It was only a matter of time before another banker, lured by the prospects of riches, would get busted on allegations of stealing source code connected to a high-frequency, stock-and-commodities trading platform.

The latest arrest concerns a former Societe Generale trader who was being detained Tuesday on New York federal court charges of stealing the computer code of the Paris-based banking concern's high-frequency trading software.

Monday's arrest of Samarth Agrawal, 26, came nine months after a Goldman Sachs programmer was arrested on similar charges that he, too, stole his employer's source code for software his employer used to make sophisticated, high-speed, high-volume stock and commodities trades.

The Securities and Exchange Commission is investigating the use of these programs that many believe give their users an unfair advantage over other traders. Nevertheless, stealing the code to these suspect programs remains illegal.

When Sergey Aleynikov, the Goldman Sachs computer programmer, was arrested in July, the authorities said the software at issue could "manipulate markets in unfair ways."

And on Monday, Manhattan federal prosecutors wrote in Agrawal's complaint that Societe Generale "believes that, if competing firms were to obtain the code and use its features, the financial institution's ability to profit from trades using the code would be significantly diminished" (.pdf).

According to Agrawal's complaint, the code at issue "uses a number of sophisticated mathematical formulas, or algorithms, to make decisions about, among other things, the volume, price and timing of trades that are made by the trading system. The trades made using the trading system typically generate millions of dollars of profits per year for the financial institution."

In both prosecutions, the authorities said the defendants had wanted the code for their own financial benefit. When Agrawal resigned from the Paris-based bank's New York offices, he allegedly told his employer he wanted to move back to India and begin his own high-frequency trading fund.

Photo: AP

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