Extracting Data from Bank Statements with Intelligent Document Processing
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Make lending decisions faster and more reliable by automating data extraction from bank statements.
Identify, classify, and validate bank statements as per your process requirements.
Ready-to-use, pre-built bank statement extractor that requires zero training data.
Plugs into your existing systems and processes.
What are bank statements?
A bank statement is a monthly financial document that provides a summary of the account holder’s activity. Bank statements are generally prepared by the bank for the account holder at the end of each month. Bank statements can be found online via online banking or be obtained from a branch of the bank. They are also commonly known as account statements or transaction summary statements.
What can you infer from bank statements?
Bank statements hold the data that tracks an individual's or business's cash flow. It is used to predict spending potential, document expenditure, assess income or profit, and maintain records of all transactions. A bank statement contains information about an individual’s financial health and credit reliability which is essential for all lending decisions.
Who uses bank statement data?
Bank statements are used in various industries to assess and validate their consumers and their claims. Bank statements are most used by:
Mortgage Providers
Government Agencies
Banks
Private Lenders
Tax Services
Auditors
Insurance Providers
Where are bank statements used?
Bank statements are often used to verify the creditworthiness of an individual or business. They are also used to verify the expenses and assets of individuals. Bank statements are generally used for:
Mortgage Applications
Refinancing
Small Business Loans
Visa Applications
Credit Card Applications
Tax Filing & Auditing
Insurance Claims
Who uses bank statement data?
Bank statements are used in various industries to assess and validate their consumers and their claims. Bank statements are most used by:
Mortgage Providers
Government Agencies
Banks
Private Lenders
Tax Services
Auditors
Insurance Providers
What is intelligent automation of bank statement extraction?
Intelligent automation of bank statement extraction refers to using artificial intelligence and machine learning technologies to automate data extraction from bank statements. By using Infrrd IDP for bank statement data extraction, financial companies will be able to make faster and data-driven lending decisions. Our platform provides granular-level access to the data in bank statements such as validating the recency of the statements, identifying transaction categories, and deriving values based on pre-set conditions.
Here is a comparison of the benefits of manual processing of bank statements against human-steered Infrrd IDP
What are the benefits of automating bank statement data extraction?
Fraud and suspicious activity detection
Data protection
Eliminate error oversight
Data Intelligence
Credit Card Applications
Faster approvals
Frequently asked questions
What is intelligent document processing for banks?
Intelligent document processing in banking utilizes AI and machine learning to transform data extraction, particularly from bank statements. Specialized bank statement extraction software - like Infrrd - employs advanced algorithms for precise interpretation, expediting the process and reducing errors.
This integration streamlines financial documentation management, providing a more agile and accurate information-handling paradigm within the dynamic banking sector. As banks embrace these innovations, the use of intelligent document processing becomes crucial for staying competitive and maintaining high standards of accuracy and efficiency in the rapidly evolving industry.
Infrrd's Intelligent Document Processing (IDP) technology adeptly extracts data from bank statements through advanced AI and machine learning algorithms. Trained meticulously to comprehend diverse statement formats, this system accurately identifies and extracts vital data points, ensuring precision.
Complementing this, Infrrd's bank statement extraction software offers a sophisticated solution, adapting to evolving document structures and enhancing reliability. For in-depth insights into guaranteed extraction accuracy, explore our eBook about optimizing data extraction from bank statements.
This comprehensive resource provides valuable information on ensuring precision in the extraction process, showcasing Infrrd's commitment to excellence in AI-driven solutions.
What is the purpose of automating data extraction from bank statements?
Automating data extraction from bank statements serves as a strategic imperative for financial institutions, offering various advantages in streamlining banking procedures. The swift and accurate extraction of data from bank statements expedites crucial operations, such as bank statement processing, credit decisions, risk assessments, and customer verification. By leveraging advanced technologies to navigate the intricate details within bank statements, including transaction histories and account balances, automation significantly reduces processing times.
This automation not only accelerates the speed of financial transactions but also simplifies complex banking procedures. The intricacies of bank statements, once prone to manual handling, are efficiently managed through automated data extraction, minimizing the potential for errors. This heightened accuracy is particularly impactful in tasks such as credit assessments, where precise data is paramount. Moreover, the automation of data extraction enhances overall operational efficiency, ensuring more agile and responsive banking services.
Which industries often need bank statement extractor tools?
Industries relying on bank statement extractor tools, emphasizing extract bank statement and bank statement processing, include financial services, accounting, insurance, real estate, fintech, retail, government, and healthcare. These tools streamline account management, financial analysis, audits, risk assessments, transaction reconciliation, and various operational processes, ensuring efficiency and accuracy in diverse sectors.
Their versatility extends to aiding in precise financial analysis for financial services and facilitating streamlined audits in accounting. In insurance and real estate, these tools enhance risk evaluations and financial verification during transactions. Fintech platforms integrate them for seamless digital financial experiences, while retailers, government agencies, and healthcare organizations benefit from enhanced transaction reconciliation, compliance assessments, and record-keeping. Infrrd's Bank statement extractor solutions prove indispensable across various industries, contributing to smoother financial workflows and informed decision-making.
How is AI used by banks?
Banks harness the power of AI across various facets to optimize their operations and elevate customer services. This includes implementing customer service chatbots, fortifying fraud detection and risk assessment capabilities, and providing personalized financial advice.
From credit scoring to intricate investment analysis, AI's influence is pervasive. In the specific context of automating data extraction from bank statements, AI plays a pivotal role in revolutionizing lending decisions. Notably, Infrrd's recognition as the Best AI Software Company of 2021 by Digital.com attests to the industry's acknowledgment of our contribution to advancing AI solutions in the financial landscape.
How to improve bank statement data extraction with Infrrd?
To enhance bank statement data extraction with Infrrd, leverage their advanced technologies designed for precise data extraction from diverse financial documents. Infrrd's specialized solutions, focusing on extracting data from bank statements and bank statement extraction, employ cutting-edge AI and machine learning algorithms.
These technologies ensure accurate identification and extraction of key data points, such as transaction amounts and dates, streamlining the entire process for improved efficiency and reliability in managing financial information.
