Machine learning

Freddie Mac's test of artificial intelligence to make lending decisions could be a significant turning point in broadening the use of the technology.

The most successful mortgage originators will use artificial intelligence and machine learning to enhance and enable their people to have better, more meaningful engagements with customers.

Credit decisions were a natural place to start with artificial intelligence, but now banks and credit unions are taking the technology to all parts of their businesses.

Blooma has developed a software product that combs databases to create property profiles for commercial real estate lenders. It can drastically cut origination costs and approval times and help banks identify safer loans, the company says.

Capacity, formerly Jane.ai, originally designed its chatbot to answer consumers' questions, but when employees started using it, that gave the startup an idea for a new business line.

Banks need to mitigate potential bias in algorithmic predictive models using artificial intelligence, as regulators are weighing how to oversee the emerging technology.

Savings related to artificial intelligence could add up to a couple million dollars within 12 months for lenders with sufficient scale, according to an independent researcher hired by Black Knight.

The mortgage industry identified two technology initiatives it claims have the greatest potential to improve processes and be the most broadly adopted over the next two years, according to Fannie Mae.

Mortgage lenders have invested heavily in various digital tools that improve the consumer experience, but what they really need to focus on is artificial intelligence that will improve data quality.

The mortgage industry is eager to adopt digital strategies like artificial intelligence to streamline processes, but they are finding it difficult to extend through the full lifecycle of the loan.