In an apparent effort to recoup some of the losses suffered under enactment of new financial reform laws, some banks are manipulating the order in which they process bank account transactions to maximize the number of overdraft fees they can charge customers.

Here’s one of the scenarios reported by irate bank customers:

Say you have $500 in your checking account on a day that your bank receives four debits against your account:

$5 latte
$220 groceries
$80 veterinarian
$565 auto insurance

Your total debits for the day total $870 against a balance of $500, overdrawing your account by $370.

If the bank debits the three small purchases totaling $305 (easily covered by your $500 balance) before it processes the larger $565 insurance debit, you would incur a single overdraft fee. However, if the bank debits the larger purchase first, causing your account to be overdrawn, it can charge an overdraft fee for each subsequent debit. At the end of the day, you’ll pay 4 overdraft fees instead of one! At $35 a pop, that’s a loss of $105.

Bank customers expect their accounts to be debited in the order purchases are received. Consumer credit repair experts, however, have found that many banks — 25% according to a 2006 FDIC survey — shuffle debits received in the same day to maximize overdraft fees, generating significant profit for banks.

In our example above, if the insurance transaction arrived at the bank early in the day and was processed before the other transactions occurred, most consumers would agree that, while onerous, the bank is within its rights to impose 4 overdraft penalties. However, when the three smaller purchases occur before the insurance debit arrives, consumers rightfully argue that they should only be charged a single overdraft fee. When banks processes debit transactions out of order to rack up fees — known as “high-to-low” check clearing – consumers are understandably outraged.

Wells Fargo bank was recently called to task for high-to-low check clearing by a California judge who called the practice “gouging and profiteering.” Wells Fargo was ordered to pay $203 million in restitution to customers who had been unfairly charged. While the U.S. District Court ruling applies only to Wells Fargo bank, it is considered an encouraging sign for similar suits in other states.

On August 25^th, 2010 I hosted a coaching call with credit expert John Ulzheimer.  This was one of our best coaching calls because we continued to break new ground on credit scoring models.  The following is some more information regarding the inner working of scoring models or, as John calls it, “The anatomy of a credit scoring system.”

There are four primary components to any credit score; the scorecards, the characteristics, the variables and the weights.

Scorecards – The scorecards are actually scoring models but cannot stand alone as a freestanding credit scoring system.  All properly designed scorecards are built to evaluate the risk of a homogenous population.  Bankrupt consumers is one example.  “Consumers with thin credit reports” is another example.  There are many more examples of scorecards but FICO and other model developers don’t generally disclose the exact definitions.

The purpose of having multiple scorecards in a model is to optimize it’s performance for all different consumer credit file types.  If your credit score just had one scorecard then it would likely do well for one group of consumers and perform substandard for all others.  That’s not a good credit scoring system.  The better your developer is at defining a unique population, one that support it’s own scorecard, the better results from your credit score.  Currently the FICO scoring system has 10 scorecards (for older versions) and 12 (for FICO 08).  The following three components all reside within the scorecards.

Characteristics – A characteristic is simply a question the models asks your credit report.  So, for example, “how many inquiries do you have in the past 12 months?” or “what is your revolving utilization?” or “what is the oldest account on your file?”  Each scorecard has a different set of characteristics, but many of the same characteristics reside across multiple scorecards.

No model developer discloses all of their characteristics but we do know some of them and we do know that there are thousands of possible characteristics to choose from when building a model.  There’s actually software designed to think up characteristics.

Variables – If the characteristic is best described as a “question” then the variable is best described as “the answer.”  So, if the model asked you “how many inquiries do you have in the past 12 months” then the variable could be “none” or “one” or “15.”  That’s why it’s called a variable, because the answer to the question can vary.

Each of your answers is going to place you neatly into a bucket or bin or class, they’re all the same thing so don’t get confused by the term.  For example, here’s how inquiries COULD be bucketed, binned, or classed…THIS IS AN EXAMPLE.

Variable Buckets for “Number of Inquires in the Past 12 Months Characteristic”

0 inquiries

1 inquiry

2-5 inquiries

6-10 inquiries

>10 inquiries

The decision on how to break up those buckets is made by the model developer.  He or she is trying to come up with the best scenario, which yields the most predictive model.  This is an important step because you can’t simply choose how to break up your buckets based on common sense or anecdotal evidence.  It has to be based on science.  Just because you “think” 5 inquires is worse than 2 inquiries it doesn’t mean that it’s actually true.  In the example above, 2, 3, 4, and 5 inquires all mean the same thing, which is why they’re all in the same bucket.

This “bucketing” process is going to apply to almost every characteristic in your scoring model.  NOTE: Just because your bucket looks one way in one of the scorecards it doesn’t mean it’s going to look the same way in the others.  It could easily look like this in a different scorecard…

Variable Buckets for “Number of Inquires in the Past 12 Months Characteristic”

0 inquiries

1 inquiry

2-4 inquiries

5-8 inquiries

9-12 inquiries

>12 inquiries

Weights – Weights, or point values, is where your scoring model is most visible to lenders and consumers.  This is where your final score is going to start coming together.  The weight is the point value given to your variable.  So, if I used the above example here’s what it could look like…

Variable Buckets for “Number of Inquires in the Past 12 Months Characteristic”

0 inquiries = 50 points

1 inquiry = 45 points

2-4 inquiries = 40 points

5-8 inquiries = 20 points

9-12 inquiries = 5 points

>12 inquiries = 0 points

Just as it is with characteristics and variables, the point values will be different in different scorecards.  So, using my first example for inquiry bucketing your weights could look like this…(remember, this is the same characteristic just in a different scorecard)

Variable Buckets for “Number of Inquires in the Past 12 Months Characteristic”

0 inquiries = 60 points

1 inquiry = 55 points

2-5 inquiries = 50 points

6-10 inquiries = 20 points

>10 inquiries = 0 points

This is what confuses so many “credit expert pretenders’ because they generally want to assign a fixed point value to each item on a credit report.  When you look at these inquiry examples you quickly realize there is not a fixed value per inquiry.  The value or points you earn is based entirely on what bucket you fall into.  You don’t lose 5 points per inquiry.  That’s not how scoring works.

There ended the lesson!

The term “credit card roulette” can have a few meanings.  One is listed in the Urban Dictionary as “A game of chance to decide which person pays for a restaurant meal. Every party contributes a credit/debit card into a hat and the waiter/waitress removes one card at time. The last card removed pays the entire bill.”  That isn’t really an issue that a financial counselor would need to help you with…unless you end up being the chosen payer more often than you can afford. 

The meaning of the credit card roulette that we’ll look at has to do with the management of several cards when there’s not enough money to pay all the bills.  Of course, roulette implies that you’re taking a gamble with your financial well-being, and gambling is only really fun when the possibility of gain outweighs the little you’ll lose in the process.  In most cases, games of credit card roulette are more like the Russian variety, where you could end up far worse off than where you began. Luckily you’re unlikely to actually die…which is an important thing to keep in mind.  Money isn’t everything.

One way to play credit card roulette is to decide which card account gets the payment this month.  That involves factoring in things like current interest rates and what they might become if a payment is missed, late payment fees, and credit line reductions across the board.  Things could go horribly wrong here and cost you far more.

Another way involves utilizing balance transfers to get lower rates on existing balances, and hopefully consolidating your debt into chunks that are easier to manage. It also feels good to pay off a balance, even if you’re really just shifting it.  The main things to keep in mind are that the new card needs to be at a significantly lower interest rate (preferably 0%, at least for a while) and that you’re approved for the full amount of the balance you want to transfer. Otherwise, you’ve just complicated matters by adding another card with its own set of minimum payments and late fees to worry about.  

But when things have gotten to this point, your best option is to contact a financial counselor. They’ll be able to help you make the best decisions for your financial well-being.