What is Document Fraud, and How to Prevent It?
Information processing volumes have increased in document fraud cases in recent decades as fraudsters create fake records. Machine learning now improves document fraud detection, vital as consumers demand accurate identification while scamming costs economies.
Officially verifying identities remains crucial as various industries rely on documents for transactions and verification, yet document forging grows more sophisticated.
Advanced detection is needed to protect customers and organizations from increasing losses due to smarter document fraud.
Proportion of document fraud cases for various industries
The FTC received over 2.1 million fraud reports in 2020 related to identity theft and misused personal information, totaling over $3.3 billion in losses. Imposter scams represented the most common form of document fraud, while stolen online account credentials were second.
Real estate fraud takes many forms, and victims must fight wrongful evictions or legal ownership claims that incur heavy costs.
Document fraud impacts various industries. Shipping documents can be altered to redirect cargo, while incorrect customs declarations risk penalties. The logistics industry faces risks like miscoding goods classifications. Accounts payable fraud threatens all businesses, from duplicate payments to fraudulent invoices.
Even large companies can suffer major losses from a single illegitimate email, as a news report described one firm losing $8 million from a deceptive payment request. Protecting sensitive data exchanged within complex supply chains remains challenging for maritime transportation.
Advances in fraud detection are needed across sectors to curb growing document scams and their heavy financial toll.
Types of document fraud
Document fraud is a major issue, valued at 3.2 trillion pounds, making it a prime target for fraudsters. The most common types include:
1. Forged Documents: These are files with tampered details, such as altered timestamps, watermarks, pages, or signatures, compromising their integrity.
2. Invoice Frauds: This occurs when an employee impersonates a vendor, generating false invoices to redirect company funds to personal accounts.
3. Blank Documents: Leaked from the supply chain, these documents can be manipulated with false information due to their empty fields, requiring verification for security.
4. Camouflage Documents: Fraudsters create fake identities, posing as government officials or authorized entities. This rare fraud type can evade detection if unchecked.
5. Counterfeit Documents: Unauthorized reproductions of official documents used to access confidential information. Examples include using a fake driving license to obtain social security numbers and bank account details.
Red flags in documentation checks
Human error makes manual checks for document fraud insufficient. Look for spelling mistakes, inconsistent fonts, and blurred text to spot fake documents.
For large volumes, use document fraud detection software with automated workflows to validate and verify information structure and visual details.
However, here are a few red flags to watch out for when reviewing the information presented in structured and unstructured documents:
- Metadata Analysis: PDF files that show structural inconsistencies and have suspicious zones that are too different from the original parts of documents
- Financial transactions: Bank statements that cross-check monthly income with average balance and key financial APIs for verifying customer details
- OCR and Barcode Data: Content obtained through OCR reading, biometric identification, and barcode scanning can be validated against official data repositories for verification and validation purposes
- Duplicate Reports: These schemes involve using duplicate invoices or making double payments. Another red flag is when an employee raises a refund after purchasing an item using the company’s funds and transfers the money directly to their account.
- Other Variables: Reviewing metrics like total decline rates, cost per analysis, checkout abandonment rates, invoice numbers, and key fraud APIs
Ultimately, human error is involved, which is why no document processing software is 100% accurate.
How Docsumo helps you to detect fraud in real-time
Docsumo uses automated procedures to scan document fields and elements, analyze issue dates, identify low-quality images, and spot photo discrepancies between real and fake documents.
Optical Character Recognition (OCR) detects text element changes, while advanced image editors enhance visual clarity and authenticity.
Fake document recognition systems map protection elements and cross-reference data from authorized sources to confirm information validity. If discrepancies arise, the platform flags them for review.
Key features of Docsumo’s document fraud detection include:
- Black & White Photos: Identifies duplicate document copies, often indicating fraud.
- Document Cropping: Flags cropped documents with missing details for review.
- Scanned Images: Uses OCR and AI to detect non-original, scanned documents.
- Photo on Photo: Detects photos of existing documents by analyzing lighting, angle, and exposure with machine learning algorithms.
Docsumo also detects formatting and presentation inconsistencies, extracts KPI values, and creates automated workflows to cross-check page structures.
It alerts users if missing pages or invoice subtotals don’t match taxes. Additionally, Docsumo uses 2-way matching to validate document details against company databases.
Conclusion
Docsumo leverages smart, efficient processes to analyze documents quickly and resolve fraud queries swiftly. Machine Learning algorithms and pre-trained APIs enhance manual reviews, accelerating the detection of fraudulent documents.
Advanced data extraction and OCR technology scale operations, reducing processing times from hours to seconds, minimizing human errors by identifying tampering patterns promptly.
Please take a look at our entire blog on Document Fraud and how to prevent it.
