MISSION LANE
Q : Legacy sources of credit ratings have made access to finance harder for disenfranchised communities in the past , what makes your proprietary machine learning system for credit ratings unique ? We do not use traditional credit scores like FICO in our underwriting . FICO is useful for categorising segments of customers and cross-referencing with other companies , but we have found that incorporating new data sources -- as well as getting more granular with traditional data -- gives a much sharper picture of a person ’ s credit situation . The most powerful data insights are those we generate through endless cycles of proprietary , systematic testing .
“ The foundation of financial education is helping consumers who are new to credit understand how the system can work for them instead of against them ”
SHANE HOLDAWAY CEO , MISSION LANE
Equally important is how we organise our data and ourselves . We make sure our data insights are not siloed into one unit but rather integrated through every aspect of our business . At many companies , data teams act as ticket takers , fulfilling requests by different teams . At Mission Lane , we ensure that data is a core competency across all business units , allowing us to continually improve not only underwriting processes but also product development , customer experience , and other areas .
Q : What are the opportunities and threats of artificial intelligence in the financial services industry ? Data and AI can have benefits across marketing , acquisitions , fraud , and operations by