Topics
Latest
AI
Amazon
Image Credits:Figure
Apps
Biotech & Health
clime
Image Credits:Figure
Cloud Computing
DoC
Crypto
endeavor
EVs
Fintech
fund raise
Gadgets
Gaming
Government & Policy
ironware
Layoffs
Media & Entertainment
Meta
Microsoft
Privacy
Robotics
Security
societal
Space
Startups
TikTok
transit
Venture
More from TechCrunch
Events
Startup Battlefield
StrictlyVC
Podcasts
Videos
Partner Content
TechCrunch Brand Studio
Crunchboard
Contact Us
loaning inauguration Figure announced today a rollout of AI tooling to make the home loaning cognitive operation more efficient . The company will be set up an AI tool power by GPT-4 to facilitate fascinate error in lending document .
Figure , founded in 2018 , specializes in aid consumer assure home equity lines of credit . The caller touts that its all - online process condense a usually 45 - day process to five . More than one-half of Figure ’s patronage is B2B , where it ’s embedded in company like solar control board loan party GoodLeap .
The troupe , which has raise over $ 1.5 billion and was last valued at around $ 3 billion , according to PitchBook , is now making a button into AI — a strategy foretell by new CEO Michael Tannenbaum , who left his station as COO at Brex to join the firm . “ I think that this was something that could really transubstantiate the fashion that fintech businesses work , ” he said of his move .
The key AI merchandise he ’s agitate for is to help with “ gaze and compare ” case in the lending process . He gave the model of a property - level verbal description , which is a unique description of the plus that has to be exactly the same on many of the legal documents . Traditionally , a human would have to front through over 60 page to ensure the description is the same . Tannenbaum said their unexampled feature massively fall the manual labor and time it take to verify the documents . It ’s an exercise , he say , of AI “ taking costs out of complex cognitive operation . ”
Given the personal information in loan applications , the company had to go back and forth with OpenAI to make indisputable their privateness concord was ironclad and “ that the model were not being school on our customer data in a certain way , ” he said .
Although the feature runs on GPT-4 , Ruben Padron , chief data officer , emphasized that the company made it a priority to build model - agnostic system . “ We ’re constantly test and value different models as they come out , and almost hebdomadal , or sometimes day by day , ” he said . Their systems “ offer us a lot of flexibleness to give up us to apace and dynamically pivot to whatever vendor is offer the highest functioning . ”
Padron sees many more AI offerings in Figure ’s hereafter , emphasise that the more they can automate the lending program cognitive operation , the less chance for error or bias . “ We ’re really trying to lower the cost , pass the manual work , concentrate the bias , ” Padron say . “ It ’s very much a journey . It ’s not a destination . ”
