AI-powered Data Standardization and Format Management
Invoice Format Standardization
Data Extraction Technologies: Advanced OCR (Optical Character Recognition) and NLP (Natural Language Processing) technologies to extract data from various invoice formats, including PDFs, scanned images, and electronic documents.
Template Recognition: ML algorithms capable of identifying and learning from different invoice templates, allowing the system to recognize and extract relevant fields such as invoice number, dates, amounts, and line items, regardless of the template layout.
Data Validation and Cleansing: Validation rules to check the accuracy of the extracted data (e.g., matching total amounts with sum of line items). Include data cleansing steps to correct common errors like misinterpretation of characters or formats.
Auto-mapping to Standardized Data Schema: ML powered solution to automatically map source attributes to standardized schema or data model where all extracted invoice data can be mapped. Flexible schema to accommodate the variety of data fields found in different invoices.
User Feedback Loop: User feedback mechanism where incorrect extractions can be manually corrected, and these corrections are fed back into the system to improve accuracy over time.
Integration with ERP Systems: Easy integration of standardized data into existing ERP systems or accounting software for further processing and analysis.
Payment Data Normalization
Multi-Source Data Integration: Data integration from various payment platforms and banks, each potentially having its own data format and transmission method (APIs, file uploads, direct feeds).
Normalization Rules: Set of rules and algorithms to transform disparate payment data into a uniform format. This includes standardizing date formats, currency, payment terms, and categorizing payment types (ACH, credit card, wire transfer, etc.).
Reconciliation Mechanisms: Mechanisms to match normalized payment data with corresponding invoices or accounts receivable entries, considering partial payments, overpayments, and aggregated payments.
Anomaly Detection: AI-powered solution to identify anomalies in payment data, such as unusual payment amounts or frequency, which might indicate errors or fraudulent activity.
Want to print your doc? This is not the way.
Try clicking the ⋯ next to your doc name or using a keyboard shortcut (