Big data, big brains
Likewise, gathering and analyzing massive amounts of data from disparate sources is a prime candidate for applying intelligent algorithms. That's why AI will play a big role in assuring compliance for companies in highly regulated industries, like health care or finance.
"Armies of people are necessary today to handle the increased regulatory pressures the financial industry is facing," says Dan Adamson, CEO of OutsideIQ, which develops AI solutions for risk assessment. "Those processes can be done in a more auditable and consistent manner through AI."
For example, under Dodd-Frank, financial services firms may be asked by regulators to "play back" a trade made months or years in the past. Traditionally, compliance officers would have to manually sift through communications data from a wide range of sources -- email archives, phone records, chat logs, document management systems, and social media posts, as well as various trading systems -- to re-create the transaction.
"Simply trying to normalize all that data and place it on a timeline is extraordinarily difficult and time consuming," says Harald Collet, global head of Bloomberg Vault, an information management and analytics service that uses machine learning. "It's a scenario where it might have taken two months to respond to a regulator, and now the regulators are saying you have to respond within 72 hours."
Collet says more than 1,000 financial firms have deployed Bloomberg Vault so that they can monitor and archive trading activities and respond to regulators quickly. But the larger goal is to use machine learning for predictive analytics, so Vault users can identify potential issues before they become regulatory headaches.
"Firms want to detect patterns across large data sets and flag irregular trading patterns," he says. "For example, they want to be able to see chats where a trader has given a price quote to the customer, then immediately compare that quote to the actual price in the market at the time. The ability to see the connections between price points, chat, and trading patterns is what our clients are looking for."
Over the long term, systems like Bloomberg Vault can help optimize business processes and identify new opportunities, says Collet. As AI drives more decisions, the role of technologists in the organization will also change, notes Steven Hillion, chief product officer at Alpine Data, an advanced analytics platform for enterprises.
"IT's role is moving from one of data governance and security to one where they think about how data is delivered, how data provides insights into business operations, and how to operationalize those analytics into strategies that will positively impact the company," Hillion says.
Working for AI
It's been true since the industrial revolution: As technology replaces low-level workers, new jobs are created to service and improve that technology. AI is no different.
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