Automate Finance Documents: Challenges and Solutions

Ashutosh Saitwal
Ashutosh Saitwal

Founder CEO - KlearStack AI

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[vc_row pix_particles_check=””][vc_column][vc_column_text]The finance sector is one of those where the dependence and importance of documents and data is immense. Therefore, it is very commonly suggested by experts to implement strategies to automate finance documents for seamless operation.EY estimates that financial automation may reduce data input expenses by up to 70 percent.

Finance departments have to deal with a vast amount of documents on a daily basis, including invoices, receipts, purchase orders, financial statements, tax filings, and more. These documents require manual data entry and processing, which can be time-consuming, error-prone, and hinder efficiency. In this blog post, we’ll explore the challenges in extracting data from finance documents, how to automate finance documents, and the advantages of automating financial documents with KlearStack AI.

Different Types of Finance Documents

Before we delve into how to automate finance documents, it’s important to understand the different types of finance documents. Some common types of finance documents include:

  1. Invoices: Invoices are used to request payment for goods or services provided.
  2. Receipts: Receipts are used to confirm payment for goods or services provided.
  3. Purchase orders: Purchase orders are used to request goods or services from a supplier.
  4. Financial statements: Financial statements provide an overview of a company’s financial performance.
  5. Tax filings: Tax filings are used to report a company’s income and expenses to the relevant tax authorities.

Challenges in Extracting Data from Finance Documents

Extracting data from finance documents can be challenging due to several factors, including:

Multiple formats:

Finance documents can come in multiple formats, such as PDF, Excel, and Word, which can make data extraction difficult.

Data variability:

The data on finance documents can be highly variable, which can make it challenging to extract accurate and consistent data.

Handwritten Documents:

Some finance documents may contain handwriting or the entire document in handwritten, which can be difficult to read and extract.

Language barriers:

Some finance documents may be in languages other than English, which can make data extraction challenging.

How to Automate Finance Documents

1.Identify the documents that need to be automated: Determine which financial documents are repetitive and time-consuming to process, such as invoices, receipts, bank statements, and purchase orders.

2.Choose the automation technology: Select the automation technology that best suits your needs. This could be OCR software, NLP algorithms, ML models, RPA bots, or blockchain solutions.

3.Collect and digitize the documents: Gather the documents and digitize them using scanners or cameras. Ensure that the images are of high quality and that the text is legible.

4.Preprocess the documents: Preprocess the documents to remove noise, correct orientation, and enhance contrast. This will improve the accuracy of the automation technology.

5.Train the automation models: Train the OCR, NLP, and ML models on a large dataset of financial documents. This will help the models learn to recognize patterns and extract information accurately.

6.Implement the automation solution: Implement the automation solution by integrating it with your existing systems and workflows. This may involve developing custom software or configuring off-the-shelf solutions.

7.Monitor and refine the automation: Monitor the automation solution to ensure that it is performing as expected. Refine the models and algorithms as needed to improve accuracy and efficiency.

Different Techniques Used for financial Document Automation

Optical Character Recognition (OCR):

OCR technology is used to extract text from financial documents such as invoices, receipts, and bank statements. The text can then be processed by software to automate tasks such as data entry, document categorization, and data validation.

Natural Language Processing (NLP):

NLP technology is used to analyze the text in financial documents and extract meaningful information. This can include identifying entities such as names, dates, and amounts, as well as analyzing the sentiment and tone of the text.

Machine Learning (ML):

Machine learning algorithms can be trained on large datasets of financial documents to automate tasks such as classification, prediction, and anomaly detection. For example, ML can be used to classify invoices based on their content, predict the likelihood of a customer defaulting on a payment, or detect fraudulent transactions.

Robotic Process Automation (RPA):

RPA involves using software robots to automate repetitive tasks such as data entry, document processing, and report generation. RPA can be used to automate tasks across multiple systems and applications, reducing the need for manual intervention.


Blockchain technology can be used to automate financial transactions, reducing the need for intermediaries and increasing transparency and security. Blockchain can also be used to automate tasks such as smart contract execution, invoice validation, and payment processing.

Advantages Of Automating Financial Documents

1. Increased efficiency:

Automated finance document processing eliminates the need for manual data entry, saving time and increasing efficiency.

2. Reduced errors:

Manual data entry can result in errors that can be costly to fix. Automated fianance documents reduces the risk of errors and ensures data accuracy.

3. Improved compliance:

Automated document processing ensures that all financial documents are accurately processed and stored in compliance with regulatory requirements.

4. Cost savings:

Automating document processing reduces the need for manual labor, resulting in cost savings.

Automating Finance Documents with KlearStack AI

KlearStack AI is an intelligent document processing platform that automates the extraction of data from finance documents accurately and efficiently. KlearStack AI can extract data from invoices, receipts, and financial statements, including handwritten text and multiple languages. Its advanced OCR technology recognizes and extracts data accurately, reducing manual errors and increasing efficiency.

Manage Compliance issues

Financial document generation and data reporting is all about utilizing the available, unstructured, raw financial data and formalizing it to present a detailed report. While it may sound like a routine task that commonly occurs in every kind of business, the fact that financial document creation is governed by several compliances and standards makes it completely different.

Handling of financial data and creating new finance documents has to be done while protecting customer investment details, mitigating the risks of fraud, and limiting all kinds of risks. Onboarding new clients in a finance setup involves conducting thorough background checks and collecting all relevant information about the client. While this preparation is crucial to establish cash flow from any new customer, the phase is governed by several standards and compliances.

When verifying the details of any new prospective client, strictly sticking to regulatory guidelines is an important thing to consider. Errors while doing so are fairly common, which have resulted in losses worth millions across the globe already.

Automate Finance documents with KlearStack to solve this problem completely. By designing custom models for creating templates for the generation of specific financial documents, KlearStack can ensure that every step is followed as prescribed by the regulatory guidelines.

The use of machine learning in our AI-based OCR tool also helps us recognize any missing components or mismatched data elements in the financial documents. This is an important aspect for tapping any possible financial fraud in its early stages itself.

Different Documents For Different Departments

Finance agencies have to deal with several different government authorities. All of these involve paperwork with very specific and separate regulatory guidelines as well. If you do not plan to invest enough to automate finance documents as per the requirements laid down by every such department, then think twice.

Manually creating documents for submission in different offices takes ages to complete. Further, missing out on some components or including unnecessary elements in the documentation is a common occurrence. What you need is a smart automation solution that not only creates finance documents on its own but also recognizes the structure of documents needed for a particular government agency.

KlearStack, with its all-encompassing machine learning models , enables exactly that. Once the model is trained to automate the generation of a document with a fixed template, it will remember it forever. Whenever the need arises subsequently, generating a fully compliant document will only take a few seconds to complete.

Insightful Reporting

Regulatory bodies, the board of directors, and the customer base. All three main stakeholders in the operations involved in the finance sector require different types of data reporting. Further, for the report to be more meaningful, all stakeholders expect that the visualization of important metrics is up to the mark.

Further, it is also expected that the interpretation and insights extracted from every piece of data reported is also put across clearly. KlearStack, with it’s AI-based OCR solution, extracts and digitizes text from raw data sets obtained during fieldwork. More importantly, it also uses artificial intelligence to derive actionable insights automatically. The generated digitized data is easy to visualize with business intelligence tools, that finally makes the reporting job much easier than before.

Learn how KlearStack had helped banks with end-to-end financial document automation. Download the case study here >>Digitizing Banks Through Smart Document Automation


Automating financial documents offers several benefits, including increased efficiency, reduced errors, improved compliance, and cost savings. By automating financial documents with KlearStack AI, finance departments can streamline their document processing, saving time and increasing efficiency while reducing the risk of errors.

To learn more about how KlearStack can help automate financial documents processing in your organization, book a demo with our experts today![/vc_column_text][/vc_column][/vc_row]

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