Anyone with a good understanding of the banking industry knows the crucial importance of data entry and data extraction for financial institutions.

Precisely with data entry, financial organizations can keep all relevant information in one place so that it is available quickly and efficiently. In this way, these institutions can create bank statements, loan agreements, credit and debit reports, etc.

However, all those who have had to work in the banking sector are also aware of the inconvenience and difficulty that data extraction, an important but repetitive task, can cause.

And it is very likely that they know it first-hand since this is a task that almost every bank worker has had to deal with at some point in their career.

And what happens when tedious and unwanted duties collide? Increases the probability of human error.

This has posed a serious problem for the financial sector, as data entry and extraction is a major operation. Therefore, the industry has been trying to find a perfect solution that minimizes human error and takes the stress out of work.

Challenges of manual data entry and extraction:

• Repetitive and demotivating – because extracting data is repetitive and generally not very interesting work, it can lead to bad working habits such as distractions, keyboard shortcuts mistakes and typos.
• High probability of inaccuracy – due to the high number of documents that have to be handled each day, this work requires strict adherence to the rules and protocols that govern it. This often leads to data entry errors can lead to significant financial problems and reputational damage if they are not detected in time.
• Costly – because the data entry process takes time, financial organizations have had to hire additional staff. As a result, they have increased their operating costs and limited themselves in terms of investment opportunities.
• Time-consuming – not only does this task take a long time, but it usually requires the help of more than one person. And when you factor in all these constraints, the need for a rapid and precise extraction tool is obvious.

AI as the perfect answer to financial data management

The fact that automation can help increase a company’s productivity is no longer news.

However, automating tasks with an intelligent system that does not require human intervention but can mimic and even surpass human performance is what has revolutionized companies today.

Exactly with the help of subsets of AI – Optical character recognition (OCR); Deep Learning and computer vision –  financial companies can address the problem of manual data handling.

Before we get to how it’s done, let’s define all these subsets:

• OCR – A technology that recognizes and transforms text from digital documents, such as photos, into machine-readable text data.
• Deep learning – A subset of AI motivated by the human brain that mimics it with artificial neural networks to solve complex problems with large amounts of data.
• Computer Vision – a field that deals with the way computers see and understand images and videos. Computer vision includes OCR but also incorporates additional features such as facial recognition.

Now that we know what each of them represents, let’s look at the detailed process of how these technologies address the challenge of data extraction.

1. The first step for the AI-powered machine to work efficiently is to provide it with the necessary data of texts, letters, figures, numbers, etc. This creates a kind of character dictionary for the system that is later used as a reference.
   
2. For the next step, the desired document is uploaded to the system and the system tries to identify the characters that are present in the file. This is done by analyzing each symbol for its characteristics, such as curves, corners as well as other details and referencing it with the system´s database.
   
3. In addition to the symbol dictionary, the system also understands words as a whole. Therefore, if some letters are difficult to identify, the OCR system checks its dictionary of words to find the closest match.
   
4. The intelligent system can also identify the type of document (financial statement, invoices, annual reports, etc.) and customize its information extraction process, increasing the precision of the extracted data.

What are the results and benefits of this process? 

• Increased document processing capacity – The process we mentioned above takes several seconds for a good AI-powered system. Imagine the number of documents that you can digitize and extract data from in a matter of minutes.
  
• Happier employees – Employee satisfaction became one of the main objectives of businesses since it is directly related to the performance of the company. Freeing your staff from uninteresting tasks and giving them meaningful work will benefit your entire organization.
  
• Greater precision in data extraction – Automating the data extraction process eliminates human error and provides greater accuracy for businesses.
  
• Cost reduction – Financial companies are one of the leading organizations engaged in document handling.  The costs associated with the artificial intelligence system and automated document data extraction are justified and more profitable in the long run.

Conclusion

The financial sector should pay more attention to recent innovations in the industry, as they can be a turning point in terms of gaining a competitive advantage.

One of the most important innovations is the inclusion of AI to streamline and optimize various operations such as data entry and extraction. 

The use of artificial intelligence in a banking context can make a significant difference by allowing accurate and fast data extraction without the need for additional staff.

This technology also allows users to extract only the required information from documents, saving time that would otherwise be spent sifting through large amounts of data. And ultimately, the incorporation of AI into this industry will

And while it may seem like a big compromise, in reality, it could prove to be a cheaper solution that makes the document data extraction process more accurate, faster, and can free up your staff from uninteresting labor.