The Top 8 Challenges in Financial Document Data Extraction and How to Overcome Them 

Lenders and financial institutions rely heavily on analysing documents such as payslips, bank statements, tax assessments and invoices. These documents are critical for assessing affordability, verifying income and managing risk. Yet extracting meaningful, reliable data from them and turning this into a useful output is time-consuming and inconsistent. 

Manual document review is slow, prone to human error, and increasingly unsustainable for organisations that need to scale. Most documents arrive in inconsistent formats, from photographs to mobile phone screenshots, making standardisation difficult. Overcoming this challenge requires moving beyond legacy methods towards intelligent, purpose-built document automation like Fortiro Accelerate. 

Accurate and automated data extraction is now essential to make faster decisions, reduce operational delays and remain competitive. Below, we explore the eight most common challenges and how a dedicated income verification solution can help. 

1. Inconsistent document formats 

There is no standard layout for financial documents. Each employer or institution formats payslips and bank statements differently, with varying terminology and data placement. Rule-based systems and templates often break when a new format appears. 

To solve this, Fortiro Accelerate has been refined on large volumes of financial documents. Instead of relying on where data appears, it understands the meaning and context of fields, allowing accurate extraction across diverse layouts. 

2. OCR without interpretation 

Optical Character Recognition (OCR) helps convert text from images to data, but it lacks context. For example, it can read “$5,000” but cannot determine whether it is gross income, net pay, or a deduction. 

Fortiro Accelerate builds on OCR with additional layers of interpretation. It structures and interprets financial data, such as identifying different income types or recognising key dates, providing lenders with reliable, usable information, not just raw text. 

3. Standardising income and deductions from payslips 

Payslips can include variable pay elements like overtime, bonuses, and allowances, as well as diverse deductions. Pay frequencies also differ.  

Fortiro Accelerate is purpose-built to extract and standardise this data, calculating income directly from financial documents, including distinguishing between earnings and deductions, and handling anomalies.  

4. Matching data across documents 

Verifying income often involves checking consistency between documents. Does the salary credit on the payslip match the salary deposit on the bank statement? Does the name align across documents? 

Fortiro Accelerate uses entity recognition and data matching to connect the dots. It automatically checks names, addresses, account numbers and more across documents, highlighting discrepancies that may indicate risk or fraud. 

5. Managing poor-quality and handwritten markups 

Not all documents are digital. Some arrive as scanned images or contain handwritten annotations. Low-quality scans, poor lighting or background noise can cause standard OCR to fail. 

Fortiro Accelerate applies image pre-processing to enhance readability, including de-skewing, noise removal (including ignoring handwritten content) and contrast adjustment.  

6. Detecting document fraud 

Document fraud remains a serious risk in lending and insurance. Changes to names, numbers or dates can go unnoticed by manual review or basic extraction tools. 

Fortiro Protect is designed to detect signs of tampering as part of the income verification process. These checks work together with Fortiro Accelerate and help flag inconsistencies or manipulation early, reducing exposure to fraud. 

7. Integration and workflow bottlenecks 

Extracted data only adds value when it flows into decision systems such as a Loan Origination System (LOS) or Customer Relationship Management (CRM) platform. Manual entry or spreadsheet uploads slow this down and increase errors. 

Fortiro Accelerate integrates via API, pushing structured data directly into core systems in real time. This enables straight-through processing, removing delays and reducing manual handling. 

8. Enabling true straight-through processing (STP) 

Many tools claim high per-field accuracy, but that is not enough. To achieve true STP, all key data must be extracted correctly across the full document set for an application. 

Fortiro Accelerate is built for complete process accuracy, not just isolated data points. It focuses on end-to-end completion to ensure critical fields like income totals and employer names are consistently extracted with confidence, reducing the need for manual intervention. 

Meeting the challenge with Fortiro Accelerate 

These eight challenges demonstrate why legacy methods and standalone OCR are no longer sufficient. Fortiro Accelerate is designed to address them all, combining advanced document analysis, interpretation, cross-checking, and fraud detection into one income verification solution. 

It helps lenders and financial institutions scale operations, improve risk management and make faster, more informed decisions. 

Smart document processing is a competitive advantage 

Organisations that move beyond manual review and basic tools stand to gain significant benefits, from faster approvals and more accurate lending decisions to improved compliance and customer experience.