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Discover how AI improves loan origination with machine learning and automation—without relying on generative AI.
The business world has been buzzing about artificial intelligence (AI), particularly generative AI, for some time now. It’s positive to see excitement about the possibilities new technologies offer. However oftentimes, when one aspect of a new technology receives all the hype, it can blind the market to the benefits of others.
Generative AI is a perfect case in point. While this aspect of artificial intelligence is stimulating, for many reasons, there are still problems to be worked out before it’s ready for inclusion in mission-critical software applications. This makes generative AI worrisome for many executives.
It's crucial for business leaders to understand that not all AI is generative.
Many AI applications in use today serve different purposes entirely. In fact, the AI technologies we’re using at Mortgage Cadence to improve the lender’s loan origination process are not generative. But they are still very effective.
While generative AI, capable of creating content or making decisions with minimal human input, has captured public imagination, it represents just one facet of AI's potential.
Artificial intelligence encompasses a wide range of technologies and applications, from simple rule-based systems to complex machine learning algorithms.
Many businesses have been using AI for years in ways that don't involve content generation or autonomous decision-making.
Machine Learning (ML) is a type of AI that uses many data samples in order to build a model that mathematically recognizes patterns. Mortgage Cadence use ML AI in combination with optical character recognition (OCR) to classify and separate groups of documents that are sent into our system during the origination process. AI models are also being used in our system to perform data extraction which augments the data entry process and drives automation. Since Machine Learning is based on samples to improve recognition, the Mortgage Cadence Platform provides a mechanism for users to flag additional samples to help the system learn while they are doing ‘human-in-the-loop’ exception processing. This process of continuous learning decreases the amount of exceptions that need to be processed in the future.
When discussing AI implementation with clients or stakeholders, it's essential to clarify the specific type of AI being used and its intended purpose. This is a conversation we have with every lender partner.
This conversation is often made more difficult by executives who believe all AI is generative AI, and who are guarding against those technologies in its tech stack. We get it.
These concerns about AI may stem from a lack of understanding about how it works in practical business contexts. Our discussion generally moves into machine learning, pattern recognition, and data analysis to alleviate fears and build trust in AI-powered solutions by showing our partners exactly how they are being used.
When executives realize that the AI in use in the mortgage industry today is not designed to make independent decisions or generate original content, we find ourselves on the same page, both working to increase the lender’s efficiency and reduce their overall cost to originate.
When our technologists work to demystify AI and focus on its practical applications as they relate to the loan origination process, lending executives are more open to discussing changes in their own businesses.
This is important because of the role of artificial intelligence in shaping the future of work. Lenders who don’t take the time to fully understand how it can benefit them will be left behind.
To find out how Mortgage Cadence is using AI for the benefit of our lender partners and to see a demo of the power MCP loan origination system, reach out to us today.
By Mark Swift, Software Product Manager at Mortgage Cadence
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Mortgage Cadence:
Alison Flaig
Head of Marketing
(919) 906-9738