It’s all about the context — that stands as one of the oldest lessons passed along by teachers and mentors, lest a single fact or event take on oversized, or undersized, importance. Now, as financial institutions (FIs) embrace Big Data and the algorithms, the idea of applying context to banking transactions stands to gain more popularity and profit potential.
That was among the main themes of a recent interview with Manish Maakan, CEO of Intellect Global Transaction Banking (iGTB), a provider of corporate banking technology. The company recently announced that its CBX corporate banking platform will be available through IBM Cloud to reach bank customers.
CBX uses APIs, machine learning, predictive analytics and other technologies to automate and customize operations for corporate banking and B2B transactions. The goal of the technology is to determine, via business data, the “best-next” actions for banking clients. That means using machine learning and predictive analytics for product upsells and cross-sells, along with what iGTB calls “context-aware recommendations,” which can lead to more client profit.
“For banks undergoing digital transformation, the risk of slow and disruptive implementation is a pressing concern,” Maakan said. “Working with IBM, we’re ensuring that not only can we offer the most sophisticated transaction banking solutions, but we can serve clients through the IBM Cloud — implementing quickly, seamlessly and with minimal risk.”
So-called contextual banking involves asking the “what” and the “why” about transactions.
For example, he said, FIs collect a lot of data when it comes to accounts payables transactions. The iGTB technology can help banking professionals “to understand the context and intent of those transactions, and how to make sense of them,” he said. That, in turn, can lead to guidance or recommendations about the “cheapest and best methods of payments” going forward, Maakan said. “You can work that into a meaningful action.”
He summed up the three principles of contextual banking at this: “Knowing the intention and circumstances of the transaction, knowing the customer, and also [having] the Big Data behind all that.”
The same general work of accumulating data and building context around banking transactions can apply to a host of B2B areas, including foreign currency conversions, he said. Each transaction offers “fresh” intelligence that software can store and analyze, then use according to business rules set by clients. Recommended options can be rated for speed, risk, legality, value and cost.
Contextual banking, in general, can also serve as fraud prevention, he said. Via the analysis of cookies on a website, software used in contextual banking might not only spot cookies from “suspect sites,” but “pick up patterns (such as) where you originate a business transactions if you are not working from (a usual) site.”
Contextual banking remains in its “first generation,” Maakan said, though developing technology, including the deployment of more sophisticated APIs throughout the banking industry, will likely lead to significant improvements in the coming few years. Each successive layer of technology architecture will bring improvements upon which to build even more contextual capabilities.
Another progression that is happening in the world of contextual banking — at least according to the iGTB experience — is the change in the size of the FIs using the relevant technology. The “tier one” banks were the initial focus, as one might expect, but as financial professionals began to read the case studies, the appeal of contextual banking has now moved to regional and local banks.
“Every time we go lower, the technology gets better,” he said.