"Features" are values derived from the user’s data, which can be used directly in a loan decisioning flow. They are returned in the decision endpoint. Definitions of the features generated by Pngme are:

featuredefinitionresponse value
average_end_of_day_depository_balance_{t0_days}_{t1_days}Average of daily total balance held in all depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
average_end_of_day_loan_balance_{t0_days}_{t1_days}Average of daily total balance held in all loan accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
count_airtime_purchase_events_{t0_days}_{t1_days}count of airtime purchase events, across all of a user's airtime accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_betting_and_lottery_events_{t0_days}_{t1_days}Distinct BettingAndLottery alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_insufficient_funds_events_{t0_days}_{t1_days}Distinct InsufficientFunds alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_loan_declined_events_{t0_days}_{t1_days}Distinct LoanDeclined alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_loan_defaulted_events_{t0_days}_{t1_days}count of loan defaulted events, across all of a user's accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.int
count_loan_missed_payment_events_{t0_days}_{t1_days}Distinct LoanMissedPayment alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_loan_opened_events_{t0_days}_{t1_days}Distinct LoanApproved or LoanDisbursed alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_loan_repayment_events_{t0_days}_{t1_days}Distinct LoanRepayment alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_of_institutions_{t0_days}_{t1_days}Count of financial institutions a given user is associated with, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_overdraft_events_{t0_days}_{t1_days}Distinct Overdraft alerts received, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_transactions_depository_{t0_days}_{t1_days}Count of depository transactions, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
count_user_shared_device_ids_0_10Distinct users using the same device updated within the time range.{int, null}
count_user_shared_phone_numbers_0_10Distinct users with the same phone number updated within the time range.{int, null}
daily_average_of_stacked_loan_alerts_0_90Daily average of count of open loans over a given period using alerts as source.{float, null}
daily_average_of_stacked_loan_fes_0_90Daily average of count of open loans over a given period using financial events as source.{float, null}
data_density_{t0_days}_{t1_days}Ratio of active user days to total number of days in range, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
data_recency_minutesReturn the time in minutes between utc_endtime and the most recent financial event or alert, as an indicator of data recency, or freshness.{int, null}
difference_count_of_loans_opened_to_loans_delinquent_{t0_days}_{t1_days}Returns the count of loans approved or disbursed - loans defaulted or missed payments, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
difference_count_of_loans_opened_to_loans_repaid_{t0_days}_{t1_days}Returns the count of loans approved or disbursed - loans repaid, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{int, null}
loan_sharks_alert_institutions_ratio_0_90Ratio of loan shark related financial events over total events over a given period.{float, null}
loan_sharks_fes_ratio_0_90Ratio of loan shark institutions over total seen institutions over a given period.{float, null}
median_end_of_day_depository_balance_{t0_days}_{t1_days}Median of daily total balance held in all depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
min_end_of_day_depository_balance_{t0_days}_{t1_days}Minimum daily total balance held in all depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
net_cash_flow_{t0_days}_{t1_days}Difference between credit and debit transactions across depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
primary_currencyReturns the primary currency based on the user's primitives data.{str, null}
slope_end_of_day_depository_balance_0_90Rate of change of daily total balance held in all depository accounts.{float, null}
slope_end_of_day_loan_balance_0_90Rate of change of daily total balance held in all loan accounts.{float, null}
stdev_end_of_day_depository_balance_{t0_days}_{t1_days}Standard deviation of daily total balance held in all depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
sum_of_airtime_credits_{t0_days}_{t1_days}Total of credit transactions across airtime accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
sum_of_credits_{t0_days}_{t1_days}Total of credit transactions across depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
sum_of_debits_{t0_days}_{t1_days}Total of debit transactions across depository accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
sum_of_depository_balances_latestTotal of latest balances summed across all depository accounts.{float, null}
sum_of_depository_transactions_between_user_accounts_{t0_days}_{t1_days}Total sum of transaction amounts potentially taking place
between depository accounts associated with the given user
{float, null}
sum_of_loan_repayments_{t0_days}_{t1_days}Total of credit transactions across loan accounts, over the previous t0 to t1 days, where the time windows are 0-30, 31-90, or 0-90 days history prior to the utc_time date.{float, null}
The {feature}_was_imputed feature equal to 1 indicates that the feature value had a missing value imputed.Imputation is performed for features that can reasonably have a missing value replaced.{boolean}