Bank Connection
Beam provides comprehensive analytics on bank statement data pulled through the bank connection in the Connect process.
The connect process must be complete for these endpoints to return a successful response.
Account Summary
The account statement summary endpoint can be used to fetch account summary data about all accounts fetched for a connection.
Label Transactions
Beam provides a transaction labeling endpoint. Beam analysese (by default) multiple transaction attributes to infer the transaction label, or "spend category". Beam's labeling engine has been trained on a large corpus of South African bank statement transactions.
- Returns a list of categorised bank statement transaction labels - assigned to each label;
- This endpoint is available as both single-record and batch requests.
Affordability
The get_affordability endpoint calculates a consumer's verified monthly average affordability, or "discretionary income", as defined by the NCA.
As per the NCA, discretionary income is defined as "Gross Income less statutory deductions such as income tax, unemployment insurance fund contributions, maintenance payments, necessary expenses and less all other committed payment obligations disclosed by the consumer, including such as may appear from the consumer’s credit records held by the credit bureaux, which income is the amount available to fund the proposed credit instalment."
Beam has endeavoured to calculate customer affordability in line with the above definition, ensuring end-users remain compliant with respect to the NCR.
Example response body:
{
"bank_connection": "66b9e5f46b1646ce983e767c",
"affordability": {
"monthly_affordability": [
{
"year": 2023,
"month": 8,
"primary_income": 0.0,
"secondary_income": 34086.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 34086.0,
"full_month": false
},
{
"year": 2023,
"month": 9,
"primary_income": 0.0,
"secondary_income": 56025.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 56025.0,
"full_month": true
},
{
"year": 2023,
"month": 10,
"primary_income": 0.0,
"secondary_income": 60729.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 60729.0,
"full_month": true
},
{
"year": 2023,
"month": 11,
"primary_income": 0.0,
"secondary_income": 61515.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 61515.0,
"full_month": true
},
{
"year": 2023,
"month": 12,
"primary_income": 0.0,
"secondary_income": 66402.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 66402.0,
"full_month": true
},
{
"year": 2024,
"month": 1,
"primary_income": 0.0,
"secondary_income": 69285.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 69285.0,
"full_month": true
},
{
"year": 2024,
"month": 2,
"primary_income": 0.0,
"secondary_income": 67425.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 67425.0,
"full_month": true
},
{
"year": 2024,
"month": 3,
"primary_income": 0.0,
"secondary_income": 74865.0,
"non_discretionary_expenses": 0.0,
"discretionary_expenses": 0.0,
"affordability_amount": 74865.0,
"full_month": true
},
],
"average_full_month_primary_income": 0.0,
"average_full_month_secondary_income": 70806.82,
"average_full_month_discretionary_expenses": 0.0,
"average_full_month_non_discretionary_expenses": 0.0,
"average_full_month_affordability": 70806.82
}
}
primary_income: aggregate amounts coming from primary income sources (eg Salaries & Wages).secondary_income: aggregate amounts coming from non-primary sources (eg Bank Transfers).non_discretionary_expenses: These are necessary expenses one cannot avoid and must pay typically on a regular basis. They're essential for day-to-day living or maintaining a basic standard of living (eg Utilities expenses).discretionary_expenses: These expenses are optional and are related to things you might want rather than need. They're often associated with leisure, luxury, or non-essential goods and services. (eg Nightlife & Entertainment)average_full_month_primary_income: average primary income for all months where the whole (full) month is available.average_full_month_secondary_income: average secondary income for all months where the whole (full) month is available.average_full_month_non_discretionary_expenses: average non-discretionary expenses for all months where the whole (full) month is available.average_full_month_discretionary_expenses: average discretionary expenses for all months where the whole (full) month is available.average_full_month_affordability: average affordability for all months where the whole (full) month is available.
Income Analysis
The get_income_analysis endpoint provides a detailed analysis on Primary Income lines (ie Salaries and Wages). This analysis primarily comprises of three metrics:
Example response body:
{
"bank_connection": "66b9e5f46b1646ce983e767c",
"income_analysis": {
"consistency_score": 0.6,
"longevity_score": 0.6,
"regularity_score": 0.6,
"income_month_breaks": 0.6,
"income_indicator": 0.6,
"months_back": 0.6,
"income_heatmap": {
"1": 0.6226091983885061,
"2": 0.6566979036690341,
"3": 0.6908305188318503,
"4": 0.725007043876948,
"5": 0.7592274788043323,
"6": 0.7934918236140031,
"7": 0.8278000783059554,
"8": 0.8621522428801923,
"9": 0.8965483173367179,
"10": 0.9309883016755265,
"11": 0.9654721958966198,
"12": 1.0,
"13": 0.0,
"14": 0.03327637245825698,
"15": 0.06659665479880061,
"16": 0.0999608470216291,
"17": 0.1333689491267407,
"18": 0.1668209611141407,
"19": 0.20031688298382197,
"20": 0.23385671473578815,
"21": 0.26744045637004277,
"22": 0.3010681078865804,
"23": 0.33473966928540116,
"24": 0.36845514056651035,
"25": 0.40221452172990263,
"26": 0.436017812775578,
"27": 0.4698650137035419,
"28": 0.5037561245137887,
"29": 0.5376911452063204,
"30": 0.5432171373617541,
"31": 0.5422054992945656
},
"strike_date": 12.0
}
}
consistency_score: Measures how stable the salary amount is. More variable month-over-month salary amounts reduce this score.longevity_score: Measures the time period in which the customer's primary income has been detected. A longer history of salary lines being detected improves this score.regularity_score: Measures income "strike" date regularity. More variation in the day of month the salary being received reduces this score.misc_info: More granular income metadata.income_month_breaks- number of breaks in income detected.income_indicator- periodicity of income: monthly, bi-weekly, weekly or irregular (for when no discernable pattern is detected).months_back- total income history length, measured in months.
income_heatmap: A 'day-of-month' distribution of all inflows into the user's bank account, averaged over the entire statement history.strike_date: Recommended strike date for debiting the customer's account, defined as the day of the month where the most income was received, on average.
Risk Insights
This series of endpoints provide behavioural insights into a customer's spending habits. The Risk Insights series comprises of:
Gambling
The Gambling insight provides standardised metrics into all gambling transactions. For months with both salary lines, and gambling lines, the function returns:
- Year;
- Month;
- Total Gambling Spend for the month;
- Total Salary for the month;
Gamblingspend as a proportion ofSalary.
Overdraft Usage
The Overdraft insight provides standardised metrics into a client's use of their bank overdraft. Where applicable, this endpoint calculates:
- The number of days the balance is less than 0 - in this case defined as overdraft - for each calendar month;
- Total days in overdraft over observation period;
- Total (unique) days in period;
- Ratio of Overdraft Days as a proportion of Total Days in Period;
Returned Debit Orders
This endpoint returns metrics on a customer's predicted number of returned (bounced) Debit Orders. Specifically, this endpoint returns:
- Predicted count of returned debit orders in the past:
- Month
- 3 months
- 6 months
- 12 months
- Average over all months
ATM & Cash Withdrawals
This insight returns standardised metrics around a user's ATM and Cash withdrawal behaviour. Specifically, this endpoint will return:
- Predicted monthly amount of cash drawn;
- Corresponding salary amount (where applicable);
- Ratio of ATM & Cash Withdrawals to Salary (where available);
- Predicted average over all months.
Net Saver or Spender
This insight tracks the customer's aggregated balances across all accounts and returns whether the trend shows a net increase (saver) or decrease (spender) in balance.
- Returns "Net Saver" or "Net Spender" depending on whether the gradient of the line of best fit through the aggregate balance is positive or negative, respectfully.
Social Security Insights
This insight tracks for any Social Security, pension or UIF payments being made into the account. These payments are indicators of unemployment or retirement, indicating financial instability.
- Returns monthly Social Security inflows (by month).
- Returns monthly average SS inflows, over the entire balance term.
Example response body:
{
"bank_connection": "66b9e5f46b1646ce983e767c",
"risk_insights": {
"begin_date": "2023-08-13",
"end_date": "2024-08-12",
"risk_insights": {
"gambling_insights": {
"monthly_gambling_analysis": [
{
"year": 2023,
"month": 8,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2023,
"month": 9,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2023,
"month": 10,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2023,
"month": 11,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2023,
"month": 12,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 1,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 2,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 3,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 4,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 5,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 6,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 7,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
},
{
"year": 2024,
"month": 8,
"total_gambling_amount": 0.0,
"total_salary_amount": 0.0,
"gambling_proportion": 0.0
}
],
"monthly_average_gambling_spend": 0.0,
"monthly_average_gambling_proportion": 0.0
},
"overdraft_insights": {
"total_days_in_overdraft": 0,
"total_proportion_of_days_in_overdraft": 0.0,
"unique_months": 13,
"monthly_average_days_in_overdraft": 0.0,
"monthly_overdraft_analysis": [
{
"year": 2023,
"month": 8,
"days_in_overdraft": 0
},
{
"year": 2023,
"month": 9,
"days_in_overdraft": 0
},
{
"year": 2023,
"month": 10,
"days_in_overdraft": 0
},
{
"year": 2023,
"month": 11,
"days_in_overdraft": 0
},
{
"year": 2023,
"month": 12,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 1,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 2,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 3,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 4,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 5,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 6,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 7,
"days_in_overdraft": 0
},
{
"year": 2024,
"month": 8,
"days_in_overdraft": 0
}
]
},
"returned_debit_orders_insights": {
"last_month_count": 0.0,
"last_3_months_count": 0.0,
"last_6_months_count": 0.0,
"last_12_months_count": 0.0,
"monthly_average_debit_order_value": 0.0
},
"atm_and_cash_insights": {
"monthly_atm_and_cash_spend_analysis": [
{
"year": 2023,
"month": 8,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2023,
"month": 9,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2023,
"month": 10,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2023,
"month": 11,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2023,
"month": 12,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 1,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 2,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 3,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 4,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 5,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 6,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 7,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
},
{
"year": 2024,
"month": 8,
"total_withdrawal_amount": 0.0,
"total_salary_amount": 0.0,
"cash_proportion": 0.0
}
],
"atm_and_cash_average_amount": 0.0,
"average_withdrawal_proportion": 0.0
},
"net_saver_spender_insights": {
"net_saver_spender": "Net Saver"
},
"ssi_insights": {
"monthly_ssi_analysis": [
{
"year": 2023,
"month": 8,
"total_social_security_amount": 0.0
},
{
"year": 2023,
"month": 9,
"total_social_security_amount": 0.0
},
{
"year": 2023,
"month": 10,
"total_social_security_amount": 0.0
},
{
"year": 2023,
"month": 11,
"total_social_security_amount": 0.0
},
{
"year": 2023,
"month": 12,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 1,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 2,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 3,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 4,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 5,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 6,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 7,
"total_social_security_amount": 0.0
},
{
"year": 2024,
"month": 8,
"total_social_security_amount": 0.0
}
],
"monthly_average_ssi": 0.0
}
}
}
}
Liquidity Score
The Liquidity Score predicts how cashflow positive an individual's bank account will remain in the future. This is quantified as the likelihood an individual will remain above R0 across all bank accounts over the defined term.
Specifically, this calculates the likelihood an individual's aggregate account balance will remain above R0 over the next:
- 30,
- 60,
- 90 days
After accounting for future balance forecasts, as well as accounting for prior balance history and statistical shocks.
Example response body:
{
"bank_connection": "66b9e5f46b1646ce983e767c",
"liquidity_score": {
"start_date": "2023-08-13",
"end_date": "2024-08-12",
"field_30_day_liquidity_score": 100.0,
"field_60_day_liquidity_score": 100.0,
"field_90_day_liquidity_score": 100.0,
"balance_forecast": [
{
"date": "2024-08-13",
"balance": 1365174.0
},
{
"date": "2024-08-14",
"balance": 1371509.19
},
{
"date": "2024-08-15",
"balance": 1373937.21
},
{
"date": "2024-08-16",
"balance": 1376301.65
},
{
"date": "2024-08-17",
"balance": 1378622.65
},
{
"date": "2024-08-18",
"balance": 1380921.55
},
{
"date": "2024-08-19",
"balance": 1383217.67
},
{
"date": "2024-08-20",
"balance": 1385525.7
},
{
"date": "2024-08-21",
"balance": 1387854.13
},
{
"date": "2024-08-22",
"balance": 1390205.03
},
{
"date": "2024-08-23",
"balance": 1392575.01
},
{
"date": "2024-08-24",
"balance": 1394957.17
},
{
"date": "2024-08-25",
"balance": 1397343.39
},
{
"date": "2024-08-26",
"balance": 1399726.56
},
{
"date": "2024-08-27",
"balance": 1402102.22
},
{
"date": "2024-08-28",
"balance": 1404469.33
},
{
"date": "2024-08-29",
"balance": 1406830.05
},
{
"date": "2024-08-30",
"balance": 1409188.84
},
{
"date": "2024-08-31",
"balance": 1411550.98
},
{
"date": "2024-09-01",
"balance": 1413921.1
},
{
"date": "2024-09-02",
"balance": 1416302.01
},
{
"date": "2024-09-03",
"balance": 1418694.15
},
{
"date": "2024-09-04",
"balance": 1421095.66
},
{
"date": "2024-09-05",
"balance": 1423503.1
},
{
"date": "2024-09-06",
"balance": 1425912.51
},
{
"date": "2024-09-07",
"balance": 1428320.52
},
{
"date": "2024-09-08",
"balance": 1430725.2
},
{
"date": "2024-09-09",
"balance": 1433126.53
},
{
"date": "2024-09-10",
"balance": 1435526.22
},
{
"date": "2024-09-11",
"balance": 1437927.16
},
{
"date": "2024-09-12",
"balance": 1440332.55
},
{
"date": "2024-09-13",
"balance": 1442744.98
},
{
"date": "2024-09-14",
"balance": 1445165.8
},
{
"date": "2024-09-15",
"balance": 1447594.75
},
{
"date": "2024-09-16",
"balance": 1450030.18
},
{
"date": "2024-09-17",
"balance": 1452469.57
},
{
"date": "2024-09-18",
"balance": 1454910.22
},
{
"date": "2024-09-19",
"balance": 1457350.08
},
{
"date": "2024-09-20",
"balance": 1459788.24
},
{
"date": "2024-09-21",
"balance": 1462225.13
},
{
"date": "2024-09-22",
"balance": 1464662.37
},
{
"date": "2024-09-23",
"balance": 1467102.24
},
{
"date": "2024-09-24",
"balance": 1469547.06
},
{
"date": "2024-09-25",
"balance": 1471998.47
},
{
"date": "2024-09-26",
"balance": 1474457.09
},
{
"date": "2024-09-27",
"balance": 1476922.3
},
{
"date": "2024-09-28",
"balance": 1479392.52
},
{
"date": "2024-09-29",
"balance": 1481865.63
},
{
"date": "2024-09-30",
"balance": 1484339.65
},
{
"date": "2024-10-01",
"balance": 1486813.22
},
{
"date": "2024-10-02",
"balance": 1489286.0
},
{
"date": "2024-10-03",
"balance": 1491758.73
},
{
"date": "2024-10-04",
"balance": 1494232.97
},
{
"date": "2024-10-05",
"balance": 1496710.68
},
{
"date": "2024-10-06",
"balance": 1499193.63
},
{
"date": "2024-10-07",
"balance": 1501682.9
},
{
"date": "2024-10-08",
"balance": 1504178.62
},
{
"date": "2024-10-09",
"balance": 1506679.94
},
{
"date": "2024-10-10",
"balance": 1509185.3
},
{
"date": "2024-10-11",
"balance": 1511692.87
},
{
"date": "2024-10-12",
"balance": 1514201.09
},
{
"date": "2024-10-13",
"balance": 1516709.1
},
{
"date": "2024-10-14",
"balance": 1519216.95
},
{
"date": "2024-10-15",
"balance": 1521725.6
},
{
"date": "2024-10-16",
"balance": 1524236.6
},
{
"date": "2024-10-17",
"balance": 1526751.66
},
{
"date": "2024-10-18",
"balance": 1529272.18
},
{
"date": "2024-10-19",
"balance": 1531798.81
},
{
"date": "2024-10-20",
"balance": 1534331.33
},
{
"date": "2024-10-21",
"balance": 1536868.71
},
{
"date": "2024-10-22",
"balance": 1539409.38
},
{
"date": "2024-10-23",
"balance": 1541951.74
},
{
"date": "2024-10-24",
"balance": 1544494.55
},
{
"date": "2024-10-25",
"balance": 1547037.34
},
{
"date": "2024-10-26",
"balance": 1549580.47
},
{
"date": "2024-10-27",
"balance": 1552125.08
},
{
"date": "2024-10-28",
"balance": 1554672.72
},
{
"date": "2024-10-29",
"balance": 1557224.91
},
{
"date": "2024-10-30",
"balance": 1559782.72
},
{
"date": "2024-10-31",
"balance": 1562346.48
},
{
"date": "2024-11-01",
"balance": 1564915.66
},
{
"date": "2024-11-02",
"balance": 1567489.06
},
{
"date": "2024-11-03",
"balance": 1570065.12
},
{
"date": "2024-11-04",
"balance": 1572642.42
},
{
"date": "2024-11-05",
"balance": 1575220.01
},
{
"date": "2024-11-06",
"balance": 1577797.73
},
{
"date": "2024-11-07",
"balance": 1580376.24
},
{
"date": "2024-11-08",
"balance": 1582956.84
},
{
"date": "2024-11-09",
"balance": 1585541.07
},
{
"date": "2024-11-10",
"balance": 1588130.28
}
]
}
}
balance_forecast: returns daily aggregate balance predictions for 90 days in the future, starting from the application date.
Expense Analysis
The Expense Analysis endpoint provides a detailed breakdown of an individual's expenses. The endpoint returns the aggregate - as well as proportionate - amount spent on each expense category over the analysis period, ordered from largest to smallest category.
Finally, the endpoint returns the split of discretionary vs non-discretionary expenses over the analysis window, with a count of unique months analysed.
Example response body:
{
"bank_connection": "66c5f3eb4e7cecced7i82fe4",
"expenses_insights": {
"top_expense_amounts": [
{
"label": "Subscriptions",
"amount": 32984.48,
"average_monthly_spend": 4712.07,
"percentage_of_total_spend": 28.81
},
{
"label": "Eating Out",
"amount": 25224.67,
"average_monthly_spend": 3603.52,
"percentage_of_total_spend": 22.03
},
{
"label": "Online Purchase",
"amount": 12110.57,
"average_monthly_spend": 1730.08,
"percentage_of_total_spend": 10.58
},
{
"label": "Fuel",
"amount": 8600.28,
"average_monthly_spend": 1228.61,
"percentage_of_total_spend": 7.51
},
{
"label": "Groceries",
"amount": 5216.45,
"average_monthly_spend": 745.21,
"percentage_of_total_spend": 4.56
},
{
"label": "Bank Transfer Out",
"amount": 3975.22,
"average_monthly_spend": 567.89,
"percentage_of_total_spend": 3.47
},
{
"label": "Nightlife & Entertainment",
"amount": 3816.93,
"average_monthly_spend": 545.28,
"percentage_of_total_spend": 3.33
},
{
"label": "Coffee",
"amount": 3764.0,
"average_monthly_spend": 537.71,
"percentage_of_total_spend": 3.29
},
{
"label": "Home and Garden",
"amount": 3187.74,
"average_monthly_spend": 455.39,
"percentage_of_total_spend": 2.78
},
{
"label": "Ride Sharing",
"amount": 3012.84,
"average_monthly_spend": 430.41,
"percentage_of_total_spend": 2.63
},
{
"label": "General Purchases",
"amount": 2606.6,
"average_monthly_spend": 372.37,
"percentage_of_total_spend": 2.28
},
{
"label": "Health and Medical",
"amount": 2495.57,
"average_monthly_spend": 356.51,
"percentage_of_total_spend": 2.18
},
{
"label": "Personal Care",
"amount": 2488.36,
"average_monthly_spend": 355.48,
"percentage_of_total_spend": 2.17
},
{
"label": "Clothing",
"amount": 2472.77,
"average_monthly_spend": 353.25,
"percentage_of_total_spend": 2.16
},
{
"label": "Sport",
"amount": 1474.68,
"average_monthly_spend": 210.67,
"percentage_of_total_spend": 1.29
},
{
"label": "Transport",
"amount": 374.08,
"average_monthly_spend": 53.44,
"percentage_of_total_spend": 0.33
},
{
"label": "Prepaid Data Purchase",
"amount": 250.0,
"average_monthly_spend": 35.71,
"percentage_of_total_spend": 0.22
},
{
"label": "Electronics and Appliances",
"amount": 188.51,
"average_monthly_spend": 26.93,
"percentage_of_total_spend": 0.16
},
{
"label": "Bank Charges and Fees",
"amount": 186.19,
"average_monthly_spend": 26.6,
"percentage_of_total_spend": 0.16
},
{
"label": "Parking",
"amount": 42.0,
"average_monthly_spend": 6.0,
"percentage_of_total_spend": 0.04
},
{
"label": "Gambling",
"amount": 20.0,
"average_monthly_spend": 2.86,
"percentage_of_total_spend": 0.02
},
{
"label": "Insufficient Funds Fee",
"amount": 8.5,
"average_monthly_spend": 1.21,
"percentage_of_total_spend": 0.01
},
{
"label": "Uncategorised",
"amount": 8.5,
"average_monthly_spend": 1.21,
"percentage_of_total_spend": 0.01
}
],
"unique_months": 7,
"spend_split": {
"discretionary_spend_percentage": 95.27,
"non_discretionary_spend_percentage": 4.73
}
}
}