Slowly but surely, intelligent automation is coming to mortgage banking – and it’s only a matter of time before you automate your own systems, if you haven’t already.

Either way, you’re not alone if you still find it all so confusing. It’s easy to get lost amid the gazillion options out there, not to mention all the strange – and strangely similar – terminology you need to wrap your head around.

In this blog, our experts distill the key components and terms to help you leverage intelligent automation technologies with the greatest potential to benefit your business.

Key Components of an Intelligent Automation Solution

Intelligent automation is more than just robotic process automation (RPA) or optical character recognition (OCR). (See Key Definitions & Concepts.) It’s a blend of the capabilities used to automate “hand work” (moving data from one place to another) with more advanced technologies that automate “head work” (processes that traditionally rely on human intelligence).

While the automation of a few years ago focused primarily on technologies like RPA and OCR, they’re continuing to evolve beyond their current limitations. RPA and OCR, for instance, can provide a lift in terms of the hand work involved in processing, but there are additional technologies that take it a step further to automate the ‘head work’ or thinking processes.

Intelligent automation combines traditional automation modalities with more cutting-edge capabilities like natural language processing or machine learning. And this allows the mortgage banking industry to move into new areas of automation, like underwriting, which probably wouldn’t be possible to tackle without all of these technologies working together.

Key Benefits of Intelligent Automation

One of the first benefits you’ll realize is the ability to streamline your processes, potentially eliminating the need for multiple touches. Intelligent automation also helps increase data accuracy, consistency and integrity by decreasing the risk involved with fat fingering an entry or misreading a data point that could have serious downstream impacts.

Intelligent automation can increase staff productivity and empower your team to focus on higher value work. The result: a more fulfilled workforce, less turnover and a new selling point for recruitment. Finally, intelligent automation makes it easier to scale up or down without new hires or layoffs. Your robotic workforce handles mundane tasks at a lower, variabilized cost, lowering your cost to originate and boosting profits.

KEY DEFINITIONS & CONCEPTS

Robotic Process Automation (RPA): Software that can mimic human mouse clicks and navigation

Optical Character Recognition (OCR): Ability of software to extract data from documents

Intelligent Character Recognition (ICR): More advanced form of OCR that typically involves recognizing handwriting and extracting data from handwritten documents

Natural Language Processing (NLP): Software that mimics human language processing to allow computers to understand text

Artificial Intelligence (AI): Ability of machines to perform tasks that normally require human intelligence

Machine Learning (ML): Ability of computer systems to learn and adapt using predictive algorithms and not specific instructions

API Integrations: Connection between two or more applications via application programming interfaces (APIs) that allows systems to exchange data and/or take actions. APIs can provide a more reliable way of interacting with systems than RPA, though those capabilities can be limited by target application protocols.