Very simple. Describe them as your greatest resource!
In my last blog post, I pointed out that the Carbanak/Anunak hack was mainly due to the recklessness of the banks’ own employees and system administrators. Now that they are aware of this, banks have to disclose this as another risk factor in their regulatory filings. Here is how one well known US bank made this disclosure in their Form 10K (page 39) last week (h/t the ever diligent Footnoted.com):
We are regularly the target of attempted cyber attacks, including denial-of-service attacks, and must continuously monitor and develop our systems to protect our technology infrastructure and data from misappropriation or corruption.
Notwithstanding the proliferation of technology and technology-based risk and control systems, our businesses ultimately rely on human beings as our greatest resource, and from time-to-time, they make mistakes that are not always caught immediately by our technological processes or by our other procedures which are intended to prevent and detect such errors. These can include calculation errors, mistakes in addressing emails, errors in software development or implementation, or simple errors in judgment. We strive to eliminate such human errors through training, supervision, technology and by redundant processes and controls. Human errors, even if promptly discovered and remediated, can result in material losses and liabilities for the firm.
Sun, 22 Feb 2015
There were a spate of press reports a week back about a group of hackers (referred to as the Carbanak or Anunak group) who had stolen nearly a billion dollars from close to a hundred different banks and financial institutions from around the world. I got around to reading the technical reports about the hack only now: the Kaspersky report and blog post as well as the Group-IB/Fox-IT report of December 2014 and their recent update. A couple of blog posts by Brian Krebs also helped.
The two technical analyses differ on a few details: Kaspersky suggests that the hackers had a Chinese connection while Group-IB/Fox-IT suggests that they were Russian. Kaspersky also seems to have had access to some evidence discovered by law enforcement agencies (including files on the servers used by the hackers). Group-IB/Fox-IT talk only about Russian banks as the victims while Kaspersky reveals that some US based banks were also hacked. But by and large the two reports tell a similar story.
The hackers did not resort to the obvious ways of skimming money from a bank. To steal money from an ATM, they did not steal customer ATM cards or PIN numbers. Nor did they tamper with the ATM itself. Instead they hacked into the personal computers of bank staff including system administrators and used these hacked machines to send instructions to the ATM using the banks’ ATM infrastructure management software. For example, an ATM uses Windows registry keys to determine which tray of cash contains 100 ruble notes and which contains 5000 ruble notes. For example, the CASH_DISPENSER registry key might have VALUE_1 set to 5000 and VALUE_4 set to 100. A system administrator can change these settings to tell the ATM that the cash has been loaded into different bins by setting VALUE_1 to 100 and VALUE_4 to 5000 and restarting Windows to let the new values take effect. The hackers did precisely that (using the system administrators’ hacked PCs) so that the ATM which thinks it is dispensing 1000 rubles in the form of ten 100 ruble notes would actually dispense 50,000 rubles (ten 5000 ruble notes).
Similarly, an ATM has a debug functionality to allow a technician to test the functioning of the ATM. With the ATM vault door open, a technician could issue a command to the ATM to dispense a specified amount of cash. There is no hazard here because with the vault door open, the technician anyway has access to the whole cash without issuing any command. With access to the system administrators’ machines, the hackers simply deleted the piece of code that checked whether the vault door was open. All that they needed to do was to have a mole stand in front of the ATM when they issued a command to the ATM to dispense a large amount of cash.
Of course, ATMs were not the only way to steal money. Online fund transfer systems could be used to transfer funds to accounts owned by the hackers. Since the hackers had compromised the administrators’ accounts, they had no difficulty getting the banks to transfer the money. The only problem was to prevent the money from being traced back to the hackers after the fraud was discovered. This was achieved by using several layers of legal entities before being loaded into hundreds of credit cards which had been prepared in advance.
It is a very effective way to steal money, but it requires a lot of patience. “The average time from the moment of penetration into the financial institutions internal network till successful theft is 42 days.” Using emails with malicious attachments to hack a bank employee’s computer, the hackers patiently worked their way laterally infecting the machines of other employees until they succeeded in compromising a system administrator’s machine. Then they collected data patiently about the banks’ internal systems using screenshots and videos sent from the administrator’s machines by the hackers’ malware. Once they understood the internal systems well, they could use the systems to steal money.
The lesson for banks and financial institutions is that it is not enough to ensure that the core computer systems are defended in depth. The Snowden episode showed that the most advanced intelligence agencies in the world are vulnerable to subversion by their own administrators. The Carbanak/Anunak incident shows that well defended bank systems are vulnerable to the recklessness of their own employees and system administrators using unpatched Windows computers and carelessly clicking on malicious email attachments.
Thu, 19 Feb 2015
Loss aversion is a basic tenet of behavioural finance, particularly prospect theory. It says that people are averse to losses and become risk seeking when confronted with certain losses. There is a huge amount of experimental evidence in support of loss aversion, and Daniel Kahneman won the Nobel Prize in Economics mainly for his work in prospect theory.
What are the implications of prospect theory for an economy with pervasive negative interest rates? As I write, German bund yields are negative up to a maturity of five years. Swiss yields are negative out to eight years (until a few days back, it was negative even at the ten year maturity). France, Denmark, Belgium and Netherlands also have negative yields out to at least three years.
A negative interest rate represents a certain loss to the investor. If loss aversion is as pervasive in the real world as it is in the laboratory, then investors should be willing to accept an even more negative expected return in risky assets if these risky assets offer a good chance of avoiding the certain loss. For example, if the expected return on stocks is -1.5% with a volatility of 15%, then there is a 41% chance that the stock market return is positive over a five year horizon (assuming a normal distribution). If the interest rate is -0.5%, a person with sufficiently strong loss aversion would prefer the 59% chance of loss in the stock market to the 100% chance of loss in the bond market. Note that this is the case even though the expected return on stocks in this example is less than that on bonds. As loss averse investors flee from bonds to stocks, the expected return on stocks should fall and we should have a negative equity risk premium. If there are any neo-classical investors in the economy who do not conform to prospect theory, they would of course see this as a bubble in the equity market; but if laboratory evidence extends to the real world, there would not be many of them.
The second consequence would be that we would see a flipping of the investor clientele in equity and bond markets. Before rates went negative, the bond market would have been dominated by the most loss averse investors. These highly loss averse investors should be the first to flee to the stock markets. At the same time, it should be the least loss averse investors who would be tempted by the higher expected return on bonds (-0.5%) than on stocks (-1.5%) and would move into bonds overcoming their (relatively low) loss aversion. During the regime of positive interest rates and positive equity risk premium, the investors with low loss aversion would all have been in the equity market, but they would now all switch to bonds. This is the flipping that we would observe: those who used to be in equities will now be in bonds, and those who used to be in bonds will now be in equities.
This predicted flipping is a testable hypothesis. Examination of the investor clienteles in equity and bond markets before and after a transition to negative interest rates will allow us to test whether prospect theory has observable macro consequences.
Wed, 04 Feb 2015
Yesterday, the Reserve Bank of India did retail depositors a favour: it announced that it would allow banks to offer “non-callable deposits”. Currently, retail deposits are callable (depositors have the facility of premature withdrawal).
Why can the facility of premature withdrawal be a bad thing for retail depositors? It would clearly be a good thing if the facility came free. But in a free market, it would be priced. The facility of premature withdrawal is an embedded American-style swaption and a callable deposit is just a non callable deposit bundled with that swaption whether the depositor wants that bundle or not. You pay for the swaption whether you need it or not.
Most depositors would not exercise that swaption optimally for the simple reason that optimal exercise is a difficult optimization problem to solve. Fifteen years ago, Longstaff, Santa-Clara and Schwartz wrote a paper showing that Wall Street firms were losing billions of dollars because they were using over simplified (single factor) models to exercise American-style swaptions (“Throwing away a billion dollars: The cost of suboptimal exercise strategies in the swaptions market.”, Journal of Financial Economics 62.1 (2001): 39-66.). Even those simplified (single factor) models would be far beyond the reach of most retail depositors. It is safe to assume that almost all retail depositors behave suboptimally in exercising their premature withdrawal option.
In a competitive market, the callable deposits would be priced using a behavioural exercise model and not an optimal exercise strategy. Still the problem remains. Some retail depositors would exercise their swaptions better than others. A significant fraction might just ignore the swaption unless they have a liquidity need to withdraw the deposits. These ignorant depositors would subsidize the smarter depositors who exercise it frequently (though still suboptimally). And it makes no sense at all for the regulator to force this bad product on all depositors.
Post global financial crisis, there is a push towards plain vanilla products. The non callable deposit is a plain vanilla product. The current callable version is a toxic/exotic derivative.