One of the most common types of fraud in both financial transactions and general business is document fraud, which occurs when scamsters submit altered or fabricated documents in order to improve their chances in any transaction they are engaging in.
The most common form of document fraud occurs in loan applications, banking operations, and other such financial transactions that require one party to submit bank statements and other financial documents. Document fraud can include everything from altering bank statements, to creating fake pay stubs, to altering tax forms, invoices, signatures, dates, etc.
The problem with document fraud, especially in the realm of loan/bank/financial operations, is that it is becoming increasingly easy to execute. With the advancement of digital imaging software and specialized counterfeiting services, it is becoming harder for financial institutions and other businesses to detect fraudulent documents. As a result, document fraud is starting to cost them millions of dollars.
Document fraud is particularly common in online banking and online loan applications and is one of the principal causes of cybercrime. McAfee’s latest report states that cybercrime currently causes $600 billion in damages to the global economy, equivalent to 0.8% of global GDP.
To combat document fraud, not only in the loan/banking process, but also in other business activities, financial institutions and companies are turning to innovative technology solutions. AI and ML-based tools are increasingly being used for document fraud detection.
How document fraud works
Document fraud is a criminal activity that involves the alteration or creation of fraudulent documents. The most common document that is altered is the bank statement in loan applications and other financial activities. These fraudulent bank statements can involve many kinds of alterations, including manipulating individual transactions or fabricating fake records.
One of the primary tools used to alter bank statements and other documents is design software, such as PhotoShop. Fraudsters with expertise in design software have an advantage in committing document fraud, but it is not a requirement.
Many fraudsters can still engage in loan application/bank transaction fraud without the need of design skills. For example, there are online services that specialize in producing “Novelty Bank Statements.” A quick internet search will reveal many of these illegal and unethical services.
In addition to generating fake bank statements, these services also produce other types of fraudulent documents, such as fake pay stubs and bills. These documents are used by fraudsters to secure loans illegitimately.
Degrees of fraud
One way to identify document fraud is by analyzing the skill level of the fraudsters. The degree of sophistication in their fake documents can provide insight on how to prevent future fraud.
At one end of the spectrum, the fraudsters may be relatively unskilled in document manipulation. Their fake documents would contain errors such as changes in fonts, that are easily noticeable and require little effort to detect. These errors are often obvious photoshopped alterations made for a single transaction or two, in order to inflate the fraudster’s bank balance. Both humans and machines can identify this type of fraud, but using automation to handle thousands of pages improves time efficiency.
The next level of document fraud is more sophisticated. These fraudsters create fake documents that look realistic and accurate. Detecting these alterations usually requires the use of anti-fraud technology to prevent fraudulent loan applications from being approved. Anti-fraud technology can pick up on subtle clues such as inconsistent fonts, formatting quirks, and reconciliation errors between transactions and stated account balances.
The most advanced level of document fraud is near-flawless document fabrication. These documents do not generate reconciliation errors, appear real to both human and machine observers, and pass multiple authenticity checks. Detection at this level may require examining the metadata of the file or identifying suspicious patterns of transactions. A fraud detection platform is the ideal method of prevention.
Document fraud is a serious issue for financial institutions and other businesses and there are several solutions that can help fight it. One of the key solutions is the use of automated document tamper detection technology. Many of these tools use artificial intelligence and multiple layers of machine-augmented human review to detect and prevent document fraud. The combination of AI tools and humans-in-the loop leads to more accurate detection of fraud and less false positives, leading to reliability.
When a document fraud is suspected, AI models can be used to automatically reject or flag transactions for further investigation. Additionally, AI models can also provide an assessment of the likelihood of fraud, which can help investigators to prioritize their efforts on the most suspicious cases.
AI can also generate “cause codes” for flagged transactions, which guides the investigator to the specific areas to investigate and speeds up the process. Furthermore, AI models can learn from the actions of investigators when they evaluate and clear questionable transactions, this helps the AI model to improve its knowledge and avoid false positive fraud detections.
Digital data sources can also be used to enhance and simplify their anti-fraud underwriting procedures. Data aggregators such as Plaid, offer access to up to 24 months of transaction history once a borrower has provided bank login credentials. By using data aggregation during the funding process, businesses can confirm that the applicant’s financial documents match the data obtained directly from the bank, ensuring the authenticity of the submitted information.
By combining efficient and precise document processing with digital verification, businesses can optimize for both customer satisfaction and minimal intrusion, while also incorporating multiple layers of fraud detection into their loan application (and other business) verification processes. This approach can help in faster and more reliable approvals for loans and other financial and business services.
Use cases of Document Fraud Detection
Document fraud detection has applications beyond loan applications and financial operations as it is a crucial tool to prevent fraudulent activities across various industries. Fraudulent documents can be used in identity theft, insurance fraud, and real estate fraud. There are several use cases for document fraud detection tools, including:
- Loan application fraud: This is the predominant area where bank statements are altered to secure loans. Document fraud detection tools can help loan and institutions, fdetect and prevent fraud in loan applications by identifying fake bank statements and pay stubs, submitted by borrowers.
- Identity verification: Document fraud verification tools can be used to verify the identity of individuals by analyzing their government-issued ID documents, such as passports and driver’s licenses, to ensure that they are genuine and match the individual’s information.
- KYC (Know Your Customer) compliance: Financial institutions can use document authenticity verification software to verify the identity of their customers and comply with anti-money laundering (AML) and countering the financing of terrorism (CFT) regulations.
- Insurance claims: Insurance companies can use document fraud detection tools to verify the authenticity of documents submitted by claimants, such as medical bills and police reports, in order to prevent fraudulent claims.
- Real estate transactions: Fraud detection tools can be used to detect irregularities in real estate transactions by analyzing documents such as property deeds and title documents to ensure that they are legitimate.
- Employee onboarding: Employers can use document fraud detection tools to verify the identity of job applicants and ensure that their qualifications and work experience are legitimate.
- Government document verification: Government agencies would benefit from fraud detection tools as they can be used to verify the authenticity of government-issued documents, such as birth certificates, marriage certificates and other forms of identification.
Implementing document fraud detection tools can help both financial and non-financial organizations detect and prevent fraudulent activities and bogus loan applicaitons, and also protect their customers and assets, ultimately reducing financial losses and improve the overall security.
Nanonets in the fraud detection protocol
Nanonets is a machine learning Intelligent Document Processing (IDP) solution that allows organizations to easily train and deploy custom AI models. It can be integrated with loan application fraud detection systems in several ways:
- OCR (Optical Character Recognition): Nanonets can be used to extract text from images of documents, such as bank statements and ID cards, which can then be analyzed to detect fraud.
- Image classification: Nanonets can be used to train image classification models to identify fake documents, such as doctored bank statements or ID cards, based on patterns and features that are unique to genuine documents.
- Data validation: Nanonets can be used to train models to validate the data entered into forms, such as loan applications, by cross-referencing it with other sources of information, such as bank account data, to detect inconsistencies and potential fraud.
- Signature verification: Nanonets can be used to train models to verify the authenticity of signatures on documents, such as loan applications and ID cards, by comparing them to known genuine signatures.
- Document segmentation: Nanonets can be used to train models to segment documents into individual fields and extract specific information such as account number, name, and address. This information can then be compared with the original document to detect tampering or fraud.
By integrating Nanonets with document fraud detection systems, organizations can improve the accuracy and speed of their fraud detection processes, and also automate the process, increasing efficiency and reducing the risk of human error.
The use of AI-enabled tools for document fraud detection has become increasingly important as fraudsters continue to find new ways to bypass traditional fraud detection methods. AI-enabled data validation, when combined with Intelligent Document Processing solutions can process large amounts of data and identify patterns that may be missed by human analysts, resulting in more accurate and efficient detection of fraud. They can also learn from past transactions and adjust their models accordingly, improving their performance over time.
The implementation of AI-enabled tools for loan application fraud detection (and other types of document fraud detection) can lead to reduced costs, better classification and digitization accuracies, and more efficient systems, making it a valuable solution for organizations across various industries to protect their assets and customers.