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Hardly a week goes by without another report on how machine
learning and AI will transform the way we work and live. AI's ability to
digest huge amounts of data, identify patterns, and predict likely outcomes
make them critical components in many areas including self-driving
vehicles, breakthrough diagnostic tools, and personal recommendation
engines. Not surprisingly, the mortgage industry is now turning to these
advanced technologies to enhance the speed and precision of everyday
decision-making.
Fannie Mae recently reported that 27% of
lenders are currently using AI in some form
and another 58% expect to use it shortly.
To date, early-stage AI/machine learning
efforts have primarily focused on enhancing
origination, fraud/risk identification, and
customer retention. But there are critical
servicing functions that can benefit, as well,
including the default life cycle and critical
disposition paths.
Most industry observers agree—and a
study by Fannie Mae supports—that the best
way to reduce default losses is to avoid taking
properties through conveyance or REO and
instead dispose of them through other means
as quickly as possible. However, this isn't
always possible as evidenced by the number
of properties that continue to convey or
move to REO. According to ATTOM Data
Solutions, more than 143,900 properties
went into REO in 2019, a number that could
grow exponentially in a default market.
LEVERAGING
MACHINE
LEARNING FOR
BETTER DEFAULT
DECISIONS
The potential for artificial intelligence to drive industry innovation isn't
limited to the origination sector.
Quick Take By: Miriam Moore
