Machine learning

Federal Reserve Gov. Lael Brainard said regulators are seeking to "understand the potential benefits and risks" from utilizing artificial intelligence in the financial services sector.

The Libor transition is creating huge headaches for the industry; harnessing AI technologies may be the key to tackling it.

The automated closing disclosures software aims to be "40% faster than the 'old fashioned' method," a company spokesman said.

The CFPB is giving stakeholders until Dec. 1 to file comments on a potential overhaul to its rules related to the Equal Credit Opportunity Act, which prohibits discrimination in credit and lending decisions.

The agency sought feedback on potential changes to the Equal Credit Opportunity Act. But a coalition of industry and advocacy groups want a longer comment period to afford “a greater opportunity for thoughtful public participation.”

IBM called for rules aimed at eliminating bias in artificial intelligence to address concerns which range from identifying faces in security-camera footage to making determinations about mortgage rates.

Wealthfront could roll out a debit card, automated bill pay and direct deposit in early 2020, Chief Executive Andy Rachleff said.

Brent Chandler of FormFree, Tim Mayopoulos of Blend and Tamra Rieger of Evergreen Home Loans share their Digital Mortgage 2019 highlights

Rick Lang of Freddie Mac, Tim Mayopoulos of Blend and Tamra Rieger of Evergreen Home Loans discuss the key objectives – from customer experience to system integrations – that mortgage companies are pursuing through digitalization.

Aaron King of Snapdocs, Brent Chandler of FormFree, Tim Mayopoulos of Blend, and Chris Backe of Ellie Mae talk about system fragmentation, data access issues, personnel management and other hurdles that still stand between the industry and comprehensive digitalization.

PointPredictive has rolled out IncomePASS, which uses machine learning technology to determine if the borrower's income as stated on the application is realistic.

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.