<transcript><audio_23>you know but they weren't making money and so we took their bureau best practice model which was based on logistic regression and primarily used credits a credit score and we replaced</transcript><transcript><audio_24>it with a machine learning based model that instead of looking at four attributes which is FICO score debt to income ratio trade lines and inquiry</transcript><transcript><audio_25>counts we looked at over 2000 and that model when we just put it in initially derived a and fpd of 22% so in the first</transcript><transcript><audio_26>month we went from 38.2 to 22% but by making the model dynamic and every time someone paid or didn't pay alone injecting that in the model and retraining it it went from 22 to 18 the</transcript><transcript><audio_27>next month then from 18 to 15 then from 15 to 12 and then from 12 to 9 and eventually seven point a one of the things that you have to be careful about in doing this sort of thing is it's very</transcript> you know but they weren't making money and so we took their bureau best practice model which was based on logistic regression and primarily used credits a credit score and we replaced it with a machine learning based model that instead of looking at four attributes which is FICO score debt to income ratio trade lines and inquiry counts we looked at over 2000 and that model when we just put it in initially derived a and fpd of 22% so in the first month we went from 38.2 to 22% but by making the model dynamic and every time someone paid or didn't pay alone injecting that in the model and retraining it it went from 22 to 18 the next month then from 18 to 15 then from 15 to 12 and then from 12 to 9 and eventually seven point a one of the things that you have to be careful about in doing this sort of thing is it's very
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