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Your Accounts Receivable Data Template

HighRadius

Accounts Receivable Attributes (20) Accounts Receivable Activities (13) Extraction Guides (2)

Your Accounts Receivable Data Template

This template outlines the essential components for analyzing your invoicing workflows within HighRadius. It provides a structured overview of the necessary data points, process milestones, and technical steps required to build a comprehensive event log. By following this guide, you can successfully map your collections cycle and identify opportunities to improve your cash flow.

Specific data attributes for your process
Standardized activity milestones
HighRadius extraction instructions

New to event logs? Learn how to create a process mining event log.

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Accounts Receivable Attributes

This table lists the recommended data fields required to construct a detailed event log for analyzing your invoice management and collections performance.

3 Required 7 Recommended 10 Optional

	Name	Description
	Activity ActivityName	The name of the event or action performed on the invoice.
Description This attribute records the specific step or action that occurred in the credit-to-cash lifecycle. It captures events such as invoice creation, automated correspondence, collector calls, dispute logging, and payment application. Analysts use this field to reconstruct the process flow and visualize the sequence of steps. Variations in the sequence of these activities help identify process deviations, rework loops, and non-compliant behaviors. Why it matters It defines the steps of the process and is essential for process discovery and variant analysis. Where to get HighRadius Activity Log, Notes History, or Transaction History tables Examples Invoice CreatedPayment Reminder SentDispute Case OpenedFull Payment Received
	Event Timestamp EventDateTime	The specific date and time when the activity occurred.
Description This attribute marks the exact moment an event took place within the HighRadius system. It provides the temporal dimension necessary for sequencing activities and calculating durations between process steps. In analysis, the timestamp is used to compute cycle times, such as Days Sales Outstanding (DSO) or dispute resolution time. It also enables the analysis of throughput and resource utilization over specific time periods. Why it matters Precise timing is required to calculate all duration-based KPIs and to order events correctly. Where to get HighRadius Transaction Logs timestamp column Examples 2023-10-01T08:30:00Z2023-10-15T14:22:10Z2023-11-05T09:15:00Z
	Invoice Number InvoiceNumber	The unique identifier for the invoice document which serves as the case ID.
Description The Invoice Number is the central identifier for tracking the financial obligation from creation through to final settlement. It links all related activities, including disputes, promises to pay, and payments, into a single case history. In analysis, this attribute is used to group event logs into distinct process instances. It allows for the calculation of cycle times per invoice and is the primary key for joining process data with other master data tables in the HighRadius environment or the source ERP. Why it matters It identifies the unique case and ensures all events are correctly associated with the specific financial transaction. Where to get HighRadius Invoice Data / Header Table or Source ERP (e.g., SAP VBAK, Oracle Headers) Examples INV-2023-001900123456US-102938550002931
	Collector Name CollectorName	The name of the agent or user responsible for the collection activity.
Description This attribute identifies the specific HighRadius user or agent who performed manual activities such as logging a call, sending a specialized email, or reviewing a dispute. It is used in the Collector Productivity Benchmarks dashboard to assess individual performance and workload distribution. This helps managers identify training needs or rebalance portfolios among the collections team. Why it matters Enables performance analysis at the resource level. Where to get Activity Log / User Table Examples John DoeJane SmithSystem AdminCollectionAgent_01
	Customer Name CustomerName	The name of the customer account associated with the invoice.
Description This attribute identifies the entity responsible for paying the invoice. In HighRadius, this is linked to the master data record for the debtor. Analyzing process performance by customer name highlights specific accounts that may require tailored collection strategies or have consistent payment delays. It supports the Customer Risk and Aging Matrix dashboard. Why it matters Essential for segmenting analysis by account to find problem customers. Where to get Customer Master Data or Invoice Header Examples Acme CorpGlobal IndustriesTechStart IncRetail Giant Ltd
	Days Sales Outstanding DaysSalesOutstanding	The number of days from invoice creation to invoice clearing.
Description This calculated attribute represents the total lifecycle duration of the invoice. It is the core metric for the DSO Cycle Time Distribution dashboard. Monitoring this at a granular level helps pin down which stages of the process (e.g., dispute resolution vs. bank matching) contribute most to the overall cash conversion cycle. Why it matters The primary efficiency metric for Accounts Receivable. Where to get Calculated from Invoice Created and Invoice Cleared timestamps Examples 45 days30 days62 days
	Due Date DueDate	The date by which the customer is contractually obligated to pay.
Description The Due Date is determined by the payment terms applied to the invoice creation date. It serves as the target deadline for the collections process. Comparison of the Full Payment Received date against this attribute allows for the calculation of the Payment Term Compliance Rate. It is critical for determining if a payment is on time, late, or early. Why it matters The reference point for determining lateness and calculating Days Sales Outstanding (DSO). Where to get Invoice Header Table (Due Date field) Examples 2023-11-302023-12-15
	Invoice Amount InvoiceAmount	The total monetary value of the invoice.
Description This attribute represents the original total amount billed to the customer. It is the baseline for calculating outstanding balances and evaluating the financial impact of disputes or delays. Process mining analysis uses this field to weight cases by value. For example, it helps differentiate between high-value priority collections and low-value administrative noise in the Low Value Dispute Volume KPI. Why it matters Allows analysis to be weighted by financial impact rather than just case count. Where to get Invoice Header Table (Amount field) Examples 1500.00250.5010000.00
	Is Automated IsAutomated	Flag indicating if the activity was performed by the system without human intervention.
Description This boolean attribute distinguishes between steps executed by the HighRadius automation engine (like auto-correspondence or cash matching) and manual steps taken by users. It is vital for the Cash Application Automation Tracker and Touchless Invoice Rate KPI. It allows analysts to measure the ROI of automation and identify process steps that still require heavy manual touch. Why it matters Measures the efficiency of the HighRadius implementation. Where to get Activity Log (System User vs. Human User check) Examples truefalse
	Payment Term Variance PaymentTermVariance	The number of days between the due date and the payment date.
Description This calculated attribute measures the deviation from the agreed payment terms. A positive number indicates late payment, while a negative number indicates early payment. It is the direct metric for the Payment Term Compliance Audit. By aggregating this variance, businesses can identify systematic late payers and adjust credit terms or collection strategies accordingly. Why it matters Direct measure of customer adherence to contract terms. Where to get Calculated from Due Date and Payment Date Examples 5 days-2 days0 days
	Business Unit BusinessUnit	The internal division or subsidiary that issued the invoice.
Description This attribute segments data by organizational structure, such as 'North America Sales', 'EMEA Services', or specific product divisions. It enables the Payment Term Compliance Audit to compare performance across different parts of the organization. This helps isolate whether collection issues are systemic or localized to specific business practices. Why it matters Allows for comparative analysis across different organizational verticals. Where to get Invoice Header / ERP Mapping Examples Consumer ElectronicsIndustrial PartsSoftware ServicesNA-West
	Credit Rating CreditRating	The creditworthiness score or rating assigned to the customer.
Description This attribute reflects the risk level of the customer, often sourced from credit bureaus or internal scoring within the HighRadius Credit Cloud. It is a dimension in the Customer Risk and Aging Matrix. Analyzing aging against credit rating helps identify high-exposure risks where customers with poor ratings have large outstanding balances. Why it matters Essential for risk management and prioritizing collections. Where to get Credit Management Module / Customer Master Examples AAAB+High RiskLow Risk
	Currency Code CurrencyCode	The ISO currency code for the invoice amount.
Description This attribute specifies the currency in which the invoice was issued (e.g., USD, EUR, GBP). When analyzing a global process, this is necessary for correctly interpreting the Invoice Amount and Open Amount fields. It ensures that aggregations are handled correctly (usually by converting to a reporting currency). Why it matters Required for accurate financial aggregation in multi-currency environments. Where to get Invoice Header Examples USDEURGBPJPY
	Customer Segment CustomerSegment	Categorization of the customer based on size, industry, or strategic value.
Description This attribute groups customers into tiers such as 'Strategic', 'Mid-Market', 'SMB', or 'High Risk'. It is used in the Dispute Resolution Performance dashboard to see if different segments experience different service levels. It ensures that high-value customers are receiving appropriate attention during the collections process. Why it matters Segments analysis to align with business strategy and service level agreements. Where to get Customer Master Data Examples Strategic Key AccountWholesaleRetailGovernment
	Dispute Reason Code DisputeReasonCode	The category code assigned to a dispute case.
Description This attribute classifies the nature of a customer's refusal to pay, such as 'Pricing Error', 'Damaged Goods', or 'Missing Documentation'. In HighRadius Deductions Cloud, these are standard codes. Analysing these codes helps identify the root causes of non-payment. Aggregating this data allows the business to fix upstream issues in sales or logistics that are causing downstream collection delays. Why it matters Crucial for Root Cause Analysis of delayed payments. Where to get Dispute/Deduction Management Module Examples P01 (Pricing)Q02 (Quality)S03 (Shortage)Admin Error
	Last Data Update LastDataUpdate	The timestamp of when the data was last refreshed in the mining model.
Description This attribute records when the record was extracted or last updated in the process mining dataset. It ensures that analysts are aware of the data currency and potential latency in reporting. It is particularly important for ongoing monitoring dashboards where users need to know if they are looking at real-time data or a snapshot from the previous day. Why it matters It ensures transparency regarding the freshness of the data used for KPIs. Where to get ETL Timestamp Examples 2023-12-01T00:00:00Z2023-12-02T06:00:00Z
	Open Amount OpenAmount	The remaining unpaid balance on the invoice.
Description This attribute tracks the amount still owed by the customer. It updates as partial payments are posted. It is essential for the Partial Payment Complexity Analysis. It allows analysts to filter for fully open vs. partially paid invoices and prioritize collection efforts on high-value open items. Why it matters Critical for determining the current exposure and success of partial collections. Where to get Invoice Header / Open Items Table Examples 0.00500.0012000.00
	Promise To Pay Date PromiseToPayDate	The date the customer promised to make a payment.
Description This attribute records the commitment date given by a customer during a collection interaction. It is a key feature in the HighRadius Collections Cloud. Used in the Promise to Pay Reliability Index, this date is compared against the actual payment date to determine if the customer kept their promise. It helps evaluate the quality of the commitment and the effectiveness of the collector's negotiation. Why it matters Key for forecasting cash flow and measuring customer reliability. Where to get Collections Module / P2P Transaction Table Examples 2023-12-102023-12-20
	Region Region	Geographic region associated with the invoice or customer.
Description This attribute defines the geographical area, such as 'North America', 'EMEA', or 'APAC', relevant to the transaction. It helps in regional benchmarking and understanding how cultural or regulatory differences affect payment behaviors and collection speeds. It is useful for high-level executive reporting. Why it matters Supports geographic performance analysis. Where to get Customer Master Data or Invoice Header Examples NAEMEALATAMAPAC
	Source System SourceSystem	The name of the system where the data originated.
Description This attribute indicates whether the data point originated directly within the HighRadius platform modules (like Collections Cloud or Cash Application Cloud) or if it was ingested from an external ERP system (like SAP or Oracle). It is useful for data lineage and validation. When analyzing process friction, knowing the source system helps identify if delays are caused by integration lags or native system processing times. Why it matters It provides context on data origin, especially in landscapes with multiple ERPs feeding into HighRadius. Where to get System Configuration or Hardcoded based on extraction logic Examples HighRadiusSAP ECCOracle NetSuiteMicrosoft Dynamics

Required Recommended Optional

Accounts Receivable Activities

These entries represent the critical process steps and transaction milestones that you should capture to visualize your end to end invoice journey.

8 Recommended 5 Optional

	Activity	Description
	Bank Statement Matched	The Cash Application engine (or user) successfully links a line on the bank statement to this specific invoice.
Why it matters Core metric for 'Automated Cash Application Rate'. Distinguishes between receipt of funds and application of funds. Where to get Cash Application module; match record creation. Capture Logged when matching rule executes Event type explicit
	Dispute Case Opened	The creation of a deduction or dispute case linked to the invoice, indicating a customer refusal to pay part or all of the balance.
Why it matters Triggers the 'Dispute Resolution Performance' analysis and pauses standard dunning for the disputed amount. Where to get Deductions/Disputes module; creation timestamp of the case ID linked to the invoice. Capture Logged when dispute case is generated Event type explicit
	Dispute Resolved	The conclusion of the dispute investigation, resulting in a decision (e.g., valid deduction or invalid claim).
Why it matters Stop-clock event for 'Dispute Resolution Cycle Time'. Delays here directly impact aging. Where to get Deductions module; status change to 'Closed', 'Resolved', or 'Approved'. Capture Compare status field before/after Event type inferred
	Full Payment Received	The receipt of funds that fully extinguishes the debt. This is the effective date of the payment for aging purposes.
Why it matters Used to calculate 'Promise to Pay Fulfillment Rate' and actual vs. expected cash flow. Where to get Payment transaction date associated with the final clearing document. Capture Logged transaction date of clearing payment Event type explicit
	Invoice Cleared	The final status change where the invoice balance becomes zero and is closed in the system.
Why it matters The end timestamp for 'Average Days Sales Outstanding'. Represents the completion of the process. Where to get Invoice Header table; Status = 'Closed' or 'Cleared'. Capture Compare status field before/after Event type inferred
	Invoice Created	The initial creation or ingestion of the invoice into the HighRadius platform from the ERP system. This establishes the start of the collection lifecycle.
Why it matters Establishes the baseline timestamp for aging calculations and Days Sales Outstanding (DSO) metrics. Where to get Open Invoices table or Data Integration logs where the invoice number first appears. Capture Logged when record inserted into invoice header table Event type explicit
	Payment Reminder Sent	An automated correspondence (email/letter) sent to the customer via the Collections module. This tracks the dunning strategy execution.
Why it matters Critical for the 'Collection Reminder Effectiveness' dashboard to measure if correspondence actually triggers payment. Where to get Correspondence History tab or Communication logs linked to the Invoice ID. Capture Logged when dunning strategy executes an action Event type explicit
	Promise to Pay Created	A formal commitment recorded in the system where a customer promises to pay a specific amount by a specific date.
Why it matters Essential for the 'Promise to Pay Reliability Index' to predict cash flow and measure customer reliability. Where to get P2P (Promise to Pay) module/tab linked to the invoice. Capture Logged when P2P record is created Event type explicit
	Collection Call Logged	A manual note or interaction recorded by a collection agent regarding this invoice. Indicates human intervention in the process.
Why it matters Supports 'Collector Productivity Benchmarks' and differentiates between automated and manual collection efforts. Where to get Notes/History tab within the Collections module. Capture Logged when user saves a call note Event type explicit
	Credit Memo Issued	A credit note is generated to offset the invoice balance, often resulting from a valid dispute resolution or return.
Why it matters Tracks 'Credit Memo Processing Efficiency' and the time lag between dispute resolution and financial posting. Where to get ERP sync logs or Credit Memo table linked to original Invoice ID. Capture Logged when CM document is linked to invoice Event type explicit
	Dispute Under Review	The dispute case moves from 'New' to an active investigation status. Represents the start of the actual work by the analyst.
Why it matters Used in 'Dispute Workflow Bottleneck Finder' to measure the lag between creation and active working time. Where to get Deductions module audit log; status change to 'In Progress' or 'Researching'. Capture Compare status field before/after Event type inferred
	Due Date Passed	A calculated event indicating the invoice remains open past its agreed payment terms date.
Why it matters Critical for 'Payment Term Compliance Audit'. Marks the transition from current to past due. Where to get Calculated by comparing the Invoice Due Date to the Current Date (if open) or Payment Date (if closed). Capture Derive from comparing field Due Date to Activity Date Event type calculated
	Partial Payment Posted	A payment is applied that covers only a portion of the total invoice amount, leaving a residual balance.
Why it matters Feeds 'Partial Payment Complexity Analysis' and indicates potential cash application friction. Where to get Cash Application module; payment transaction linked to invoice where Payment Amount < Open Amount. Capture Logged when payment is applied but status remains open Event type explicit

Recommended Optional

Extraction Guides

How to get your data from HighRadius

Steps

Login to the HighRadius Integrated Receivables platform and navigate to the Analytics or Reports module.
Locate the Transaction History or Open Items report template. You will likely need to configure three separate exports to capture the full lifecycle: Invoice Header Data, Collection Activities, and Dispute/Deduction History.
Configure the Invoice Header Export: Select columns for Invoice Number, Customer Name, Invoice Amount, Invoice Date, Due Date, Clear Date, and Final Status. Apply filters for the relevant Company Codes and a creation date range covering your process mining window.
Configure the Collection Activities Export: Select columns for Invoice Number, Activity Type (Call, Email, Note), Activity Date, Collector Name, and Promise to Pay details. Ensure you include both automated system actions and manual user logs.
Configure the Dispute History Export: Select columns for Invoice Number, Dispute Case ID, Dispute Amount, Status Change Date, Reason Code, and Resolution Date. This captures the lifecycle of deductions.
Configure the Payment/Cash App Export: Select columns for Invoice Number, Payment Reference, Payment Date, Payment Amount, and Payment Type (Partial, Full, Credit Memo).
Run these reports and export the results to CSV format.
Import these CSV files into a staging database or data transformation tool (like Python/Pandas or a SQL database) to perform the unification steps.
Execute the transformation script provided in the Query section to standardize column names, calculate derived events (like Due Date Passed), and unite the disparate sources into a single event log.
Verify that date formats are consistent (ISO 8601 recommended) and that the Invoice Number is formatted identically across all files (e.g., removing leading zeros if inconsistent).
Export the final result set as a single CSV file.
Upload the final CSV to ProcessMind, mapping InvoiceNumber to Case ID, EventDateTime to Timestamp, and ActivityName to Activity.

Configuration

Date Range: Select a rolling window (e.g., past 12 months) based on Invoice Creation Date to ensure complete lifecycle capture.
Data Sources: Requires access to Collections, Cash Application, and Deductions modules within HighRadius.
Granularity: Ensure reports are generated at the Invoice level, not the Account or Summary level.
User Permissions: The extracting user requires Reporting or Analytics Admin privileges to access historical activity logs.
System Actions: Explicitly enable filters to include System or Automated User actions in the Activity logs to capture automated correspondence.
Mapping Required: HighRadius activity types may need mapping to standard process mining activity names (e.g., mapping 'Dunning Letter' to 'Payment Reminder Sent').

a Sample Query config

/* 
Title: HighRadius Event Log Transformation Script
Description: This script assumes the raw CSV exports from HighRadius have been loaded into four staging tables:
1. STG_INVOICES (Header data)
2. STG_ACTIVITIES (Collections notes, calls, correspondence)
3. STG_DISPUTES (Deduction and dispute lifecycle)
4. STG_PAYMENTS (Cash application details)
*/

/* 1. Invoice Created */
SELECT 
    InvoiceNumber AS InvoiceNumber,
    'Invoice Created' AS ActivityName,
    InvoiceDate AS EventDateTime,
    CustomerName AS CustomerName,
    InvoiceAmount AS InvoiceAmount,
    DueDate AS DueDate,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    NULL AS PaymentTermVariance,
    0 AS DaysSalesOutstanding
FROM STG_INVOICES

UNION ALL

/* 2. Payment Reminder Sent */
SELECT 
    InvoiceNumber,
    'Payment Reminder Sent',
    ActivityDate,
    CustomerName,
    NULL,
    NULL,
    UserName AS CollectorName,
    CASE WHEN UserName = 'System' THEN 'True' ELSE 'False' END,
    NULL,
    NULL
FROM STG_ACTIVITIES
WHERE ActivityType IN ('Dunning', 'Correspondence', 'Email Sent')

UNION ALL

/* 3. Collection Call Logged */
SELECT 
    InvoiceNumber,
    'Collection Call Logged',
    ActivityDate,
    CustomerName,
    NULL,
    NULL,
    UserName AS CollectorName,
    'False' AS IsAutomated,
    NULL,
    NULL
FROM STG_ACTIVITIES
WHERE ActivityType IN ('Call', 'Outbound Call')

UNION ALL

/* 4. Promise to Pay Created */
SELECT 
    InvoiceNumber,
    'Promise to Pay Created',
    PromiseDate,
    CustomerName,
    PromiseAmount,
    NULL,
    UserName AS CollectorName,
    'False' AS IsAutomated,
    NULL,
    NULL
FROM STG_ACTIVITIES
WHERE ActivityType = 'Promise to Pay' AND PromiseDate IS NOT NULL

UNION ALL

/* 5. Dispute Case Opened */
SELECT 
    InvoiceNumber,
    'Dispute Case Opened',
    CreateDate,
    CustomerName,
    DisputeAmount,
    NULL,
    AnalystName AS CollectorName,
    'False' AS IsAutomated,
    NULL,
    NULL
FROM STG_DISPUTES

UNION ALL

/* 6. Dispute Under Review */
SELECT 
    InvoiceNumber,
    'Dispute Under Review',
    StatusDate,
    CustomerName,
    NULL,
    NULL,
    AnalystName AS CollectorName,
    'False' AS IsAutomated,
    NULL,
    NULL
FROM STG_DISPUTES
WHERE Status = 'In Review'

UNION ALL

/* 7. Dispute Resolved */
SELECT 
    InvoiceNumber,
    'Dispute Resolved',
    ResolutionDate,
    CustomerName,
    NULL,
    NULL,
    AnalystName AS CollectorName,
    'False' AS IsAutomated,
    NULL,
    NULL
FROM STG_DISPUTES
WHERE Status IN ('Closed', 'Resolved', 'Denied', 'Approved')

UNION ALL

/* 8. Credit Memo Issued */
SELECT 
    InvoiceNumber,
    'Credit Memo Issued',
    PaymentDate,
    CustomerName,
    PaymentAmount,
    NULL,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    NULL,
    NULL
FROM STG_PAYMENTS
WHERE PaymentType = 'Credit Memo'

UNION ALL

/* 9. Partial Payment Posted */
SELECT 
    P.InvoiceNumber,
    'Partial Payment Posted',
    P.PaymentDate,
    I.CustomerName,
    P.PaymentAmount,
    I.DueDate,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    DATEDIFF(day, I.DueDate, P.PaymentDate) AS PaymentTermVariance,
    DATEDIFF(day, I.InvoiceDate, P.PaymentDate) AS DaysSalesOutstanding
FROM STG_PAYMENTS P
JOIN STG_INVOICES I ON P.InvoiceNumber = I.InvoiceNumber
WHERE P.PaymentType = 'Payment' AND P.PaymentAmount < I.InvoiceAmount

UNION ALL

/* 10. Bank Statement Matched */
SELECT 
    InvoiceNumber,
    'Bank Statement Matched',
    MatchDate,
    CustomerName,
    NULL,
    NULL,
    'CashApp System' AS CollectorName,
    'True' AS IsAutomated,
    NULL,
    NULL
FROM STG_PAYMENTS
WHERE MatchDate IS NOT NULL

UNION ALL

/* 11. Full Payment Received */
SELECT 
    P.InvoiceNumber,
    'Full Payment Received',
    P.PaymentDate,
    I.CustomerName,
    P.PaymentAmount,
    I.DueDate,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    DATEDIFF(day, I.DueDate, P.PaymentDate) AS PaymentTermVariance,
    DATEDIFF(day, I.InvoiceDate, P.PaymentDate) AS DaysSalesOutstanding
FROM STG_PAYMENTS P
JOIN STG_INVOICES I ON P.InvoiceNumber = I.InvoiceNumber
WHERE P.PaymentType = 'Payment' AND P.PaymentAmount >= I.InvoiceAmount

UNION ALL

/* 12. Due Date Passed */
SELECT 
    InvoiceNumber,
    'Due Date Passed',
    DueDate,
    CustomerName,
    InvoiceAmount,
    DueDate,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    NULL,
    DATEDIFF(day, InvoiceDate, DueDate) AS DaysSalesOutstanding
FROM STG_INVOICES
WHERE DueDate < GETDATE() AND (ClearDate IS NULL OR ClearDate > DueDate)

UNION ALL

/* 13. Invoice Cleared */
SELECT 
    InvoiceNumber,
    'Invoice Cleared',
    ClearDate,
    CustomerName,
    InvoiceAmount,
    DueDate,
    'System' AS CollectorName,
    'True' AS IsAutomated,
    DATEDIFF(day, DueDate, ClearDate) AS PaymentTermVariance,
    DATEDIFF(day, InvoiceDate, ClearDate) AS DaysSalesOutstanding
FROM STG_INVOICES
WHERE ClearDate IS NOT NULL

Steps

Prerequisites and Environment Setup Ensure Python 3.8 or higher is installed. You will need the requests and pandas libraries. Install them via pip if not present. Obtain your HighRadius API Client ID, Client Secret, and Base URL from your system administrator. These are typically found in the Administration or Developer Portal section of HighRadius.
Configure API Credentials Open the provided Python script. Locate the configuration section at the top. Replace the placeholders for CLIENT_ID, CLIENT_SECRET, and BASE_URL. Ensure the user associated with these credentials has permissions to access the Collections, Cash Application, and Deductions modules.
Set Data Extraction Parameters Define the START_DATE and END_DATE variables in the script. It is recommended to extract data in monthly or quarterly chunks to avoid timeouts. The script expects standard ISO 8601 date formats (YYYY-MM-DD).
Script Execution: Authentication The script first executes an OAuth2 flow to obtain a bearer token. This token is valid for a limited time (usually 1 hour). The script handles the initial token retrieval automatically.
Script Execution: Data Fetching The script sequentially queries specific endpoints. It first retrieves the header-level invoice data. It then iterates through related endpoints for Activities (Notes), Promises to Pay, Disputes, and Payment History using the Invoice Numbers as reference keys where necessary.
Data Transformation and Activity Mapping The script processes raw JSON responses into a flattened event log structure. It maps specific HighRadius codes to the required Activity Names. For example, it checks the invoice_balance against total_amount to distinguish between 'Partial Payment Posted' and 'Full Payment Received'. It also calculates the 'Due Date Passed' event by comparing the due date against the clearing date or current date.
Handling Pagination HighRadius APIs typically paginate results. The provided script includes a loop mechanism to fetch all pages of data until no further records are returned. Ensure your network connection is stable during this process.
Data Consolidation All extracted lists (Invoices, Activities, Disputes, Payments) are merged into a single Pandas DataFrame. The script sorts this DataFrame by InvoiceNumber and EventDateTime to ensure a chronological event flow.
Validation and Quality Check Before finalizing, the script prints a summary of the extracted unique activities. Verify that the counts look reasonable compared to your operational volumes. Check that the EventDateTime column is properly formatted as YYYY-MM-DD HH:MM:SS.
Export to CSV The final DataFrame is exported to a file named HighRadius_EventLog.csv. This file is formatted with the specific columns required for ProcessMind.
Final Review Open the CSV file. Check for any NULL values in InvoiceNumber or ActivityName. Ensure that dates are not in the future unless they refer to expected due dates (though EventDateTime should always be past or present).
Upload to ProcessMind Import the generated CSV file into ProcessMind. Map InvoiceNumber to Case ID, ActivityName to Activity, and EventDateTime to Timestamp.

Configuration

API Base URL: Identify whether you are connecting to a Production or Sandbox environment. The URL structure usually differs (e.g., https://[client].highradius.com/api vs https://[client]-sandbox.highradius.com/api).
Client Scope: Ensure the API Client has read access to radiusOne, collections, deductions, and cashApp scopes.
Date Range: Keep extraction windows to 3 months or less per run if transaction volume is high (over 100k invoices per month).
Pagination Limit: The script defaults to 1000 records per page. Adjust the limit parameter in the API calls if the server returns timeout errors.
Throttle/Rate Limiting: HighRadius may enforce rate limits. If you encounter HTTP 429 errors, introduce a time.sleep(1) command inside the pagination loops.

a Sample Query python

import requests
import pandas as pd
import json
from datetime import datetime, timedelta

class=class="hl-string">"hl-comment"># ==========================================
class=class="hl-string">"hl-comment"># CONFIGURATION
class=class="hl-string">"hl-comment"># ==========================================
BASE_URL = class="hl-string">"https://[Your Instance].highradius.com/api/v1"
TOKEN_URL = class="hl-string">"https://[Your Instance].highradius.com/oauth/token"
CLIENT_ID = class="hl-string">"[Your Client ID]"
CLIENT_SECRET = class="hl-string">"[Your Client Secret]"
SCOPE = class="hl-string">"read_write"

class=class="hl-string">"hl-comment"># Extraction Window
START_DATE = class="hl-string">"2023-01-01"
END_DATE = class="hl-string">"2023-01-31"

class=class="hl-string">"hl-comment"># Global container for event log rows
event_log = []

def get_access_token():
    payload = {
        class="hl-string">'grant_type': class="hl-string">'client_credentials',
        class="hl-string">'client_id': CLIENT_ID,
        class="hl-string">'client_secret': CLIENT_SECRET,
        class="hl-string">'scope': SCOPE
    }
    try:
        response = requests.post(TOKEN_URL, data=payload)
        response.raise_for_status()
        return response.json().get(class="hl-string">'access_token')
    except Exception as e:
        print(fclass="hl-string">"Authentication failed: {e}")
        return None

def fetch_paged_data(endpoint, token, params={}):
    headers = {class="hl-string">"Authorization": fclass="hl-string">"Bearer {token}", class="hl-string">"Content-Type": class="hl-string">"application/json"}
    all_records = []
    page = 1
    while True:
        params[class="hl-string">'page'] = page
        params[class="hl-string">'limit'] = 1000
        try:
            resp = requests.get(fclass="hl-string">"{BASE_URL}/{endpoint}", headers=headers, params=params)
            if resp.status_code != 200:
                break
            data = resp.json()
            records = data.get(class="hl-string">'data', [])
            if not records:
                break
            all_records.extend(records)
            page += 1
        except Exception:
            break
    return all_records

def process_extraction():
    token = get_access_token()
    if not token:
        return

    class=class="hl-string">"hl-comment"># 1. Fetch Invoices (Header Data)
    print(class="hl-string">"Fetching Invoices...")
    invoices = fetch_paged_data(class="hl-string">"invoices", token, {class="hl-string">"filter_date_from": START_DATE, class="hl-string">"filter_date_to": END_DATE})
    
    class=class="hl-string">"hl-comment"># Process Invoice Headers and Derived Events
    invoice_ids = []
    for inv in invoices:
        inv_num = str(inv.get(class="hl-string">'invoice_number', class="hl-string">''))
        cust_name = inv.get(class="hl-string">'customer_name', class="hl-string">'')
        amount = float(inv.get(class="hl-string">'amount', 0.0))
        create_date = inv.get(class="hl-string">'create_date')  class=class="hl-string">"hl-comment"># YYYY-MM-DD
        due_date = inv.get(class="hl-string">'due_date')
        clear_date = inv.get(class="hl-string">'clear_date')
        status = inv.get(class="hl-string">'status', class="hl-string">'Open')
        
        invoice_ids.append(inv_num)
        
        class=class="hl-string">"hl-comment"># Event: Invoice Created
        event_log.append({
            class="hl-string">"InvoiceNumber": inv_num,
            class="hl-string">"ActivityName": class="hl-string">"Invoice Created",
            class="hl-string">"EventDateTime": fclass="hl-string">"{create_date} 00:00:00",
            class="hl-string">"CustomerName": cust_name,
            class="hl-string">"InvoiceAmount": amount,
            class="hl-string">"DueDate": due_date,
            class="hl-string">"IsAutomated": True
        })
        
        class=class="hl-string">"hl-comment"># Event: Invoice Cleared
        if status.lower() in [class="hl-string">'closed', class="hl-string">'cleared'] and clear_date:
             event_log.append({
                class="hl-string">"InvoiceNumber": inv_num,
                class="hl-string">"ActivityName": class="hl-string">"Invoice Cleared",
                class="hl-string">"EventDateTime": fclass="hl-string">"{clear_date} 23:59:59",
                class="hl-string">"CustomerName": cust_name,
                class="hl-string">"InvoiceAmount": amount,
                class="hl-string">"DueDate": due_date,
                class="hl-string">"IsAutomated": True
            })
             
        class=class="hl-string">"hl-comment"># Event: Due Date Passed (Calculated)
        class=class="hl-string">"hl-comment"># Logic: If closed and cleared after due date OR if open and today is after due date
        d_due = datetime.strptime(due_date, class="hl-string">"%Y-%m-%d")
        limit_date = datetime.strptime(clear_date, class="hl-string">"%Y-%m-%d") if clear_date else datetime.now()
        
        if limit_date > d_due:
            overdue_ts = d_due + timedelta(days=1)
            event_log.append({
                class="hl-string">"InvoiceNumber": inv_num,
                class="hl-string">"ActivityName": class="hl-string">"Due Date Passed",
                class="hl-string">"EventDateTime": overdue_ts.strftime(class="hl-string">"%Y-%m-%d %H:%M:%S"),
                class="hl-string">"CustomerName": cust_name,
                class="hl-string">"InvoiceAmount": amount,
                class="hl-string">"DueDate": due_date,
                class="hl-string">"IsAutomated": True
            })

        class=class="hl-string">"hl-comment"># Event: Credit Memo Issued
        if inv.get(class="hl-string">'document_type', class="hl-string">'').lower() == class="hl-string">'credit_memo':
             event_log.append({
                class="hl-string">"InvoiceNumber": inv_num,
                class="hl-string">"ActivityName": class="hl-string">"Credit Memo Issued",
                class="hl-string">"EventDateTime": fclass="hl-string">"{create_date} 12:00:00",
                class="hl-string">"CustomerName": cust_name,
                class="hl-string">"InvoiceAmount": amount,
                class="hl-string">"DueDate": due_date,
                class="hl-string">"IsAutomated": True
            })

    class=class="hl-string">"hl-comment"># 2. Fetch Activities / Notes (Calls, Reminders)
    print(class="hl-string">"Fetching Activities...")
    class=class="hl-string">"hl-comment"># In a real scenario, you might iterate invoice_ids in chunks if the API requires filtering by ID
    class=class="hl-string">"hl-comment"># Here we assume an endpoint allowing date filtering similar to invoices
    activities = fetch_paged_data(class="hl-string">"activities", token, {class="hl-string">"date_from": START_DATE, class="hl-string">"date_to": END_DATE})
    
    for act in activities:
        inv_num = str(act.get(class="hl-string">'invoice_number', class="hl-string">''))
        act_type = act.get(class="hl-string">'activity_type', class="hl-string">'').lower()
        act_date = act.get(class="hl-string">'activity_date') class=class="hl-string">"hl-comment"># Assume valid timestamp
        user = act.get(class="hl-string">'performed_by', class="hl-string">'System')
        
        activity_name = None
        if class="hl-string">'email' in act_type or class="hl-string">'letter' in act_type or class="hl-string">'reminder' in act_type:
            activity_name = class="hl-string">"Payment Reminder Sent"
        elif class="hl-string">'call' in act_type:
            activity_name = class="hl-string">"Collection Call Logged"
            
        if activity_name:
            event_log.append({
                class="hl-string">"InvoiceNumber": inv_num,
                class="hl-string">"ActivityName": activity_name,
                class="hl-string">"EventDateTime": act_date,
                class="hl-string">"CollectorName": user,
                class="hl-string">"IsAutomated": user == class="hl-string">'System'
            })

    class=class="hl-string">"hl-comment"># 3. Fetch Promises to Pay
    print(class="hl-string">"Fetching Promises to Pay...")
    ptps = fetch_paged_data(class="hl-string">"promises", token, {class="hl-string">"created_from": START_DATE, class="hl-string">"created_to": END_DATE})
    for ptp in ptps:
        event_log.append({
            class="hl-string">"InvoiceNumber": str(ptp.get(class="hl-string">'invoice_number', class="hl-string">'')),
            class="hl-string">"ActivityName": class="hl-string">"Promise to Pay Created",
            class="hl-string">"EventDateTime": ptp.get(class="hl-string">'created_at'),
            class="hl-string">"CollectorName": ptp.get(class="hl-string">'created_by'),
            class="hl-string">"IsAutomated": False
        })

    class=class="hl-string">"hl-comment"># 4. Fetch Disputes
    print(class="hl-string">"Fetching Disputes...")
    disputes = fetch_paged_data(class="hl-string">"disputes", token, {class="hl-string">"date_from": START_DATE, class="hl-string">"date_to": END_DATE})
    for disp in disputes:
        inv_num = str(disp.get(class="hl-string">'invoice_number', class="hl-string">''))
        create_ts = disp.get(class="hl-string">'create_date')
        status_history = disp.get(class="hl-string">'status_history', [])
        
        class=class="hl-string">"hl-comment"># Event: Dispute Case Opened
        event_log.append({
            class="hl-string">"InvoiceNumber": inv_num,
            class="hl-string">"ActivityName": class="hl-string">"Dispute Case Opened",
            class="hl-string">"EventDateTime": create_ts,
            class="hl-string">"IsAutomated": False
        })
        
        class=class="hl-string">"hl-comment"># Process Audit Trail for Status Changes
        for history in status_history:
            status = history.get(class="hl-string">'status', class="hl-string">'').lower()
            hist_date = history.get(class="hl-string">'date')
            
            if status == class="hl-string">'in_review' or status == class="hl-string">'investigation':
                event_log.append({
                    class="hl-string">"InvoiceNumber": inv_num,
                    class="hl-string">"ActivityName": class="hl-string">"Dispute Under Review",
                    class="hl-string">"EventDateTime": hist_date,
                    class="hl-string">"IsAutomated": False
                })
            elif status == class="hl-string">'resolved' or status == class="hl-string">'closed':
                 event_log.append({
                    class="hl-string">"InvoiceNumber": inv_num,
                    class="hl-string">"ActivityName": class="hl-string">"Dispute Resolved",
                    class="hl-string">"EventDateTime": hist_date,
                    class="hl-string">"IsAutomated": False
                })

    class=class="hl-string">"hl-comment"># 5. Fetch Payments
    print(class="hl-string">"Fetching Payments...")
    payments = fetch_paged_data(class="hl-string">"payments", token, {class="hl-string">"date_from": START_DATE, class="hl-string">"date_to": END_DATE})
    for pay in payments:
        inv_num = str(pay.get(class="hl-string">'invoice_number', class="hl-string">''))
        pay_date = pay.get(class="hl-string">'payment_date')
        pay_amount = float(pay.get(class="hl-string">'payment_amount', 0.0))
        inv_total = float(pay.get(class="hl-string">'invoice_total_amount', 0.0))
        is_matched = pay.get(class="hl-string">'is_matched', False)
        
        class=class="hl-string">"hl-comment"># Determine Partial vs Full
        class=class="hl-string">"hl-comment"># Note: logic simplified; usually compare accumulated payments
        if pay_amount < inv_total:
            act_name = class="hl-string">"Partial Payment Posted"
        else:
            act_name = class="hl-string">"Full Payment Received"
            
        event_log.append({
            class="hl-string">"InvoiceNumber": inv_num,
            class="hl-string">"ActivityName": act_name,
            class="hl-string">"EventDateTime": pay_date,
            class="hl-string">"InvoiceAmount": inv_total,
            class="hl-string">"IsAutomated": True
        })
        
        class=class="hl-string">"hl-comment"># Event: Bank Statement Matched
        class=class="hl-string">"hl-comment"># Trigger if the system flags this payment as successfully matched to bank line
        if is_matched:
             event_log.append({
                class="hl-string">"InvoiceNumber": inv_num,
                class="hl-string">"ActivityName": class="hl-string">"Bank Statement Matched",
                class="hl-string">"EventDateTime": pay_date, class=class="hl-string">"hl-comment"># Often same time as posting
                class="hl-string">"IsAutomated": True
            })

    class=class="hl-string">"hl-comment"># Export
    df = pd.DataFrame(event_log)
    class=class="hl-string">"hl-comment"># Ensure required columns exist even if empty
    required_cols = [class="hl-string">"InvoiceNumber", class="hl-string">"ActivityName", class="hl-string">"EventDateTime"]
    for col in required_cols:
        if col not in df.columns:
            df[col] = None
            
    class=class="hl-string">"hl-comment"># Fill recommended cols with None if missing
    recommended_cols = [class="hl-string">"CustomerName", class="hl-string">"InvoiceAmount", class="hl-string">"DueDate", class="hl-string">"CollectorName", class="hl-string">"IsAutomated"]
    for col in recommended_cols:
        if col not in df.columns:
            df[col] = None

    df.dropna(subset=[class="hl-string">"InvoiceNumber", class="hl-string">"ActivityName", class="hl-string">"EventDateTime"], inplace=True)
    df.sort_values(by=[class="hl-string">"InvoiceNumber", class="hl-string">"EventDateTime"], inplace=True)
    
    output_file = class="hl-string">"HighRadius_EventLog.csv"
    df.to_csv(output_file, index=False)
    print(fclass="hl-string">"Extraction Complete. {len(df)} rows saved to {output_file}")

if __name__ == class="hl-string">"__main__":
    process_extraction()

Your Accounts Receivable Data Template

Your Accounts Receivable Data Template

Accounts Receivable Attributes

Accounts Receivable Activities

Extraction Guides

HighRadius Analytics and Reporting Export

Steps

Configuration

a Sample Query config

HighRadius REST API Data Extraction

Steps

Configuration

a Sample Query python

Ready to Get Started?

Optimize Accounts Receivable and Recover Cash Flow Today

Your Accounts Receivable Data Template

Your Accounts Receivable Data Template

Accounts Receivable Attributes

Accounts Receivable Activities

Extraction Guides

HighRadius Analytics and Reporting Export

Steps

Configuration

a Sample Query config

HighRadius REST API Data Extraction

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Optimize Accounts Receivable and Recover Cash Flow Today