Michael Curry, vice president of engineering for Watson Financial Services, tells WatersTechnology, that the thrust of these upgrades is centered on making it easier for users to both monitor risk and compliance across the enterprise, but also to be able to drill into that information without having to be a risk or compliance expert.

“You really want to manage risk and compliance everywhere in the company at all times. So one of the key elements of what we’re doing is trying to lower the bar so that it’s not just risk and compliance people, with those risk and compliance skills, who are continually tracking and monitoring their risk positions and things that might constitute a risk conduct or compliance issue, but it’s everybody in the company,” he says. “The only way to do that is by making the technology so simple and so approachable that [anyone] can use it.”

One of the key pieces of this rollout is the integration of Armanta’s technology, which IBM acquired last month. The Armanta platform is a big-data analytics engine that pulls in live feeds of data and information from historical databases, as well as from open-source platforms. With the integration, users can aggregate data across multiple systems for their risk and compliance needs, and couple that with reporting processes to streamline their regulatory reporting environment.

Curry says that, through this integration, they have the ability to pull together a real-time view of risk across multiple different risk factors, in order to better monitor market, credit and liquidity risks against a portfolio.

“What we’re able to do with that technology that was difficult to do in the past is to integrate the views of risk across multiple different dimensions and across multiple different product lines and be able to slice and dice that view of risk,” he says. “This allows people to manage risk much more precisely.”

OpenPages Upgrade

IBM has also released the latest version of OpenPages, which IBM acquired in 2010 and which serves as a governance, risk and compliance engine for banks. Through the release, users will be able to interpret complex issues and match them automatically to controls and obligations, as well as analyze losses, emerging risks and failed controls.

As new regulations come down the pike—whether upgrades to Mifid II’s conduct requirements or brand new regulations taking effect, such as the General Data Protection Regulation (GDPR)—that content is fed into IBM’s regulatory framework and is automatically broken down into obligations, then it’s tied to policies and controls and tracked through issues within the OpenPages environment. This also includes public sources of information from speeches or opinion pieces given by government officials.

The aim of the solution is to automate some of the processes between digesting the laws and how those rules connect to internal policies, thus freeing up lawyers and compliance teams to better focus on specific needs in order to make better decisions.

“That’s all stuff that has to be done manually and it requires fairly skilled people to do that work,” Curry says. “Our goal is to provide cognitive assistance for that and to make it a much simpler process while providing recommendations from Watson on what makes the most sense as far as those mappings that might already apply to a new regulatory obligation.”

In a release, it was noted that HSBC—an early beta adopter of IBM’s new GRC technologies—used OpenPages 8.0 with Watson to scale up their users on the system to 15,000 employees across 70 countries, with over 400 unique users every 24 hours using the platform.

Finally, IBM also announced improvements for its Financial Crimes Insight with Watson platform, which features an updated user interface, tighter integration of due diligence data, and more advanced analytics and visualizations. This mainly focuses on banks anti-money-laundering (AML) and know-your-customer (KYC) needs.

“We’re trying to make it easier to find the patterns of bad behavior, such as internal-conduct issues, payments fraud or insurance-claims fraud, or money laundering activity for human trafficking or organized crime,” Curry says. “We take a machine-learning-based approach to solving those problems. We take a look at the transaction patterns and we look at external pieces of information and based on learning the patterns that represent fraud or crime, over time, we can get very accurate in being able to find new incidents of crime as they come in.”