The statement insights provide a clear and insightful analysis of a user's transactions over a certain period of time. This includes a general summary of the bank account, activity insights, transaction details, insights on repeat and recurring transactions, and some rare findings such as identical debits and credits, cash deposits larger than the salary, and immediate large withdrawals after the salary date. These insights are all important and can aid in credit scoring decisions.
Here's a breakdown of all insights that can be gotten from the statement insights API.
Variable | Description |
account | This is the account ID of the user whose account was linked. |
start_date | Date of earliest transaction linked on the account (YYYY-MM-DD). |
end_date | Date of latest transaction linked on the account (YYYY-MM-DD). |
transaction_length | Number of days between the first and last transaction |
transaction_count | Number of transactions found linked on the account |
balance_after_expense | Total credit amount minus total debit amount of all transactions |
opening_balance |
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closing_balance |
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average_balance | Average of |
debit_to_credit_ratio | Ratio of all debit to credit transactions |
overall_credits | Total credit amount within the duration |
overall_debits | Total debit amount within the duration |
number_of_credit_transactions | Number of all credit transactions |
number_of_debit_transactions | Number of all debit transactions |
total_recurring_credits | Total amount for all recurring credit transactions |
total_recurring_debits | Total amount for all recurring debit transactions |
immediate_large_withdrawal_post_payday | More than 2 occurrences of withdrawal >80% of salary within 24hrs of credit. |
identical_debit_vs_credit | This finds a match for the following criterias: |
cash_deposits_larger_than_salary | If salary is found; this returns credit amount higher than the salary amount. |
highest_debits | Top 3 highest debits showing the amount and date of transaction |
highest_credits | Top 3 highest credits showing the amount and date of transaction |
inflow | This breaks down the average monthly sums of |
outflow | This breaks down the average and total monthly sums of |
all_transaction | This section considers all transactions, whether they are repeated or not. It shows the average amount per month, as well as sum of all amounts for each month over the last 12 months. |
repeat_transactions | This section considers repeated transactions. It shows the average amount per month, as well as sum of all amounts for each month over the last 12 months. |
recurring_transactions | This returns the clusters of repeat transactions and its details. |
From the |
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i) description | This is the transaction description for the cluster. The version returned maybe a modified version that has been stripped some text like months and reference number |
ii) category | Cluster category returned from the transaction categoriser |
iii) type | The type of transactions in the cluster. This could be |
iv) count | Total number of transactions in the cluster |
v) stability | Variance of transaction amounts in the cluster. Ranges between 0-1. |
vi) consistency | Consistency of the transaction amounts in the cluster, weighted by days between transactions. Ranges between 0-1. |
vii) average_monthly_sum | Total monthly average / Number of months |
viii) average_days_between_transactions | Average number of days between transactions in the cluster |
ix) compound_monthly_growth_rate | monthly_growth_rate: monthly growth rate in total transaction amount for that cluster |