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Mining the Data Intersection of Artificial Intelligence and BPM for Financial Services

Banks have been at the center of a data explosion for decades and have traditionally aggregated this data in the immediate context, often to solve one business problem at one-point-in-time, in order to stay compliant. Enter Artificial Intelligence (AI)…while not a new term, its use case in banking today speeds what researchers have usually had to do manually to help financial institutions keep up with the growing regulatory scrutiny, to flag suspicious activities and to capture wrongdoing (like money laundering) that could be sneaking through the cracks of the organization.

From Months to Minutes – AI in KYC

When used during the Know Your Customer (KYC) process, AI can cut costs and complexity. It can generate profiles on individuals and companies in mere minutes and turn an otherwise tedious process into instant, auditable information so that key stakeholders can make informed decisions. The clear business value for AI in KYC is time-savings which ultimately leads to increased customer satisfaction and revenue.

Our recent partnership with OutsideIQ brings this opportunity to our customers via the company’s investigative cognitive computing technology, DDIQ®. With the growing number of data sources available, the product’s cognitive computing engine searches thousands of international structured and unstructured sources to cut through false positives and accurately flag potential risk issues on a subject. It thinks like an investigator and searches the open web and deep web for anything relevant published about the third party. The technology is designed to enhance (not replace) the reporting process so that human researchers can be armed with the information they need, when they need it, to make key decisions.

While KYC and improved due diligence is one great example of AI’s value, we are merely scratching the surface with its potential to improve overall business process management practices. There’s a business case for looking at the data as a whole vs. immediate instance to uncover new customer experiences and cross-selling opportunities. The more companies can dive into the data and make sense of its patterns, the more they can understand its impact to create a competitive advantage.

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