcy. (The consumer was often the co-signer on an account whose spouse or ex-spouse had filed for bankruptcy.) In that case, the scans enabled the CRAs to identify the number of class members and pave the way for a settlement.¹⁰⁶

As Thomas C. Harney, a Kilpatrick & Stockton attorney representing Equifax, testified in a September 2003 Fairness Hearing, "...The only way we could get this information was to go back to these monthly archives or snapshots, also called cuts, that we've talked about before and take this snapshot in time."¹⁰⁷

As mentioned before, the CRAs sometimes resist disclosing monthly scans, despite the fact that they were requested in discovery. In January 2004, U.S. District Judge T. John Ward scolded Lewis Perling, a Kilpatrick & Stockton attorney representing Equifax, for not producing frozen scans by the court's deadline, and for not producing witnesses and other documents.

Noting that Equifax should have coughed up the evidence months earlier, Judge Ward ordered Perling to produce within 10 days all evidence subpoenaed by plaintiffs, including "those stored by electronic means... all of these screens, frozen screens."¹⁰⁸

Judge Ward threatened to create special procedures for Kirkpatrick & Stockton's out-of-town attorneys to appear in his court if there was not immediate compliance. Turning to Perling, he added, "Since I have ordered you specifically, and if you fail to comply, I will still have jurisdiction over your person, and I will order you back over here for a contempt hearing, and when I do those kinds of things, I can assure you, you will need to bring your toothbrush.

¹⁰⁶ Franklin E. Clark, et al. v. Experian, et al.: U.S. Dist. Ct. - South Carolina - C.A. No. 8:00-1217-24. A modified settlement had not received final approval at the time this book went to press in spring of 2004.
¹⁰⁷ Id., "Fairness Hearing," September 23-24, 2003
¹⁰⁸ "Transcript of Hearing On Plaintiffs' Motion To Compel," January 13, 2004, Deborah Moore v. CSC Credit Services, Inc., et al.: U.S. Dist. Ct. - Eastern Dist. of Texas - Civ. Dock. No. 2:02-CV-303. Moore was represented by David Szwak of Shreveport, Louisiana.

I do not tolerate your kind of behavior sir."¹⁰⁹

The 'Do-Not-Confuse' Statement

The FCRA gives all consumers the right to place a statement on their credit report to further explain its contents or to prevent some harm. Carol Fleischer, of Ann Arbor, Mich., thought she was being wrongly confused with another woman, so she placed a "Do Not Confuse Me With Anyone Else" statement in her credit report, which was duly recorded in the Trans Union Name Scan. Some people might think that placing such a statement would alert TU not to mix her file with someone else.

In litigation, however, Ms. Fleischer learned that was not the case. TU's Regina Sorenson testified that the purpose of the "Do Not Confuse" statement was not to prevent further mixing; instead she said, "It's to alert potential creditors that there may be more than one consumer with similar identification in the system."

TU's Lynn Romanowski also testified that Ms. Fleischer's "Do Not Confuse" statement needed to be on both her file and on Ms. Cassidy's file to prevent improper mixing.

Romanowski: A consumer statement present on both files would prevent those two files from being permitted to combine.

Szwak: So if a "do not confuse statement" only appears on one file but not the other, it would still permit the combination of those files?

Romanowski: At this point in time, yes, according to this scan, yes.¹¹⁰

It's safe to say that nobody outside of Trans Union had any idea that to prevent the mixing of files you needed to place the "Do Not Confuse" Statements in your file and the file of a total stranger.

¹⁰⁹ Id.
¹¹⁰ Deposition of Lynn Romanowski, Fleischer v. Trans Union, et al.: U.S. Dist. Ct. - Eastern Dist. of Michigan - Case No. CV 02-71301

Organizational Structure

Like all major corporations, the CRAs are organized into various departments and divisions. Trans Union's (TU) organizational infrastructure helps illustrate its approach and operations. TU's main credit reporting database is called CHRONUS. Within TU, there are at least three major departments or divisions that interact with CHRONUS. One department, headed by William Stockdale, is responsible for the manner in which CHRONUS receives consumer data from furnishers and integrates those data. Another department is responsible for the "rules" or algorithms by which CHRONUS assembles and returns credit reports in response to subscriber inquiries. A third department, consumer relations, responds to consumer request for copies of their credit reports (disclosure), handles consumer disputes, and conducts reinvestigations.¹¹¹

As we will see in the next chapter on "reinvestigations," when a consumer discovers inaccuracies in her credit report, the responses of all three departments likely will determine whether the inaccuracies are corrected and/or deleted, and whether they will reoccur (re-mixing and/or reinsertion).

There have been instances when each of these three departments were not sufficiently familiar with each other's practices and procedures to ensure that corrections were not undone.

For instance, let's say TU's consumer affairs department corrects a consumer's mixed file, removing all of the data generated by the "other" person. However, if the consumer affairs department does not know that the "partial match" algorithms created by the other department will continue to cause mixed files in the future, then they are not prepared to do all that is necessary to ensure that a consumer's credit report remains accurate.

¹¹¹ From depositions in Fleischer and Thomas, op. cit.

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