Prof. Jayanth R. Varma’s Financial Markets Blog

A blog on financial markets and their regulation

Distrust and cross-check

I have piece in today’s Mint arguing that the Volkswagen emission scandal is a wake-up call for all financial regulators worldwide:


The implications of big firms such as Volkswagen using software to cheat their customers go far beyond a few million diesel cars

The Volkswagen emissions scandal challenges us to move beyond Ronald Reagan’s favourite Russian proverb “trust but verify” to a more sceptical attitude: “distrust and cross-check”.

A modern car is reported to contain a hundred million lines of code to deliver optimised performance. But we learned last month that all this software can also be used to cheat. Volkswagen had a cheating software in its diesel cars so that the car appeared to meet emission standards in the lab while switching off the emission controls to deliver fuel economy on the road.

The shocking thing about Volkswagen is that (unlike, say Enron), it is not perceived to be a significantly more unethical company than its peers. Perhaps, the interposition of software makes the cheating impersonal, and allows managers to psychologically distance themselves from the crime. Individuals who might hesitate to cheat personally might have less compunctions in authorizing the creation of software that cheats.

The implications of big corporations using software to cheat their customers go far beyond a few million diesel cars. We are forced to ask whether, after Volkswagen, any corporate software can be trusted. In this article, I explore the implications of distrusting the software used by big corporations in the financial sector:

Can you trust your bank’s software to calculate the interest on your checking account correctly? Or might the software be programmed to check your Facebook and LinkedIn profiles to deduce that you are not the kind of person who checks bank statements meticulously, and then switch on a module that computes the interest due to you at a lower rate?

Can you be sure that the stock exchange is implementing price-time priority rules correctly or might the software in the order matching engine be programmed to favour particular clients?

Can you trust your mutual funds’ software to calculate Net Asset Value (NAV) correctly? Or might the software be programmed to understate the NAV on days where there are lots of redemption (and the mutual fund is paying out the NAV) while overstating the NAV on days of large inflows when the mutual fund is receiving the NAV?

Can you be sure that your credit card issuer has not programmed the software to deliberately add surcharges to your purchases. Perhaps, if you complain, the surcharges will be promptly reversed, but the issuer makes a profit from those who do not complain.

Can you trust the financials of a large corporation? Or could the accounting software be smart enough to figure out that it is the auditor who has logged in, and accordingly display a set of numbers different from what the management sees?

After Volkswagen, these fears can no longer be dismissed as mere paranoia. The question today is how can we, as individuals, protect ourselves against software-enabled corporate cheating? The answer lies in open source software and open data. Computing is cheap, and these days each of us walks around with a computer in our pocket (though, we choose to call it a smartphone instead of a computer). Each individual can, therefore, well afford to cross-check every computation if (a) the requisite data is accessible in machine-readable form, and (b) the applicable rules of computation are available in the form of open source software.

Financial sector regulations today require both the data and the rules to be disclosed to the consumers. What the rules do not do is to require the disclosures to be computer friendly. I often receive PDF files from which it is very hard to extract data for further processing. Even where a bank allows me to download data as a text or CSV (comma-separated value) file, the column order and format changes often and the processing code needs to be modified every time this happens. This must change. It must be mandatory to provide data in a standard format or in an extensible format like XML. Since data anyway comes from a computer database, the bank or financial firm can provide machine-readable data to the consumer at negligible cost.

When it comes to rules, disclosure is in the form of several pages of fine print legalese. Since the financial firm anyway has to implement rules in computer code, there is little cost to requiring that computer code be freely made available to the consumer. It could be Python code as the US SEC proposed five years ago in the context of mortgage-backed securities (http://www.sec.gov/rules/proposed/2010/33-9117.pdf), or it could be in any other open source language that does not require the consumer to buy an expensive compiler to run the code.

In the battle between the consumer and the corporation, the computer is the consumer’s best friend. Of course, the big corporation has far more powerful computers than you and I do, but it needs to process data of millions of consumers in real time. You and I need to process only one person’s data and that too at some leisure and so the scales are roughly balanced if only the regulators mandate that corporate computers start talking to consumers’ computers.

Volkswagen is a wake-up call for all financial regulators worldwide. I hope they heed the call.

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2 responses to “Distrust and cross-check

  1. Richard Careaga (@technocrat) October 19, 2015 at 12:19 pm

    Yet another example of information arbitrage in action. One of the philosophical pillars of free market ideology is the symmetry of market power between buyer and seller, which VW reminds, if not exposes, is a simplifying assumption in a ceteris paribus model that should never be used to guide navigation among the real morals of the marketplace

  2. Pingback: In the sister blog during October and November 2015 | Prof. Jayanth R Varma's blog on computing

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