AI-Bank Statement Parser in Power Automate

PDF4me AI-Bank Statement Parser extracts structured data from bank statements using AI-powered machine learning through Power Automate flows. Process bank statement PDFs or images via Power Automate triggers, binary data, base64 strings, or public URLs to automatically extract account information, transaction details, balances, fees, interest, recurring payment patterns, unusual transactions, spending analytics, and comprehensive financial insights with high accuracy and intelligent field recognition. This solution is ideal for bank statement processing automation, financial statement digitization, transaction analysis, bank reconciliation, cash flow management, spending analytics, automated accounting, and financial data extraction workflows that require AI-powered extraction with structured output and seamless Microsoft 365 integration.

Authenticating Your API Request

To access the PDF4me Web API through Power Automate, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user, enabling seamless integration between your Power Automate flows and PDF4me's powerful AI-powered bank statement processing services.

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Key Features

• AI-Powered Extraction: Advanced machine learning technology for accurate bank statement data extraction
• Multi-Format Support: Process bank statements in PDF, PNG, JPG, and JPEG formats
• Comprehensive Transaction Analysis: Extract detailed transaction information including dates, amounts, descriptions, types, and categories
• Balance Tracking: Extract opening balance, closing balance, total deposits, and total withdrawals
• Pattern Recognition: Identify recurring payments and unusual transactions automatically
• Check Processing: Extract paid check information including check numbers, amounts, payees, and dates
• Financial Analytics: Generate spending summaries, category breakdowns, and transaction insights
• Bank Information Extraction: Extract bank name, account holder, account number, account type, and branch details
• Statement Period Recognition: Automatically identify statement start and end dates
• Microsoft 365 Integration: Seamlessly integrate extracted data with SharePoint, Excel, Dynamics 365, and Power BI

Parameters

Complete list of parameters for the AI-Bank Statement Parser action. Configure these parameters to control bank statement processing and data extraction.

Important: Parameters marked with an asterisk (***) are required and must be provided for the action to function correctly.

Document Source Parameters

Parameter	Type	Description	Example
Statement File Content***	Binary	Source Bank Statement Binary Data • Map bank statement file content from previous Power Automate action • Supports dynamic expressions: body('Get_file_content') • Compatible with Dropbox, SharePoint, OneDrive, and email attachments • Supports .pdf, .png, .jpg, .jpeg formats	body('Get_file_content')
Statement Name***	String	Bank Statement File Identifier with Extension • Specify the name of the input bank statement file with proper extension • Used for format detection and AI processing optimization • Supports dynamic naming from flow variables • Must include file extension (.pdf, .png, .jpg, .jpeg) • Enables document tracking in logs and audit trails	statement_2024_01.pdf

Advanced Parameters

Parameter	Type	Description	Example
Body/bankName	String	Optional Bank Name • Optional bank name for improved parsing accuracy • Specify bank name to enhance extraction precision • Helps AI engine optimize field recognition for specific bank formats • Improves accuracy when processing statements from known banks	Chase Bank
Body/analyzePatterns	Boolean	Pattern Analysis Enable • Enable or disable pattern analysis for recurring payments and unusual transactions • true = enables advanced pattern recognition and analysis • false = processes statement without pattern analysis • When enabled, extracts recurring payment patterns and identifies unusual transactions	Yes
Body/customFieldKeys	Array	Optional Custom Field Keys List • Optional list of custom field keys to extract from the bank statement • Specify additional fields beyond standard statement data • Supports multiple custom field keys for enhanced data extraction • Enables extraction of domain-specific or custom statement fields • Each item in the array represents a custom field key to extract	["customField1", "customField2"]

Output

The PDF4me AI-Bank Statement Parser action returns comprehensive output data for seamless Power Automate flow integration:

Table

Table View

Response data in a structured table format:

Parameter	Type	Description
bankName	String	The name of the bank extracted from the bank statement
accountHolderName	String	The name of the account holder extracted from the bank statement
accountNumber	String	The bank account number extracted from the bank statement
accountType	String	The type of bank account extracted from the statement (e.g., Checking, Savings)
branch	String	The branch location or identifier extracted from the bank statement
statementNumber	String	The statement number or reference identifier extracted from the bank statement
statementPeriod	Object	Object containing statement period information with start date and end date (YYYY-MM-DD format)
balances	Object	Object containing balance information including opening balance, closing balance, total deposits, and total withdrawals
currency	String	The currency code (ISO 4217) of the bank statement amounts (e.g., USD, EUR, INR)
fees	Number	The total fees charged during the statement period, with precise decimal handling
interest	Number	The total interest earned during the statement period, with precise decimal handling
transactions	Array	Array of individual transactions with dates, descriptions, amounts, types, balances, categories, merchants, and reference numbers
checksPaid	Array	Array of checks paid during the statement period including check numbers, paid dates, amounts, payees, and descriptions
patterns	Object	Object containing pattern analysis results including recurring payments and unusual transactions
summary	Object	Object containing summary analytics including total transactions, category summaries, average daily balance, largest credit, and largest debit
fallbackUsed	Boolean	Boolean flag indicating whether fallback extraction methods were used during processing
warnings	Array	Array of warning messages indicating potential data quality issues or extraction challenges encountered during processing
jobId	String	Unique identifier for the AI processing job, used for tracking and debugging
jobIdExt	String	External job identifier for integration with third-party systems, if applicable
success	Boolean	Boolean flag indicating the success or failure of the AI-powered bank statement data extraction
message	String	Descriptive message indicating the result of the AI-powered bank statement data extraction process

JSON

JSON Response Format

The raw JSON response from the action:

{
  "bankName": "Chase Bank",
  "accountHolderName": "John Michael Smith",
  "accountNumber": "1234567890",
  "accountType": "Checking",
  "branch": "New York Main Branch",
  "statementNumber": "STMT-2024-001",
  "statementPeriod": {
    "startDate": "2024-01-01",
    "endDate": "2024-01-31"
  },
  "balances": {
    "openingBalance": 5000.00,
    "closingBalance": 6750.00,
    "totalDeposits": 3500.00,
    "totalWithdrawals": 1750.00
  },
  "currency": "USD",
  "fees": 5.00,
  "interest": 2.50,
  "transactions": [
    {
      "transactionDate": "2024-01-05",
      "description": "Direct Deposit - Salary",
      "amount": 3500.00,
      "type": "credit",
      "balance": 8500.00,
      "category": "Income",
      "merchant": "Employer Corp",
      "referenceNumber": "REF123456"
    },
    {
      "transactionDate": "2024-01-10",
      "description": "Online Payment - Utilities",
      "amount": 250.00,
      "type": "debit",
      "balance": 8250.00,
      "category": "Utilities",
      "merchant": "Electric Company",
      "referenceNumber": "REF789012"
    },
    {
      "transactionDate": "2024-01-15",
      "description": "ATM Withdrawal",
      "amount": 200.00,
      "type": "debit",
      "balance": 8050.00,
      "category": "Cash",
      "merchant": "ATM Network",
      "referenceNumber": "ATM345678"
    }
  ],
  "checksPaid": [
    {
      "checkNumber": "1234",
      "paidDate": "2024-01-12",
      "amount": 500.00,
      "payee": "ABC Corporation",
      "description": "Invoice Payment"
    },
    {
      "checkNumber": "1235",
      "paidDate": "2024-01-20",
      "amount": 800.00,
      "payee": "XYZ Services Ltd.",
      "description": "Service Fee"
    }
  ],
  "patterns": {
    "recurringPayments": [
      {
        "merchant": "Electric Company",
        "amount": 250.00,
        "frequency": "Monthly",
        "recurringDates": ["2024-01-10", "2024-02-10", "2024-03-10"]
      }
    ],
    "unusualTransactions": [
      {
        "unusualDate": "2024-01-15",
        "description": "Large ATM Withdrawal",
        "amount": 200.00,
        "reason": "Amount exceeds typical withdrawal pattern"
      }
    ]
  },
  "summary": {
    "totalTransactions": 3,
    "categorySummary": {
      "Income": {
        "count": 1,
        "totalAmount": 3500.00,
        "averageAmount": 3500.00,
        "percentage": 66.67
      },
      "Utilities": {
        "count": 1,
        "totalAmount": 250.00,
        "averageAmount": 250.00,
        "percentage": 4.76
      },
      "Cash": {
        "count": 1,
        "totalAmount": 200.00,
        "averageAmount": 200.00,
        "percentage": 3.81
      }
    },
    "averageDailyBalance": 6750.00,
    "largestCredit": {
      "largestTransactionDate": "2024-01-05",
      "amount": 3500.00,
      "description": "Direct Deposit - Salary"
    },
    "largestDebit": {
      "largestTransactionDate": "2024-01-12",
      "amount": 500.00,
      "description": "Check Payment - ABC Corporation"
    }
  },
  "fallbackUsed": false,
  "warnings": [],
  "jobId": "12345678-1234-1234-1234-123456789012",
  "jobIdExt": "STMT-2024-001",
  "success": true,
  "message": "Bank statement data extracted successfully using AI technology"
}

Flow Integration

Power Automate Flow Usage

The extracted bank statement data enables powerful automation across Microsoft ecosystem:

• SharePoint Lists: Store extracted statement data in SharePoint lists for financial tracking and reconciliation
• Excel Integration: Export transaction data to Excel workbooks for financial analysis and reporting
• Dynamics 365: Create bank reconciliation records and financial entries automatically
• SQL Database: Insert extracted statement data into SQL Server databases for financial data warehousing
• Power BI: Feed statement data into Power BI dashboards for cash flow analysis and spending insights
• Email Notifications: Send statement summaries and financial alerts via Outlook
• Approval Workflows: Route statements or transactions based on extracted amounts using Power Automate approvals
• Bank Reconciliation: Match extracted transactions with accounting records for automated reconciliation
• Expense Tracking: Categorize and track expenses using extracted transaction data
• Financial Reporting: Generate financial reports from extracted statement and transaction data
• Document Storage: Link extracted statement data with original statement documents in SharePoint document libraries

Workflow Examples

The PDF4me AI-Bank Statement Parser action in Power Automate provides comprehensive workflow templates designed for real-world business scenarios:

Bank Reconciliation Automation

Automated Bank Reconciliation Workflow

Streamline your bank reconciliation processes with AI-powered statement data extraction:

Complete Workflow Steps:

1. Trigger: Bank statement PDF uploaded to SharePoint or received via email
2. AI Bank Statement Parser: Extract account, transactions, balances, and check information using PDF4me AI
3. Account Matching: Match extracted account number with accounting system accounts
4. Transaction Matching: Match extracted transactions with accounting records
5. Balance Verification: Compare extracted opening and closing balances with accounting system
6. Check Reconciliation: Reconcile extracted check payments with accounts payable records
7. Create Reconciliation Record: Insert statement data into Dynamics 365 Finance or accounting system
8. Update SharePoint: Store extracted statement data in SharePoint list with reconciliation status
9. Exception Handling: Flag unmatched transactions or discrepancies for manual review
10. Email Notification: Notify accounting team with reconciliation summary and exceptions
11. Archive: Move processed statement to archive folder with extracted metadata

Business Benefits:

• Automates bank reconciliation for monthly and daily statements
• Reduces manual reconciliation time by 90%
• Eliminates human errors in transaction matching
• Accelerates month-end and year-end closing processes
• Maintains complete audit trail of all reconciliation activities

Create Flow

Cash Flow Analysis Automation

Automated Cash Flow Analysis Workflow

Automate cash flow monitoring and analysis with intelligent statement data extraction:

Complete Workflow Steps:

1. Trigger: Bank statement received via email or uploaded to SharePoint
2. AI Bank Statement Parser: Extract transactions, balances, deposits, and withdrawals with pattern analysis enabled
3. Cash Flow Calculation: Calculate net cash flow from extracted deposits and withdrawals
4. Balance Tracking: Track opening and closing balances for trend analysis
5. Power BI Update: Send extracted data to Power BI dataset for cash flow dashboards
6. Excel Export: Export transaction data to Excel workbook for detailed analysis
7. Alert Generation: Generate alerts for low balances or unusual transaction patterns
8. Report Creation: Generate cash flow reports from extracted statement data
9. Dashboard Update: Update financial dashboards with latest cash flow metrics
10. Notification: Send cash flow summary email to finance team and management

Business Benefits:

• Real-time cash flow visibility and monitoring
• Automatic cash flow trend analysis
• Proactive alerts for cash flow issues
• Improved financial planning and decision-making
• Automated financial reporting and analytics

Create Flow

Expense Tracking & Categorization

Automated Expense Tracking Workflow

Automate expense tracking and categorization using extracted transaction data:

Complete Workflow Steps:

1. Trigger: Bank statement uploaded to SharePoint expense tracking folder
2. AI Bank Statement Parser: Extract transactions with categories, merchants, and descriptions
3. Expense Categorization: Use extracted categories and merchants for expense classification
4. Budget Comparison: Compare extracted expenses against budget limits using Power Automate
5. Excel Update: Append categorized expenses to Excel expense tracking workbook
6. SharePoint List: Store categorized expenses in SharePoint list for team visibility
7. Power BI Integration: Feed expense data into Power BI for expense analytics dashboards
8. Approval Routing: Route high-value expenses to managers for approval
9. Receipt Matching: Match extracted transactions with receipt images in SharePoint
10. Expense Report: Generate expense reports from categorized transaction data
11. Notification: Send expense summary to finance team with categorization details

Business Benefits:

• Automated expense categorization reduces manual effort
• Real-time expense tracking and budget monitoring
• Improved expense visibility and control
• Faster expense reporting and reimbursement
• Comprehensive expense analytics and insights

Create Flow

Fraud Detection & Monitoring

Automated Fraud Detection Workflow

Monitor and detect fraudulent activities using extracted transaction patterns:

Complete Workflow Steps:

1. Trigger: Bank statement uploaded to SharePoint fraud monitoring folder
2. AI Bank Statement Parser: Extract transactions with pattern analysis enabled
3. Pattern Analysis: Identify unusual transactions and recurring payment patterns
4. Fraud Detection Rules: Apply fraud detection rules to extracted transactions
5. Anomaly Detection: Flag transactions that deviate from normal patterns
6. Alert Generation: Generate alerts for suspicious transactions or patterns
7. Security Team Notification: Email security team with flagged transactions
8. Create Investigation Record: Log suspicious transactions in SharePoint or SQL database
9. Dashboard Update: Update fraud monitoring dashboard with latest findings
10. Compliance Reporting: Generate fraud detection reports for compliance purposes

Business Benefits:

• Automated fraud detection and monitoring
• Early identification of suspicious activities
• Reduced fraud losses through proactive detection
• Comprehensive fraud audit trails
• Improved security and compliance

Create Flow

Industry Use Cases & Applications

Finance & Accounting

Finance & Accounting Use Cases

• Bank Reconciliation: Automate bank reconciliation using extracted statement transactions
• Financial Reporting: Generate financial reports from extracted statement and transaction data
• Cash Flow Management: Monitor and analyze cash flows using extracted balance and transaction information
• Audit Compliance: Maintain structured statement data for audit trails and compliance reporting
• Expense Management: Track and categorize expenses using extracted transaction data

Banking & Financial Services

Banking & Financial Services Use Cases

• Statement Processing: Automate bank statement processing and digitization
• Transaction Analysis: Analyze transaction patterns and trends from extracted statement data
• Account Verification: Verify account information using extracted account details
• Fraud Detection: Detect fraudulent activities using extracted transaction patterns
• Customer Service: Provide faster customer service with automated statement data extraction

Treasury Management

Treasury Management Use Cases

• Cash Position Monitoring: Track cash positions using extracted balance information
• Liquidity Analysis: Analyze liquidity using extracted transaction and balance data
• Payment Tracking: Track payments and receipts using extracted transaction details
• Financial Planning: Support financial planning with extracted cash flow data
• Risk Management: Monitor financial risks using extracted transaction patterns

Accounting & Bookkeeping

Accounting & Bookkeeping Use Cases

• Journal Entries: Automate journal entry creation from extracted transaction data
• Account Reconciliation: Reconcile accounts using extracted statement transactions
• Transaction Posting: Automatically post transactions to accounting systems
• Financial Close: Accelerate month-end and year-end closing processes
• Expense Allocation: Allocate expenses using extracted transaction categories

Business Intelligence & Analytics

Business Intelligence & Analytics Use Cases

• Spending Analytics: Analyze spending patterns from extracted transaction and category data
• Financial Dashboards: Build financial dashboards using extracted statement data
• Trend Analysis: Identify financial trends from extracted transaction history
• Forecasting: Support financial forecasting with extracted cash flow data
• Performance Metrics: Calculate financial performance metrics from extracted statement data

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