Automated cheque parser for back office operations

Payments for loans are often done through cheque at the acquisitions stage as well as during EMI payment and closure stages. Cheques have become an important part of the loan business, so extracting the right information and storing it is crucial.

Most banks have back-office teams to perform this task but with manual intervention, it is expensive as well as prone to errors. Modern technological advancements provide ways to automate this process. It increases the accuracy as well as saves on cost in long term.

This solution is a tool designed to extract information from images of cheques. It leverages Azure Document Intelligence Studio, which utilizes machine learning and advanced Optical Character Recognition (OCR) capabilities to analyze and extract key fields and line items from scanned cheques.

Additionally, this tool can be custom-trained and extended to extract information from various documents such as invoices, utility bills, sales orders, and purchase orders. It supports a wide range of formats and qualities, including phone-captured images, scanned documents, and digital PDFs.

This solution is designed for organizations requiring precise documentation of cheque transactions. It effectively reduces manual labor and errors in back-office tasks by implementing an automated, digitized data storage system.

The business benefits include:

1. Cost: This solution minimizes the manual effort needed to copy cheques and maintain digital records.
2. Accuracy: It helps prevent manual errors during the record-copying process.

No predetermined data is needed for this solution.

Optical Character Recognition (OCR)

1. On prem ( on customer systems or on DeepQ-AI Environment)
2. On hosted cloud space ( Customer or DeepQ-AI Environment)
   ( deployment is subject to data availability in the same environment, or feasibility of seamless data transfers within secured environments)”

1. Final outputs could include cheque data in digital form.
2. Batch files, such as Excel files or flat files.
3. Outputs can be shared through API requests. By sending an API request with inputs, you can receive a response. This can be integrated into an existing application or a separate web app can be created.”