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Unleashing Cash Flow Potential through Invoice Data Extraction 

Ammar Ali

Content Manager

February 22nd, 2024

Within the dynamic landscape of financial services, businesses are constantly seeking new ways to improve cash flow and stay ahead of the competition. One area that holds significant potential is automated invoice data extraction.  

By leveraging cutting-edge technology, financial service providers can streamline their invoicing processes, reduce errors and delays, and ultimately optimize their cash flow potential.  

What is Cash Flow Management and Why is It Important? 

Cash flow refers to the consistent inflow and outflow of money within a financial service business, which is of utmost importance for its survival. Numerous profitable financial service businesses risk closure because they don’t have sufficient cash to meet their financial obligations when they become due.  

Positive cash flow fuels growth, help organizations meet obligations, and empowers strategic maneuvering. When it comes to optimizing cash flow, automating extraction of invoice data is indispensable to receiving accurate and timely financial data. 

How Efficient Invoice Processing Bolster Cash Flow 

Automating and streamlining the invoicing process allows financial service businesses to monitor and track outstanding payments more effectively. By promptly following up on overdue invoices, accounts payable (AP) departments can take the necessary steps to arrange for funds. This may involve contacting clients to inquire about their payment status, negotiating better payment terms, or availing early payment discounts.  

By staying on top of outstanding payments, financial service businesses can better manage their cash flow and make informed decisions regarding their financial commitments and expenditures. Timely invoice processing also enhances transparency and communication between the business and its clients, reducing the likelihood of payment delays or disputes.  

Ultimately, by prioritizing effective invoice processing, businesses can cultivate a stronger financial foundation and ensure a steady cash flow to support their operations and growth. 

How Much of a Difference Can an Invoice Data Extraction Tool Make? 

An invoice data extraction tool substantially reduces invoice processing time, paving the way for cost savings and enhanced vendor partnerships. On average, automated data extraction empowers the finance team to process invoices roughly 10 times faster.  

In other words, if a finance department was processing just 50 invoices per employee each week, data extraction automation can make that number jump to 500 invoices. And we’re just talking averages here. One of our clients, a consumer finance company, successfully reduced invoice processing time from 25.5 days to a mere 24 hours. That’s more than 24 times faster! 

Another client, a mortgage lender, successfully downscaled their document processing department from 25 employees to 15 employees in the first year and further to just three employees in the second year. Meanwhile, they achieved a remarkable eightfold improvement in invoice processing efficiency. This efficiency not only provides cost benefits but also streamlines the invoice approval and payment process, guaranteeing timely payments to vendors or suppliers.  

Consequently, businesses avoid late payment fees, cultivate positive vendor relationships, and position themselves for improved negotiation opportunities. 

The Potential Cost Savings 

Suppose a financial service company receives 4,000 invoices from 30 different vendors every month, each with a different structure and layout. Oftentimes, even invoices from a single supplier vary in format. Processing these invoices manually can be a time-consuming, error-prone, and labor-intensive activity, but with automation, not so much! In fact, it’s the other way around. 

Automating data extraction can significantly accelerate invoice processing, eliminate human errors, and streamline payment processing. Not to mention the cost savings that financial service companies can derive using automated data extraction.  

For example, an average employee can process five invoices in an hour, which translates to 40 in a day or 800 monthly. This means the financial service company must dedicate five full-time employees to process invoices. Given the average salary for an invoice processor in the US is $39,523 per year, the company would save $197,615 annually by automating this process.  

Final Word 

Automated invoice processing can greatly improve the cash flow of a financial service company. By implementing automation, invoice data becomes more precise, comprehensive, and easily accessible, which ultimately optimizes the cash flow of your business. Additionally, the enhanced visibility and usability of data simplifies the auditing process. 

Astera ReportMiner—The Ultimate Automated Data Extraction Tool  

Astera ReportMiner is our state-of-the-art data extraction automation solution, now powered by the advanced NLP algorithm, Astera North Star.  

Our tool revolutionizes invoice processing, enabling the rapid extraction of data from diverse invoices within minutes with minimal manual intervention. Imagine being able to process 100 different invoices in minutes. With ReportMiner, this level of efficiency is routine.  

Moreover, our code-free solution goes beyond automating data extraction; it also comes with an automated data verification feature. You can define custom data quality rules to guarantee the utmost accuracy of the data extracted from invoices 

Additionally, ReportMiner enables the seamless integration of invoice data into automated data pipelines to enable end-to-end automation. Our tool is compatible with AP automation solutions, facilitating efficient payment processing as well as seamless reporting and analytics. 

Do you want to learn more about how to automate invoice processing with Astera ReportMiner and ensure your cash flow statements stay green? Check out this free eBook:

Astera’s Guide to Insurance Data Quality and Governance
Information Governance vs. Data Governance: A Comparative Analysis
Data Quality Framework: What It Is and How to Implement It
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