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This chapter is from the book

Credit Controversies

Controversies over credit scoring continue to rage. Here are just of few of them.

Credit Scoring's Vulnerability to Errors

No matter how good the mathematics of credit scoring, it's based on information in your credit report—which may be, and frequently is, wrong. Sometimes the errors are small or irrelevant, such as when your credit file lists a past employer as a current employer. Other times the problems are significant, such as when your file contains accounts that don't belong to you. Many people only discover this misinformation after they've been turned down for credit.

The credit bureaus handle billions of pieces of data every day, so to some extent, errors, outdated, and missing information are inevitable—but the credit-reporting system often makes it difficult to get rid of errors after you spot them.

The problem is only getting worse. The rise in automated lending decisions means a human might never see your application or notice that something's awry. The explosion in identity theft, with its 10 million victims a year, means more bad, fraudulent information is included in innocent people's credit files every day.

Patricia of Seattle, Washington, tells of the ongoing horror of becoming a victim:

"I've always been careful about protecting my identity. Unfortunately, when I was trying to purchase a home, the real estate broker, to whom I'd given my application with birth date and Social Security number, had her laptop stolen. My worst fears came true when, four months later, I suddenly had creditors calling me like crazy asking why I wasn't paying on accounts that were just recently opened in my name. On top of this, I learned the criminals had also stolen my mail with preapproved credit cards. This has created a nightmare of time, work, and frustration trying to clean up my credit history. It's been over two years now, and I'm still working with the major credit-reporting agencies as we speak."

Credit Scoring's Complexity

You're being judged by the formula, so shouldn't it be easy to understand and predictable? Not even credit-scoring experts can always forecast in advance how certain behaviors will affect a score. Because the formula takes into account so many variables, the best answer they can muster is: "It depends."

The variety of different scoring formulas and different approaches among lenders can confuse matters even further.

Lenders can get scores calculated from different versions of the FICO formula. They also can have in-house formulas that incorporate a FICO score along with other information that might punish or reward certain behaviors more heavily than the FICO formula does on its own. Some call the result a FICO score, even though that's not technically correct.

Not surprisingly, this causes confusion for consumers and mortgage professionals alike.

A.J. Cleland, an Indianapolis mortgage broker, discovered how different scores can be when trying to help a client who had been turned down for a loan by a bank. The bank reported the client's FICO score was 602, whereas the FICO score Cleland pulled for the client—on the same day and from the same credit bureau—was 31 points lower.

"I called my credit provider and was informed that there are different types of reports and different scores," Cleland said. "I thought your score was your score, period."

Credit Scoring's Use for Noncredit Decisions

I mentioned earlier that your landlord or employer might check your credit and your credit score in evaluating your application; however, the most controversial noncredit use of scoring is in insurance.

Insurers have discovered that there's an enormously strong link between the quality of your credit and the likelihood you'll file a claim. They can't really explain it, but every large study of the issue has confirmed that this link exists. The worse your credit, the more likely you will cost an insurer money. The better your credit, the less likely you are to have an accident or otherwise suffer an insured loss.

As a result, more than 90 percent of homeowners and auto insurers use credit scoring to decide who to cover and what premiums to charge them.

That outrages many consumers and consumer advocates who don't see a logical connection between credit and insurance. Julie, a city worker in Poulsbo, Washington, saw her insurances soar after a divorce and subsequent bankruptcy trashed her credit. [2]

"I have had the same insurer for 30 years, never been late, never missed a payment, never had an accident, and never filed a claim—yet now I pay the price of higher rates. I absolutely do not understand how this is fair."

This leads to the final controversy, spelled out in the next section.

Credit Scoring's Potential Unfairness

Developers of credit scoring point out their formulas are designed not to discriminate. Credit scores don't factor in your income, race, religion, ethnic background, or anything else that's not on your credit report.

But it's not clear if the result of those formulas actually is nondiscriminatory. Some consumer advocates worry that some disadvantaged groups might suffer disproportionately as a result of credit scoring.

Among their theories: People who have low incomes or who live in some minority neighborhoods might have less access to mainstream lenders and thus have worse credit scores. The lenders these disadvantaged populations do use—finance companies, subprime lenders, and community groups—might not report to credit bureaus, making it harder to build a credit history. If these lenders do report to the bureaus, their accounts might count for less in the credit-scoring formula than those of mainstream lenders. Seasonal work is also more prevalent in some neighborhoods, which can lead to a higher rate of late payments in the off-seasons.

Even if credit scoring doesn't discriminate against groups, it might discriminate against you.

No credit-scoring system is perfect. Lenders know that their formulas will reject a certain number of people who actually would have paid their bills. Another group will be accepted as good risks, but then default.

If these groups get too large, the lender has trouble. When too many bad applicants are accepted, the lender's profits plunge. When too many good applicants are rejected, the lender's competitors can scoop them up and make more money.

But lenders accept a certain number of misclassified applicants as a cost of doing business.

That's little comfort to you, if you're one of the responsible ones who loses out on the mortgage you need to buy a home, or if you end up paying more for it.

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