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Category Archives: Credit Cards

Many unintended consequences in business & finance occur because upside (profitability) and downside (loss) risk have very different characteristics.

Background
In 2007 I sifted through 330,000 RMBS (Residential Mortgage Backed Securities) assets or loans with the purpose of developing a default & loss econometric model that would enable my then employer differentiate between good and bad RMBS bonds.

I had to do a lot of data structuring and clean up to standardize incoming data from about 20 different servicers. I should say data structuring and data scrubbing. And after that sift through this asset data set to filter out the bad data. So you can imagine the amount of work that went into this.

My strategy to identify the loss quality of a bond was to use the origination and close data to forecast future losses. Why? Because once you have purchased the bond you are stuck with whatever losses that unfold.  If this was possible we could very quickly eliminate the poor quality bonds, and use cash flow methodologies (more on this in a later blog) to evaluate the better quality bonds. We did not want to expend effort valuing poor quality bonds.

Dichotomy of Metrics
Well, at least that was the theory. What went wrong? In residential mortgages FICO scores are a major component, if not the primary driver for assessing future default behavior. I found that for residential mortgage FICO scores at origination were poor predictors of future defaults. How? Build two probability distributions of FICO scores. The first is a distribution of FICO scores of the borrowers at origination for all assets. The second is the distribution of the FICO scores at origination for defaulted assets only. You could not tell the difference between the two distributions!

Bewildering. Was there an analogy in other areas of finance? Yes. Company pro forma profitability analysis are good predictors of future profitability, but they are poor predictors of severe losses or bankruptcy risk. To get a handle on future company bankruptcy risk one requires a tool like Altman’s Z-Scores.

Here we observe a dichotomy in forecasting characteristics. On the one hand pro forma informs us of future profitability and on the other hand Altman’s Z-Scores informs on bankruptcy risk. We concluded that FICO scores behave like pro forma profitability, that they are good predictors of success but poor predictors of defaults.

I must add that unlike investment bankers and fund managers who are focused on upside risk or profitability, my career in financial services has been focused on downside risk. Therefore I did not test if FICO scores are good predictors of success.

When we recognized this dichotomy we abandoned RMBS bonds as a viable investment vehicle. But this story does not end here. I have an extensive business reengineering background and investigated how FICO scores are generated.

How Credit Cards Drive FICO Scores
From a business process perspective recent FICO scores are generated by your credit card issuer. Really. You the card holder use your card to transact purchases. In so doing you create debt. How much of this debt you pay down, how quickly, etc., is reported to the rating agencies. This reporting provides an insight into your debt payment characteristics which the rating agencies convert into FICO scores. FICO scores appear to predict defaults because they are adjusted downwards as your credit card payments deteriorate. That is, in my opinion, FICO scores have a limited window of about 90-days within which they work, but by then it is too late for the card issuer. Or no credit card visibility no FICO adjustments.

Here is the weak link in this whole business process. Without your credit card spending and payments reported by your card issuer, the rating agencies would not have a clue what your recent credit rating should be.

Take 2 people John & Jay. John has house and car payments and uses his credit card for all his purchasing transactions. Jay also has house and car payments, but he only uses cash for his purchasing transactions.

Now both have suffered a partial loss of income. They both continue to make house and car payments. Therefore the ratings agencies cannot tell from these payment that there has been a partial loss of income. Both reduce their spending to manage within their new realities. But John has now slowed his credit card payments. The rating agencies see this and are able to adjust John’s FICO scores accordingly but not Jay’s.

The use or not of credit cards provides asymmetric information to rating agencies. Now guess what happens as credit card companies ramp up interest rates, consumers pay down their card debt and stop using their cards.

Unintended Consequences
All manner of unintended consequences occur.

1. The banking industry loses it recent FICO information for a much larger proportion of the population.

2. Consumers do get penalized with lower FICO scores for not having recent payment histories.

3. First time home buyers will face higher rates because they don’t have sufficient recent history.

4. FICO scores are no longer as “effective” as they were “supposed” to be.

5. Because of this additional “FICO risk” for the same “risk” bonds with credit card debt should trade at a discount to bonds with residential mortgages which in turn should trade at a discount to CMBS bonds.

6. As I had stated in my Feb/02/09 post Risk-Reward is Non-Linear, increased rates will increase defaults. The unintended consequence of this is that banks that have rushed to increase rates to 30% before the new laws come into effect, will have locked themselves into a population demographics that experiences a higher default rate. Therefore we can expect to see an increase in credit card losses.

Summary
I’m sure there are a lot of very smart people in the credit card and rating industries, but… This situation is not dissimilar to what I observed as a management consultant reengineering manufacturing companies – one may have the best, the brightest and the most experienced managers but surprisingly when they come together at their management meetings they do strange things.

There needs to be a better way to address bank losses on credit cards and a better way to treat customers. Remember your customers are not your enemies.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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Are banks panicking? I ask this question because the New York Times article, A Squeeze on Customers Ahead of New Rules, points to several bewildering measures (quoted directly from the article) banks seem to be taking:

1. Practices outlawed by Congress: ‘A study by the Pew Charitable Trusts, released late last month, concluded that the 12 largest banks, issuing more than 80 percent of the credit cards, were continuing to use practices that the Fed concluded were “unfair or deceptive” and that in many instances had been outlawed by Congress’.

This is unfortunate as the banks are bring more negative attention to themselves. This is only going to increase the determination of our elected officials to tighted the regulatory environment.

2. Banks are becoming aggressive: ‘As banks have become more aggressive in making changes, lawmakers have accused them of trying to impose rate increases before many of the new rules take effect in February’.

Chasing diminishing profits in this manner is the fastest way to alienate your customers, and ensure sustained negative growth in the years to come. There are many other competitive instruments that can replace credit cards, e.g. debit cards, electronic checks, bill pay, ecommerce services like PayPal. Oh! I forgot the humble paper check.

My bet is that PayPal and similar ecommerce sites will grow substantially from these banking missteps. This will pose further risks if the new ecommerce sites that take advantage of these banking missteps, are based offshore.

3. We don’t sell sweaters: “We sell credit; we don’t sell sweaters,” said Kenneth J. Clayton, senior vice president for card policy at the American Bankers Association. “The only way to manage your return is through the price of the product or the availability.”

I don’t understand Kenneth Clayton’s comments about sweaters. Everything is supply and demand. Maybe he is thinking about it from the perspective of the algorithms. Credit card debt is based on mathematical/statistical algorithms and sweaters are not? If that is the case then credit cards are like sweaters when compared to quant trading strategies. Anyone have any idea what Kenneth Clayton was trying to express?

I must say that having worked in financial services for many years I know that financial services companies did attract the brightest and the best, but the recent banking industry responses to the changing regulatory and economic environment bewilders me.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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The New York Times reported Goldman Earns $3.19 Billion, Beating Estimates and this on a Tier-1 capital ratio of 14.5%. Goldman has the second highest Tier-1 capital ratio after State Street. Most banks are now in the 10%-12% range with US Government assistance. This is a far cry from the original Basel II requirement of 4%, and Tier-1 capital ratios of 14.5% would have been considered insane in the pre-2007 days.

Goldman Sachs is sending important market signals:

1. Well managed banks can make good profits in spite of “insane” Tier-1 ratios.

2. My guess is that Goldman Sachs is expecting a second asset value collapse soon as this firm has been steadily increasing its Tier-1 ratio and its risk adjusted capital since 2008. See my post  Quant Error! Goldman Sachs Success.

What does all this mean? Well lets look at all the facts.

1. A total of 106 regional banks failed in the United States this year, a figure not seen since 1992.

2. 15.1 million people are unemployed and counting coupled with a jobless recovery. That means prime mortgages are defaulting at unprecedented rates.

3. Many banks are in denial about their current viability and are resorting  to giving incorrect information to their customers. In particular:
3.1 These banks’  credit card operations are telling their customers that they are not part of the banking business and therefore did not receive TARP, when the banks did receive TARP.
3.2 Some banks are telling their customers to take out loans on the other collateral they have and use it to pay off their existing loans.
3.3 Other banks are telling their customer that they have no access to TARP funds or any government assistance and therefore have to foreclose on their customers’ properties.

Points 1, 2 & 3 by themselves just show that the mortgage mess is pretty bad. But add that to what Goldman Sachs is doing – Tier-1 of 14.5% – then that, in my opinion, suggests that Goldman Sachs does not have much confidence in the economy. I hope I’m wrong but it is better to be aware of the downside risk then to walk around in rose tinted glasses.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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Giacomo John Roma pointed me to an interesting article by Taleb & Spitznagel as part of the LinkedIn discussion and here are my thoughts on this and the related discussion.

I infer that Taleb’s primary concern is leverage. Debt provides leverage, and unconstrained debt provides unconstrained leverage. That is the lesson of 2008. Taleb wants us to reduce the extent of the leverage in our economy, because debt has a property that affects our perception of risk, i.e. debt hides volatility.

Regarding VaR:

(1) If you examine the historical data, outside of social sciences and quality control, there are very few thing that are Normally distributed. Taleb’s point here is that much of the mathematics that is used in finance and economics is based strongly on the assumptions of normality, and therefore, are not good forecasters of their metrics. They only appear to work when the law of large numbers can be applied. Therefore Taleb is recommending that a lot of these mathematics and their resulting analytical tools are erroneous in the long run.

(2) There are serious problems with VaR even without the normality assumption. In my experiece (I never assume normality) with years of building econometric CMBS loss and default models I found that VaR would consistently underestimate losses in the first 3 to 5 years of the loan.

Black Swans are a real problem in mortgages. The historical data shows that they are real. Just look at 2008. My own estimates are that Black Swans in CMBS bonds are on the order of 20% to 80%.

I also found that the only realistic way to handle undisciplined leverage was to implement non-linear economic or risk capital controls. This comes back to Taleb’s point on non-linearity.

Non-linearity is not new. Credit card companies use non-linearity a lot. They impose 2x and even 3x or 30% rates on delinquent card holders. Try imposing that on institutions, and all hell breaks loose. This is the power of buyers and sellers at play, not mathematics and not finance.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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There was this article in CNNMoney, Consumer credit: Surprise $1.8 billion jump, that suggested that consumer’s credit card borrowings increased by an annualized rate of 1.2% or $1.8 billion, however, economist were expecting a fall of $5 billion, signaling that households may have started to loosen their purse strings.

Yes, this would be the correct intrepretation in a normal healthy economy, but our economy is shrinking and has been throwing off 100,000s of jobs every month for more than a year. Current unemployment now stands at 8.1% or about 11 million.

The correct intrepretation is that consumers are hoarding cash and switching to credit cards to make their payments. Why? Because of the zero income survival strategy.

First, at the household level, in a zero income household, the survival strategy is you use your cash to make your mortgage and car payments first, and eliminate all unnecessary purchases.

Second, consumers shift down their credit card payments from full outstanding balance to minimum payments to conserve more cash.

Third, at the regional/national level, as the consumers’ period of unemployment increases and as the numbers of unemployed increases, this household level behavior translates to more spending moving to credit cards to conserve cash combined with less credit card payments.

There are two key measures to the health of the credit card industry that the industry should be watching in a downturn,
1. The change in the proportion of card holders making minimum payments.
2. The change in the proportion of outstanding debt to card payments.

If both have increased then my intrepretation is correct, if not then this is a good early signal that a recovery is in sight.

Of course if the increase in consumer credit is due to the zero-income survival strategy,  that means that when your cash runs out you default on your card debt. And that is not good news for the banks.

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Disclosure: I’m a capitalist too, and my musings & opinions on this blog are for informational/educational purposes and part of my efforts to learn from the mistakes of other people. Hope you do, too. These musings are not to be taken as financial advise, and are based on data that is assumed to be correct. Therefore, my opinions are subject to change without notice. This blog is not intended to either negate or advocate any persons, entity, product, services or political position.
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