Follow Datanami:
June 26, 2013

Financial Services Firm Look to Big Data for Compliance Solutions

Alex Woodie

Financial services firms are hoping a new generation of big data technology can assist them in implementing deal monitoring systems, as required by new regulations passed since the global financial crises.

When a key provision of the Dodd Frank Act goes into effect on March 31, 2014, the global financial system should be sturdier and more transparent thanks to new rules that require big swap traders to implement deal monitoring systems that document everything that goes into each swap trade, and to provide that documentation to regulators within 72 hours, if requested.

However, the actual task of monitoring traders, collecting all that unstructured data, and hammering it into an acceptable format presents a significant computational challenge, if not expense. In addition to the specific details of the deal, such as price and quantity, Dodd Frank requires that big trading firms collect all communications–including phone calls, mail, and online chats–related to specific deals.

Big firms are expected to pay between $50 million and $200 million apiece to implement a Dodd Frank-compliant deal monitoring and record keeping system that can collect all the unstructured data and synthesize it into an acceptable format, according to a recent ComputerWeekly article. Companies such as CGI Group, Traiana, and Fonetic, among others, are expected to build the big data applications that service this new market need.

The looming deadlines belie the fact that not all of the regulations have been written. The European version of Dodd Frank, called the MiFID (Markets in Financial Instruments Directive), is still being hashed out.

Not surprisingly, financial firms are taking their compliance efforts slowly at this point. Since there are so many unknowns in the compliance equation, industry observers expect  financial firms to take a “bolt-on” approach with their compliance software, which could bode well for providers who can deliver big data solutions as a service over the cloud.

In addition to tracking what goes into each swap deal so that they can be unwound if needed, the hope is that such deal-monitoring systems will also be able to help big banks stop rouge traders and erroneous trades before they can hurt the market.

So-called “fat finger” mistakes are rare but costly. There’s the Lehman trader who wiped £30 billion in value off the FTSE 12 years ago after submitting a sell order 100 times bigger than he intended. More recently, there’s the story of The London Whale, who cost JP Morgan Chase up to $7 billion after making risky bets on bonds that turned bad.

Once developers have a handle on the trade monitoring systems–a difficult task, given that not all of the rules have been written yet–the hope is that firms will be able to use the new big data tools to deliver deeper and better analysis into the effectiveness of their own traders and trading programs. As these types of tools become common with the big firms, the smaller firms will gradually adopt them as the costs come down.

Related Items:

Hortonworks Previews Future After Massive Funding Haul

The Art of Scheduling in Big Data Infrastructures Today

Facebook Molds HDFS to Achieve Storage Savings