FinCEN has warned financial institutions about a surge in check fraud schemes targeting U.S. mail. Financial institutions filed over 680,000 SARs for check fraud in 2022, almost doubling the previous year’s filings.
Check fraud is still a cause for concern for all the banks out there, irrespective of the decline in the usage of checks. Criminals use counterfeiting, check washing, and mail-related thefts to steal checks, make purchases, or withdraw money.
Investigating check fraud cases is overwhelming. Bankers manually examine checks and verify additional documents, such as deposit slips, payment orders, and bank statements. This process is time-consuming, monotonous, and daunting for bankers. Moreover, deciphering handwritten checks poses its own challenges.
Automated check image processing can quickly, easily, and reassuringly mitigate the above-mentioned pain points. Automated check image processing uses software and technology to read and interpret check images and extract relevant information.
ScanWriter, a product by Personable, offers automated check image processing to enable seamless check fraud investigations. This powerful financial investigation software captures data from thousands of checks in minutes with 100% accuracy. ScanWriter also organizes data into Excel sheets and provides automated data visualizations in PowerBI for quick and efficient analysis.
Shortcomings of Existing Automated Check Image Processing Solutions
Various tools like Adobe and OCR-based software offer automated check image processing to streamline the tedious manual process of capturing data from checks. While these tools can be helpful, they still have limitations that must be considered.
Low Accuracy: OCR-based software for automated check image processing may not accurately capture data with 100% accuracy, leading to an increased workload for bankers to validate the data before proceeding with fraud investigations.
Unorganized Data: OCR software often needs a more systematically organized data format, posing challenges for investigators to comprehend and requiring additional time for data organization. Furthermore, accurately capturing handwritten data can be complex for OCR-based software.
Incompatible Integration With Data Visualization Tools: One of the challenges associated with check fraud investigations is the limited integration of automated check image processing tools with data visualization platforms such as Power BI. This lack of integration results in a deficiency of pre-built visualizations, like the flow of funds, which are extremely valuable for effectively investigating instances of check fraud.
Limited Features: Not many software solutions offer one-click source verification, automatic audit trail, automatic creation of financial models like the flow of funds for asset tracing, and case management capability for effective collaboration.
Risk of Data Breach: With cloud-based solutions for check image processing, there is always a risk of data breach. Due to the sensitivity of the information involved, banks would prefer an on-premise solution.
Automated Check Image Processing: ScanWriter – A Trusted Choice for Banks
When selecting an automated check image processing tool, financial institutions should prioritize streamlined fraud investigations, accurate data capture, strict security protocols, and seamless integration with data visualization software like Microsoft Power BI. Cost-effectiveness should also be considered.
Introducing ScanWriter by Personable, the perfect financial fraud investigation software.
ScanWriter is an innovative, powerful, and seamless automated check image processing solution trusted by banks. With on-premise deployment for enhanced security, quick and accurate data capture from various paper and digital documents, including bank statements, bills, invoices, receipts, insurance forms, and check images, into Excel within minutes.<