Q&A: Hyland expert discusses the power of intelligent automation in banking
How can banks and credit unions keep up with the increased demand? Often, they turn to automation.
Today’s consumers demand fast and efficient digital channels to conduct financial transactions. How can banks and credit unions keep up with the increased demand? Often, they turn to automation. BAI, a nonprofit that provides research, training and thought leadership in financial services, recently discussed key industry trends with Hyland's Steve Comer. Steve, Hyland’s assistant vice president of financial services and insurance sales, has more than two decades of experience in financial services.
An excerpt from his Q&A with BAI follows.
Banking’s digital transformation is being driven by intelligent automation (IA), which taps artificial intelligence (AI), machine learning and other electronic processes to build robust and efficient workflows. IA can deliver information, reduce costs, improve speed, enhance accuracy and remove bottlenecks with fewer human touchpoints.
Even better, IA is smart enough to learn as it grows.
Examples of IA include robotic process automation (RPA), which uses bots to perform repetitive, high-volume data processes, freeing employees to focus on higher-value tasks. And there’s intelligent capture, the heart of IA, which allows banks and credit unions to capture and classify documents and data.
IA can improve the customer experience by anticipating needs and boosting productivity even as financial services organizations increasingly rely on remote workforces.
Steve Comer discusses the impact this strategic lever has on the banking industry and best practices for implementation.
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What is the biggest challenge to implementing intelligent automation and banks and credit unions?
SC: The design is critical. Banks know what they want to automate, but if they don’t design the solution appropriately — if the fundamental architecture or the process flow lacks clearly defined success criteria — they’ve essentially automated a bad process. Without redesigning and rethinking the process itself, you’re stuck with an outcome that’s not a whole lot better than what you started with. Design is one of the biggest challenges, but it ultimately leads to the biggest success.
How can intelligent automation bring efficiency to the mortgage lending process?
SC: Mortgage lending has historically been heavily paper-based, with a lot of data duplication from one system to another. Financial institutions gather data about credit scores, flood-zone verifications, employment information, income verification and information that falls under the “Know Your Customer” initiative.
RPA bots, for example, can easily grab that information, replicate it and advance it to the loan origination system (LOS), underwriting and other systems where the data is required. The lender can get to a quicker decision and therefore get to funding faster, which translates to higher and more immediate revenue.
Most intelligent automation takes place in the back office, so how does that translate to front-end customer engagement?
SC: Back-office operations are the catalysts to front-end engagement, and they’re the real focus of automation. Today’s consumers, especially in the younger generations, don’t want to step into brick-and-mortar institutions to transact business. They want mobile efficiencies and omnichannel experiences without interacting with a human. The only way to do that is to make back-office operations more efficient via faster decisions and response times. Banks need the tools on the back end to be as responsive, accurate and efficient as possible on the front end.
Is it difficult implementing intelligent automation on older core banking systems?
SC: It’s definitely difficult.
The old legacy banking systems are challenged to support technology that’s not native to the core system. Technology continues to advance at a very rapid pace. APIs are becoming much more open, functional and capable when it comes to data access. Institutions still on a legacy core system aren’t necessarily stuck — but it will always be more of a challenge to integrate older technology with modern tools. In any case, the key to success is ensuring that the organization finds the right partners and the right solutions to advance the modernization efforts.
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