Wall Street & Technology is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Compliance

06:15 AM
Becca Lipman
Becca Lipman
Commentary
Connect Directly
Facebook
Google+
Twitter
RSS
E-Mail
100%
0%

2015 Prediction: FinServ & Regulators Will See Opportunity in Internet of Things

The Internet of Things still seems a bit foreign to capital markets, but next year may be the start of conversations, investment, and regulations on how firms can incorporate the world of sensor data.

Sensors are nearly everywhere, from our fitness bands and cars to dishwashers and thermostats, and from smart home automation to machines with "feelings" that can tell you when a part needs replacing.

Tapping into all that data has proved profitable in a number of previously unimaginable ways. Farmers have optimized their efficiency by knowing more accurately the state of their crops and when is the best time for watering and harvesting. Transport systems put out just the right number of buses and trains to conserve fuel. The list goes on.

But what about investors? Little has been said of incorporating all the Internet of Things sensor data into investment strategies, probably because few are trying and even fewer have found success. (If they have, they intend to keep their secret sauce guarded.)

But imagine the possibilities. Dr John Bates, group executive board member at Software AG, had a few potential scenarios to share. For example, on massive farms, there are tractors that drive themselves and have sensors to convey the state of the harvest. "If you can tap into all that data, maybe you don't need to wait for the crop reports. You can do your own automatically with analytics." But it poses a big question: "Is this a new way of insider trading?"

And it's not just tapping into trade data. Machine learning can also be used to spot when unusual things happen. Envision, from an HR perspective, combining more traditional data like holiday requests and travel schedules with sensors that track where traders are in the building, what time they've arrived, who is meeting with them, and how often. And now there's smart video analytics that can tell facial expressions like sadness, worry, or happiness.

"What if they could correlate that stuff?" Bates muses. "If an unusual trade happens just before news article came out that moves markets by a certain amount, and the trader had been meeting somebody outside the second floor elevators looking nervous, and this has happened three times in the last week, we investigate. This is going to lead to massive riots... Traders will say this going too far."

Regulators leveraging IoT
Understanding what the IoT could mean for traders is important for regulators to get ahead and define some of the legal grey areas that might emerge.

Using the examples above, some legal gray areas might be whether it would be okay if a third party aggregated the farm information, combined it with satellite imagery of fields, and sold subscriptions to trading shops? If so, would that service come under regulatory scrutiny? And if that data could affect share price, how public would this data be?

Would regulators call foul on firms that could not correlate the sensor data and flag suspicious employee behavior? What responsibility would a firm have to adopt these surveillance measures?

"Regulators are going to be tapping into all these techniques and speeding up," Bates said. It is very probable they will leverage sensor data to track more people and things, just as firms will use the data to innovate their strategies.

Sensors for protection
Bates offered another hopeful prediction: Could algorithm-generated problems soon be things of the past?

Many flaws in algorithms have been revealed (very publicly), and a determination to avoid attention from the news media and regulators has meant a lot of preventable problems have been attended to tirelessly.

Today, smarter self-learning algorithms are spotting instances when things are deviating from normal patterns. In reaction, they know to shut down the instances, report problems, and, most importantly, not make drastic and hasty decisions, such as ones that can cause flash crashes in the market.

With all the safeties in place, "I think we're being so boring now," Bates said.

Becca Lipman is Senior Editor for Wall Street & Technology. She writes in-depth news articles with a focus on big data and compliance in the capital markets. She regularly meets with information technology leaders and innovators and writes about cloud computing, datacenters, ... View Full Bio
More Commentary
A Wild Ride Comes to an End
Covering the financial services technology space for the past 15 years has been a thrilling ride with many ups as downs.
The End of an Era: Farewell to an Icon
After more than two decades of writing for Wall Street & Technology, I am leaving the media brand. It's time to reflect on our mutual history and the road ahead.
Beyond Bitcoin: Why Counterparty Has Won Support From Overstock's Chairman
The combined excitement over the currency and the Blockchain has kept the market capitalization above $4 billion for more than a year. This has attracted both imitators and innovators.
Asset Managers Set Sights on Defragmenting Back-Office Data
Defragmenting back-office data and technology will be a top focus for asset managers in 2015.
4 Mobile Security Predictions for 2015
As we look ahead, mobility is the perfect breeding ground for attacks in 2015.
Register for Wall Street & Technology Newsletters
Video
Stressed Out by Compliance, Reputational Damage & Fines?
Stressed Out by Compliance, Reputational Damage & Fines?
Financial services executives are living in a "regulatory pressure cooker." Here's how executives are preparing for the new compliance requirements.