Machine Learning While the terms “machine learning” and “artificial intelligence” are often used interchangeably, there is a distinction between the two.
Machine learning is a specific application of AI.
When machine learning is used, processors and underwriters can focus more time on higher-value activities to keep the mortgage process on track, and less time on document-level work.
Neural networks form the basis of much of today’s applications of AI, and it is a widely-held view that their use will bring incredible change across virtually every aspect of the industry.
Neural networks are becoming increasingly more accessible and easier to adopt.
Some of the most innovative and leading edge companies in the mortgage vertical are now bringing this technology to bear on the very specific needs of the industry.
At a high level, machine learning is the process by which AI deepens its knowledge by completing a task, processing information or accessing functionality – literally many thousands of times – via neural networks.
However, as it applies to the mortgage industry today, these technologies can certainly enable mortgage professionals to spend less time on remedial work, increasing capacity and decreasing costs.
Advanced technology can handle the validation of much of the mortgage-related documentation, while processors and underwriters focus on ensuring that any issues that may arise are quickly resolved, essentially turning task executors into knowledge workers In addition, freeing up the valuable time of mortgage professionals, like underwriters, may allow mortgage companies to be more aggressive in promoting growth.
Smart homes controlled by our voices; driverless cars; lights-out processing of previously hands-on, labor-intensive tasks involved in loan origination.