what is a good probability for predicting default on loan?
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i'm attempting to answer a question for a job interview, where i am given a dataset of customer data showing the customer's bank transactions over the past year, and asked to calculate the probability that the customer will default on a loan based on their data.
so far, i've been able to achieve around 75% using a simple binary classifier in Keras. i based the features on things such as maximum deposit, # withdrawals, etc.
i'm wondering, is 75% considered good for such a type of problem? i have very little experience in this field. obviously, if i was working with mnist, 75% would by abysmal, but with this type of data, perhaps it is quite good?
just wondering if anyone has a sense for this type of data, and what probability they consider good for predicting whether a customer will default on a loan or not, thanks,
deep-learning classification keras categorical-data
asked yesterday
Russell ButlerRussell Butler
162
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add a comment |
$begingroup$
i'm attempting to answer a question for a job interview, where i am given a dataset of customer data showing the customer's bank transactions over the past year, and asked to calculate the probability that the customer will default on a loan based on their data.
so far, i've been able to achieve around 75% using a simple binary classifier in Keras. i based the features on things such as maximum deposit, # withdrawals, etc.
i'm wondering, is 75% considered good for such a type of problem? i have very little experience in this field. obviously, if i was working with mnist, 75% would by abysmal, but with this type of data, perhaps it is quite good?
just wondering if anyone has a sense for this type of data, and what probability they consider good for predicting whether a customer will default on a loan or not, thanks,
deep-learning classification keras categorical-data
asked yesterday
Russell ButlerRussell Butler
162
$endgroup$
$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago
add a comment |
$begingroup$
i'm attempting to answer a question for a job interview, where i am given a dataset of customer data showing the customer's bank transactions over the past year, and asked to calculate the probability that the customer will default on a loan based on their data.
so far, i've been able to achieve around 75% using a simple binary classifier in Keras. i based the features on things such as maximum deposit, # withdrawals, etc.
i'm wondering, is 75% considered good for such a type of problem? i have very little experience in this field. obviously, if i was working with mnist, 75% would by abysmal, but with this type of data, perhaps it is quite good?
just wondering if anyone has a sense for this type of data, and what probability they consider good for predicting whether a customer will default on a loan or not, thanks,
deep-learning classification keras categorical-data
asked yesterday
Russell ButlerRussell Butler
162
$endgroup$
i'm attempting to answer a question for a job interview, where i am given a dataset of customer data showing the customer's bank transactions over the past year, and asked to calculate the probability that the customer will default on a loan based on their data.
so far, i've been able to achieve around 75% using a simple binary classifier in Keras. i based the features on things such as maximum deposit, # withdrawals, etc.
i'm wondering, is 75% considered good for such a type of problem? i have very little experience in this field. obviously, if i was working with mnist, 75% would by abysmal, but with this type of data, perhaps it is quite good?
just wondering if anyone has a sense for this type of data, and what probability they consider good for predicting whether a customer will default on a loan or not, thanks,
deep-learning classification keras categorical-data
deep-learning classification keras categorical-data
asked yesterday
Russell ButlerRussell Butler
162
asked yesterday
Russell ButlerRussell Butler
162
asked yesterday
Russell ButlerRussell Butler
162
asked yesterday
Russell ButlerRussell Butler
162
asked yesterday
Russell ButlerRussell Butler
162
162
$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago
add a comment |
$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago
$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago
add a comment |
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$begingroup$
This question is fairly objective, but can be broken down to, with what probability are you willing to lose money investing in a mortgage backed asset or issuing a home loan.
$endgroup$
– Ethan
yesterday
$begingroup$
@Ethan yes...good point, and i'm sure there are lots of economic factors outside of the individual's control that you would have a tough time predicting from their transaction history alone...which is why i'm thinking that prediction accuracy probably isn't much better than 70-80%, though i'm not sure..
$endgroup$
– Russell Butler
22 hours ago