Available Annotations

Annotations are actions applied to data that has already been processed or derived from other sources. These actions help add more context to the data. In a journey, businesses can configure one or more annotations depending on what additional information they need, allowing for a flexible and customised process.

📘
Currently, none of the annotations are pre-configured in our journeys. To configure any annotation with your journey reach out to your account manager.

Currently, we support the following annotations:

Watermarking

Through this annotation the businesses can watermark any user pdf or image to authenticate any information and use-case for which that information was captured with some text. The position of the text, font-size, font-colour are configurable as per the business requirements.

{
  "status": "DUMMY_STATUS",
  "message": "DUMMY_MESSAGE",
  "status_code": "DUMMY_STATUS_CODE",
  "transaction_id": "DUMMY_TRANSACTION_ID",
  "journey_transaction_id": "DUMMY_JOURNEY_TRANSACTION_ID",
  "journey_id": "DUMMY_JOURNEY_ID",
  "data": {
    "insights": {
      "user_document_annotation": [
        {
          "data": {
            "watermarked_doc_s3_url": "DUMMY_WATERMARKED_DOC_URL",
            "watermarked_doc_base64": "DUMMY_WATERMARKED_BASE64"
          }
        }
      ]
    }
  }
}

Loan Transactions: EMI Debits and Loan Credits Annotations

These annotations can be configured within the Bank Statement Analytics Journey to extract information about the user's loan and EMI transactions.

EMI Debit Amount

The EMI Debit Amount annotation provides the total value of EMI debits within the configured period. The system groups the amounts by the chosen time frame (e.g., monthly) and sorts them based on the configuration (e.g., descending order). This helps to analyze patterns in EMI repayments over time. The data includes values representing each period, making it easy to identify fluctuations in EMI amounts.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_emi_debit_amount": [
    {
      "data": {
        "emi_debit_amounts": [
          0.0,
          0.0,
          18901.25,
          44529.95,
          28151.730000000003,
          13093.47,
          22263.48,
          25005.559999999998,
          24434.739999999998,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_emi_debit_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb"
      "config": {
        "period": 13,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

EMI Debit Count

The EMI Debit Count annotation records the number of EMI debit transactions within the configured time frame. Grouped by a specified period (e.g., monthly), this count helps businesses track how often EMI payments are made by a user, aiding in assessing repayment consistency. The annotation also allows for sorting to reveal trends in the frequency of EMI debits over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_emi_debit_count": [
    {
      "data": {
        "emi_debit_counts": [
          0.0,
          0.0,
          3.0,
          8.0,
          4.0,
          4.0,
          4.0,
          4.0,
          5.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_emi_debit_count",
      "id": "4dfa35f3-d77e-43b7-b3cb-e3ea40f61d52",
      "config": {
        "period": 13,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Loan Credit Amount

The Loan Credit Amount annotation provides the total value of loan credits received by the user within a configured period. Grouped by time frames such as months, this data helps businesses understand the loan disbursement trends. Sorting options, such as descending order, allow businesses to easily focus on periods with significant loan credits, aiding in analyzing borrowing patterns.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_loan_credit_amount": [
    {
      "data": {
        "loan_credit_amounts": [
          3845.68,
          0.0,
          0.0,
          0.0,
          0.0,
          1729.83,
          11423.89,
          2553.34,
          0.0,
          7241.68,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_loan_credit_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "grouping": "Monthly",
        "sortby": "descending"
      }
    }
  ]
}

Loan Credit Count

The Loan Credit Count annotation records the number of loan credit transactions within a specified period. Like other annotations, it groups the data based on a time frame (e.g., monthly) and sorts it according to the business's requirements. This helps in assessing how often loans are credited to a user's account, which can be useful for understanding their borrowing behavior over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_loan_credit_count": [
    {
      "data": {
        "loan_credit_counts": [
          1,
          0.0,
          0.0,
          0.0,
          0.0,
          1,
          2,
          1,
          0.0,
          2,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_loan_credit_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "grouping": "Monthly",
        "sortby": "descending"
      }
    }
  ]
}

Investment Transactions Annotations

These annotations can be configured within the Bank Statement Analytics Journey to gather insights on the user's investment transactions. Businesses can customize the analysis period (12 months, 13 months, etc.), select time grouping (weekly, monthly, etc.), and determine sorting preferences (ascending, descending) based on their specific needs.

Investment Credit Amount

The Investment Credit Amount annotation captures the total amount credited for investments over the specified period. Grouped by the chosen time frame (e.g., monthly), this data helps businesses identify patterns in investment inflows. Sorting options like descending order make it easier to spot high-credit periods, which may indicate significant investment activity.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_investment_credit_amount": [
    {
      "data": {
        "investment_credit_amounts": [
          0.0,
          0.0,
          0.0,
          0.0,
          4455.67,
          0.0,
          0.0,
          0.0,
          3726.01,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_investment_credit_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Investment Debit Amount

The Investment Debit Amount annotation provides the total amount debited from the account for investments during a selected time period. By grouping the data (e.g., monthly) and sorting it in a specified order (e.g., descending), businesses can easily track investment outflows and analyze investment-related spending patterns over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_investment_debit_amount": [
    {
      "data": {
        "investment_debit_amounts": [
          1198.72,
          2538.97,
          3121.85,
          17745.55,
          6947.65,
          0.0,
          2706.57,
          0.0,
          0.0,
          8963.21,
          0.0,
          0.0,
          0.0
        ]
      },
      "id": "grouped_investment_debit_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Credit Card Payments Annotations

These annotations can be configured within the Bank Statement Analytics Journey to track information related to the user's credit card payments. Businesses have the flexibility to define the analysis period (12 months, 13 months, etc.), choose time grouping (weekly, monthly, etc.), and adjust sorting (ascending, descending) according to their requirements.

Credit Card Payment Amount

The Credit Card Payment Amount annotation tracks the total amount paid toward credit card bills during the chosen analysis period. This data is grouped by the selected time frame (e.g., monthly) and sorted as required (e.g., descending), providing businesses with insights into the user's credit card payment behaviour.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_creditcard_payment_amount": [
    {
      "data": {
        "creditcard_payment_amounts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_creditcard_payment_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Credit Card Payment Count

The Credit Card Payment Count annotation records the number of credit card payment transactions within a defined time frame. Grouped by the chosen period (e.g., monthly), this helps businesses assess how often users make payments toward their credit card bills, offering insights into payment habits.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_creditcard_payment_count": [
    {
      "data": {
        "creditcard_payment_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_creditcard_payment_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Cash Withdrawals Annotations

These annotations can be configured within the Bank Statement Analytics Journey to analyze the user's cash withdrawal transactions. Businesses can set the analysis period (12 months, 13 months, etc.), opt for time grouping (weekly, monthly, etc.), and select sorting (ascending, descending) to align with their needs.

Cash Withdrawl Amount

The Cash Withdrawal Amount annotation tracks the total amount withdrawn in cash during a defined period. Grouped by time intervals (e.g., monthly) and sorted according to business preferences, this data provides valuable insights into a user's cash withdrawal habits, helping businesses understand cash usage trends.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_cash_withdrawal_amount": [
    {
      "data": {
        "cash_withdrawal_amounts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_cash_withdrawal_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Cash Withdrawl Count

The Cash Withdrawal Count annotation records the number of cash withdrawals made during the analysis period. By grouping and sorting the data (e.g., monthly in descending order), businesses can evaluate how frequently the user relies on cash withdrawals over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_cash_withdrawal_count": [
    {
      "data": {
        "cash_withdrawal_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_cash_withdrawal_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

UPI Transactions Annotations

These annotations can be configured within the Bank Statement Analytics Journey to examine the user's UPI transaction history. Businesses can specify the analysis period (12 months, 13 months, etc.), determine time grouping (weekly, monthly, etc.), and adjust sorting preferences (ascending, descending) to meet their requirements.

UPI Credit Count

The UPI Credit Count annotation tracks the number of UPI credit transactions (i.e., funds received via UPI) over the configured time period. The data can be grouped (e.g., monthly) and sorted (e.g., descending), enabling businesses to assess the frequency of UPI credits and understand transaction behavior over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_upi_credits_count": [
    {
      "data": {
        "upi_credit_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_upi_credits_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

UPI Credit Amount

The UPI Credit Amount annotation captures the total value of UPI credits over the specified analysis period. Grouped and sorted as required, this data provides insights into the user's UPI income trends and helps businesses understand the financial inflow through UPI.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_upi_credits_amount": [
    {
      "data": {
        "upi_credit_amounts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_upi_credits_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

UPI Debit Count

The UPI Debit Count annotation records the number of UPI debit transactions (i.e., payments made via UPI) during the configured period. The ability to group and sort this data allows businesses to analyze spending behavior through UPI and assess the frequency of outgoing payments.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_upi_debits_count": [
    {
      "data": {
        "upi_debit_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_upi_debits_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

UPI Debit Amount

The UPI Debit Amount annotation tracks the total value of UPI debits over the defined time period. Grouped by a chosen time frame (e.g., monthly) and sorted as per business needs, this data helps in identifying UPI outflow trends, providing insight into the user’s payment activities.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_upi_debits_amount": [
    {
      "data": {
        "debit_amounts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_total_upi_debits_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Account Balance Summary (Low balance, high balance days, median balance) Annotations

These annotations can be configured within the Bank Statement Analytics Journey to provide a summary of the user's account balance, highlighting low balance days, high balance days, and median balance. Businesses can choose the analysis period (12 months, 13 months, etc.), select time grouping (weekly, monthly, etc.), and set sorting options (ascending, descending) according to their needs.

Average Balance

The Average Balance annotation provides the average account balance for the user during each period. It is typically grouped by a specific time frame (e.g., monthly) and can be sorted in ascending or descending order. This data gives businesses an overall picture of the user’s financial health by displaying how much money is typically held in the account over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "avg_balance": [
    {
      "data": {
        "average_balance": [
          158770.0,
          0.0,
          0.0,
          0.0,
          0.0,
          246350.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]  
      },
      "type": "avg_balance_monthly",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "ascending",
        "grouping": "monthly"
      }
    }
  ]
}

Days since Maximum Balance Count

The Days since Maximum Balance Count annotation tracks the number of days since the user last had their maximum account balance. This metric helps businesses assess how frequently users reach their peak balance, providing insights into financial behavior over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_days_since_max_bal_count": [
    {
      "data": {
        "days_counts": [
          17,
          28,
          7,
          15,
          30,
          0,
          4,
          27,
          28,
          3,
          29,
          21,
          0.0
        ]
      },
      "type": "grouped_days_since_max_bal_count",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Maximum Account Balance Amount

The Maximum Account Balance Amount annotation records the highest account balance for each configured time period. Grouped and sorted by business needs, this data helps identify when users held the most funds, aiding in financial stability assessments.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_max_balance_amount": [
    {
      "data": {
        "max_balance_amounts": [
          180689.84,
          177735.68,
          179572.33,
          155294.61,
          185009.95,
          186838.74,
          137778.31,
          156312.97,
          193663.24,
          190306.88,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_max_balance_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Minimum Account Balance Amount

The Minimum Account Balance Amount annotation captures the lowest account balance within the configured period. Grouping and sorting options help businesses track low-balance periods, which can indicate potential cash flow issues or spending habits.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_min_balance_amount": [
    {
      "data": {
        "min_balance_amounts": [
          140585.34,
          147399.90,
          144941.22,
          126731.03,
          129540.51,
          140773.38,
          100365.51,
          116098.60,
          146862.53,
          129188.54,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_min_balance_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Median EOD Balance Amount

The Median End of Day (EOD) Balance Amount annotation provides the median balance the user holds at the end of each day, offering a more balanced view of their financial health over the analysis period. This helps in assessing typical balance levels rather than extreme high or low values.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_median_eod_balance_amount": [
    {
      "data": {
        "max_balance_amounts": [
          168159.55,
          160620.22,
          162715.91,
          139777.48,
          145746.52,
          168945.74,
          116596.90,
          138085.35,
          170090.80,
          145724.40,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_median_eod_balance_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Days with EOD Balance Less Than 1000

The Days with EOD Balance Less Than 1000 annotation records the number of days where the end-of-day balance was less than a configurable threshold, such as 1000. Businesses can adjust the threshold to suit their analysis, helping to track how often users maintain a minimum balance. Businesses can configure the threshold as per their requirements.

This annotation could be configured with Bank Statement Analytics Journey

{
  "grouped_eod_balance_lt_1000_count": [
    {
      "data": {
        "days_count":[
          17,
          28,
          7,
          15,
          30,
          0,
          4,
          27,
          28,
          3,
          29,
          21,
          0.0
        ]
      },
      "type": "count_days_eod_bal",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "ascending",
        "grouping": "monthly"
      }
    }
  ]
}

End of the month Account Balance Annotations

These annotations can be configured within the Bank Statement Analytics Journey to summarize the user's account balance at the end of each month. Businesses can define the analysis period (12 months, 13 months, etc.), determine time grouping (weekly, monthly, etc.), and adjust sorting (ascending, descending) to fit their requirements.

Last 7 days Maximum Balance Amount

The Last 7 Days Maximum Balance Amount annotation tracks the highest account balance in the last seven days of each configured period. The number of days can be customized according to business needs.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_max_balance_last_7days_amount": [
    {
      "data": {
        "amounts": [
          152108.24,
          172011.58,
          179572.33,
          149301.90,
          147991.31,
          186838.74,
          137778.31,
          145248.32,
          155232.69,
          190306.88,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_max_balance_last_7days_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Last 7 Days Minimum Balance Amount

The Last 7 Days Minimum Balance Amount annotation records the lowest account balance during the last seven days of each period. Configuring the number of days and grouping the data (e.g., monthly) allows businesses to assess low points in the user's account balance at the end of the selected period.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_min_balance_last_7days_amount": [
    {
      "data": {
        "min_balance_amounts": [
          140585.34,
          155284.31,
          163784.43,
          126731.03,
          129540.51,
          162162.23,
          120793.09,
          116098.60,
          146862.53,
          174410.88,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_min_balance_last_7days_amount",
      "id":"c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Month End Balance Amount

The Month End Balance Amount annotation captures the account balance on the last day of each month. This summary helps businesses understand how much users typically have in their accounts at the close of each period, offering insights into financial stability.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_month_end_balance_amount": [
    {
      "data": {
        "month_end_balance_amounts": [
          143978.32,
          171215.93,
          177544.32,
          149301.90,
          129540.51,
          186838.74,
          131716.94,
          116098.60,
          153263.79,
          184209.82,
          132518.97,
          132518.97,
          0.0
        ]
      },
      "type": "grouped_month_end_balance_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Total Credits & Debits Annotations

These annotations can be configured within the Bank Statement Analytics Journey to aggregate the total credits and debits in the user's account. Businesses can specify the analysis period (12 months, 13 months, etc.), choose time grouping (weekly, monthly, etc.), and select sorting preferences (ascending, descending) to suit their needs.

Maximum Credit Amount

The Maximum Credit Amount annotation provides the highest credit transaction amount during the specified time period. Grouping and sorting this data helps businesses focus on significant credit events and analyze major inflows over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_max_credit_amount": [
    {
      "data": {
        "max_credit_amounts": [
          7701.47,
          9885.83,
          9926.69,
          9787.94,
          9433.27,
          9494.93,
          9655.74,
          9651.43,
          8712.66,
          15691.88,
          15691.88,
          15691.88,
          0.0
        ]
      },
      "type": "grouped_max_credit_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Total Credit Count

The Total Credit Count annotation tracks the number of credit transactions during the analysis period. By grouping and sorting the data (e.g., monthly), businesses can identify trends in the frequency of credits, which is useful for understanding income patterns.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_number_of_credits_count": [
    {
      "data": {
        "total_credit_counts": [
          7,
          14,
          15,
          17,
          8,
          19,
          18,
          12,
          15,
          13,
          1,
          1,
          0.0
        ]
      },
      "type": "grouped_number_of_credits_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Maximum Debit Amount

The Maximum Debit Amount annotation captures the highest debit transaction amount during the specified period. Grouping and sorting the data helps identify major spending events, offering insights into the user's financial outflows.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_max_debit_count": [
    {
      "data": {
        "max_debit_counts": [
          9979.95,
          9841.43,
          9582.78,
          9380.66,
          9962.74,
          8916.55,
          9833.23,
          9028.25,
          9920.68,
          8963.21,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_max_debit_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Total Debit Count

The Total Debit Count annotation records the number of debit transactions made in the configured period. Businesses can group and sort this data to analyze the frequency of debits, which aids in understanding spending behaviour.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_debit_count": [
    {
      "data": {
        "total_debit_counts": [
          14,
          17,
          16,
          13,
          23,
          11,
          13,
          16,
          16,
          7,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_number_of_debits_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "grouping": "Monthly",
        "sortby": "descending"
      }
    }
  ]
}

Total Amount Credited

The Total Amount Credited annotation sums up all the credit transactions for the chosen period. Grouping and sorting options provide businesses with insights into the total financial inflow, helping them understand the user's income over time.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_credits_amount": [
    {
      "data": {
        "total_credits_amounts": [
          35685.52,
          85260.44,
          100815.77,
          80127.2,
          53927.99,
          111167.22,
          100180.0,
          58696.56,
          69941.69,
          100518.18,
          15691.88,
          15691.88,
          0.0
        ]
      },
      "type": "grouped_total_credits_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Total Amount Debited

The Total Amount Debited annotation aggregates all debit transactions over the analysis period. Grouping and sorting this data enables businesses to analyze total spending and cash outflow, offering a comprehensive view of the user's expenditure.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_debits_amount": [
    {
      "data": {
        "total_debit_amounts": [
          62923.13,
          91588.83,
          72573.35,
          60365.81,
          111226.22,
          56045.42,
          84561.66,
          95861.75,
          100887.72,
          33135.45,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_total_debits_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Salary Annotations

These annotations can be configured within the Bank Statement Analytics Journey to identify and analyze salary transactions in the user's account. Businesses can define the analysis period (12 months, 13 months, etc.), select time grouping (weekly, monthly, etc.), and set sorting (ascending, descending) according to their requirements.

Salary Credited Amount

The Salary Credited Amount annotation tracks the amount of salary deposited in the user’s account over the selected time frame. Grouping and sorting the data helps businesses analyze salary trends and understand the consistency of income.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_salary_credits_amount": [
    {
      "data": {
        "salary_credit_amounts": [
          5087.97,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_salary_credits_amount",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Salary Transactions

The Salary Transactions annotation provides detailed information about individual salary credits, including transaction dates, amounts, and descriptions. This data helps businesses track salary deposits and analyze pay periods for consistency.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "salary": [
    {
      "data": {
        "salary_transactions": [
          {
            "date": "2024-04-01",
            "amount": 50000,
            "pay_period": null,
            "UTR": null,
            "transaction_description": "BY TRANSFER- NEFT*RBIS0GOKAEP*RBI3392335282137*Chanapatna Sub T// description of the transaction"
          },
          {
            "date": "2024-04-01",
            "amount": 50000,
            "pay_period": null,
            "UTR": null,
            "transaction_description": null
          }
        ]
      },
      "type":"salary",
      "id": "type#<uuid>",
      "config": {
        "sortby": "descending"
      }
    }
  ]
}

Third-Party Credits Annotations

These annotations can be configured within the Bank Statement Analytics Journey to capture information about third-party credit transactions in the user's account. Businesses can customize the analysis period (12 months, 13 months, etc.), choose time grouping (weekly, monthly, etc.), and adjust sorting preferences (ascending, descending) based on their needs.

Third Party Credit Amounts

The Third-Party Credit Amounts annotation records the total amount of third-party credits during the configured period. Grouping and sorting the data allows businesses to focus on inflows from external parties, helping identify patterns in third-party transactions.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_third_party_credit_amounts": [
    {
      "data": {
        "third_party_credit_amounts": [
          7677.22,
          0.0,
          0.0,
          4194.23,
          4455.67,
          17919.91,
          0.0,
          3049.18,
          3726.01,
          22635.75,
          15691.88,
          15691.88,
          0.0
        ]
      },
      "type": "grouped_third_party_credit_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Penalty Payments Annotations

These annotations can be configured within the Bank Statement Analytics Journey to track penalty payment transactions made by the user. Businesses can set the analysis period (12 months, 13 months, etc.), opt for time grouping (weekly, monthly, etc.), and select sorting (ascending, descending) to align with their requirements.

Penalty Payments Count

The Penalty Payments Count annotation records the number of penalty payment transactions in the user's account during the configured period. Grouping and sorting the data helps businesses track the frequency of penalties and assess financial behaviour.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_penalty_payment_count": [
    {
      "data": {
        "penalty_payment_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_penalty_payment_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Penalty Payment Amount

The Penalty Payment Amount annotation captures the total amount spent on penalty payments over the specified time frame. Sorting and grouping options help businesses analyze the financial impact of penalties on the user.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_penalty_amount_count": [
    {
      "data": {
        "penalty_counts": [
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_penalty_amount_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Largest Single Transaction Annotations

These annotations can be configured within the Bank Statement Analytics Journey to identify and analyse the user's largest single transaction. Businesses can specify the analysis period (12 months, 13 months, etc.), determine time grouping (weekly, monthly, etc.), and adjust sorting preferences (ascending, descending) to meet their needs.

Maximum Amount Credited

The Maximum Amount Credited annotation tracks the largest credit transaction during the configured period. Grouping and sorting the data helps businesses identify significant financial inflows and analyze major credit events.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_single_acc_max_credit_amount": [
    {
      "data": {
        "single_acc_max_credit_amounts": [
          7677.22,
          32910.55,
          30437.34,
          16934.45,
          22033.09,
          23387.13,
          35787.83,
          12213.28,
          16114.27,
          22635.75,
          15691.88,
          15691.88,
          0.0
        ]
      },
      "type": "grouped_single_acc_max_credit_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "sortby": "descending",
        "grouping": "monthly"
      }
    }
  ]
}

Maximum Amount Debited

The Maximum Amount Debited annotation captures the largest debit transaction recorded in the user's account during the specified time period. The data is grouped by the selected time frame (e.g., monthly) and sorted in descending order, providing insights into significant outflows from the user's account.

This annotation could be configured with Bank Statement Analytics Journey.

{
  "grouped_single_acc_max_debit_amount": [
    {
      "data": {
        "single_acc_max_debit_amounts": [
          17997.71,
          17075.99,
          19517.52,
          17745.55,
          22988.6,
          10855.74,
          18871.83,
          16384.47,
          28442.19,
          8963.21,
          0.0,
          0.0,
          0.0
        ]
      },
      "type": "grouped_single_acc_max_debit_count",
      "id": "c1148cf2-77f4-4243-a10d-c49119d93fbb",
      "config": {
        "period": 12,
        "grouping": "Monthly",
        "sortby": "descending"
      }
    }
  ]
}

📘Currently, none of the annotations are pre-configured in our journeys. To configure any annotation with your journey reach out to your account manager.

Watermarking

Loan Transactions: EMI Debits and Loan Credits Annotations

EMI Debit Amount

EMI Debit Count

Loan Credit Amount

Loan Credit Count

Investment Transactions Annotations

Investment Credit Amount

Investment Debit Amount

Credit Card Payments Annotations

Credit Card Payment Amount

Credit Card Payment Count

Cash Withdrawals Annotations

Cash Withdrawl Amount

Cash Withdrawl Count

UPI Transactions Annotations

UPI Credit Count

UPI Credit Amount

UPI Debit Count

UPI Debit Amount

Account Balance Summary (Low balance, high balance days, median balance) Annotations

Average Balance

Days since Maximum Balance Count

Maximum Account Balance Amount

Minimum Account Balance Amount

Median EOD Balance Amount

Days with EOD Balance Less Than 1000

End of the month Account Balance Annotations

Last 7 days Maximum Balance Amount

Last 7 Days Minimum Balance Amount

Month End Balance Amount

Total Credits & Debits Annotations

Maximum Credit Amount

Total Credit Count

Maximum Debit Amount

Total Debit Count

Total Amount Credited

Total Amount Debited

Salary Annotations

Salary Credited Amount

Salary Transactions

Third-Party Credits Annotations

Third Party Credit Amounts

Penalty Payments Annotations

Penalty Payments Count

Penalty Payment Amount

Largest Single Transaction Annotations

Maximum Amount Credited

Maximum Amount Debited

📘
Currently, none of the annotations are pre-configured in our journeys. To configure any annotation with your journey reach out to your account manager.