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Convert PDF bank statements to Excel
A bank statement is a document that shows all transactions made in a bank account, including deposits, withdrawals, and payments. It is commonly used by lenders as a way to verify an applicant’s income and financial stability before approving a loan or credit.
However, as technology has advanced, it has become easier for scammers to create fake bank statements that look legitimate. These fake bank statements can be used to misrepresent an applicant’s income and financial stability, making them appear more creditworthy than they really are.
The use of fake bank statements in loan applications can have serious consequences for lenders and borrowers. False statements can be used to inflate income, hide financial responsibilities, or misrepresent a borrower’s financial situation. This can lead to lenders extending credit to borrowers who are actually unable to repay the loan. Additionally, lenders may be exposed to legal liability if they fail to properly verify the information contained in a false bank statement. Borrowers can also be plagued by debt and legal problems.
Therefore, lenders are constantly looking for ways to detect fake bank statements and protect themselves against fraud.
This can include manual verification of returns, using data from the return to compare it with other sources of information, which is time consuming and error prone.
In this post, we’ll cover why fake bank statements are a major problem for lenders to solve, and how using AI and machine learning technologies like Nanonets can help.
Automate your mortgage processing, underwriting, fraud detection, bank reconciliations or accounting processes with a custom workflow out of the box.
How do lenders spot fake bank statements?
Bank statement verification can be a laborious and time-consuming process, especially when dealing with a large number of records or statements. Usually done manually, the following steps are involved in detecting fake bank statements:
- Inconsistencies or irregularities in the information in the declaration: One way to spot a fake bank statement is to look for inconsistencies or irregularities in the information on the statement. For example, a statement that shows large or unusual transactions, has inconsistent spelling errors, sizes, and fonts is a potential red flag.
- Compare the declaration with other documents: Lenders may also compare the statement with other documents provided by the borrower, such as identification or pay stubs, to ensure that the information provided matches and that the statement is not false.
- Check authenticity: Lenders can verify authenticity by contacting the bank listed on the statement and verify whether the statement is genuine or not.
- Check for discrepancies with bank records: Lenders may also check statement information against bank records to make sure the statement is legitimate.
- Use specialized software: Specialized software and services are also available that can help lenders spot fake bank statements by analyzing the document and comparing it to a database of known fake statements. Some of these methods involve:
- Data extraction and analysis: Lenders can use specialized software or services to automatically extract data from bank statements and analyze them for inconsistencies or irregularities.
- Fraud detection software: Some lenders use specialized fraud detection software to scan bank statements for patterns or characteristics commonly associated with false statements.
It’s important to note that while these methods can be effective for verifying bank statements, they can be time consuming and labor intensive. This is where machine learning, coupled with human judgment, can come in handy.
Despite the above methods, fraudulent and altered documents may be undetectable to the human eye. Manual reviews are also time-consuming, error-prone, and use company resources intensively.
This is where automation technologies like Nanonets can help. Nanonets is an AI-based optical character recognition (OCR) tool that can help automate data extraction from various types of documents.
Nanogrids can extract data from bank statements at scale, allowing large numbers of statements to be quickly and accurately verified. The platform can be used to model, identify and flag suspicious returns, and even automatically cross-check the return information against other sources of information. This can save lenders a significant amount of time and effort, and help protect their customers from fraud.
Automating the extraction of data from bank statements using Nanonets provides many benefits, including:
- Greater precision and the consistency of data extraction, as AI-powered technology can identify patterns in the data and extract them precisely.
- Reduction of time, effort and costs compared to manual data extraction and verification, as AI-powered technology can do it faster and more accurately.
- enhanced securitysince automated processes and models can be taught to detect and alert any suspicious activity.
- Improved customer experienceas AI-powered technology can quickly and accurately extract the data needed to give customers the best experience.
Automate your mortgage processing, underwriting, fraud detection, bank reconciliations or accounting processes with a custom workflow out of the box.
Carry
Fake bank statements are a growing problem for lenders, as they can be used to fraudulently obtain loans or credit. The sophistication of these fake bank statements is increasing with more advanced technologies. The challenge for lenders is to quickly and accurately detect these false statements to prevent fraud and protect their customers.
Nanogrids can be a valuable tool for lenders in the fight against false bank statements. By quickly and accurately verifying a large number of account statements, lenders can protect their customers and prevent fraud.