There are a number of reasons why banks may want to extract data from documents. Whether it’s for fraud prevention, compliance with regulations, or just to have more information for marketing purposes, extracting data is now an essential part of the banking industry.

Many banks are turning to solutions that automate this process. This frees up time and resources so that staff can focus on other tasks. Automated document extraction also reduces the risk of costly mistakes due to manual data extraction. But before you start automating your document extraction process, here are some things you’ll want to know!

Why banks extract data from documents

Banks and credit unions may want to extract data from documents for a number of reasons. Some banks might be required to do so by law. For example, banks in the United States may be required to extract customer’s social security numbers in order to comply with the Patriot Act.

Other banks might want to extract data in order to detect fraud or comply with regulations. For example, if your bank is doing business internationally, it may need to extract certain information in order to abide by international banking regulations.

Banks may also use document extraction software for marketing purposes. For example, they might run text mining on expense reports for keywords related to products or services they offer. This can help them make advertising decisions which are more targeted towards specific groups of customers.

The benefits of extracting data from documents

As banks, we know how important it is to protect our customers’ data. Extraction of data from documents is a process that helps us do just that. Extracting data from documents can be done for many reasons. For example, extracting data can help reduce the risk of fraud due to forged signatures or other fraudulent activity. The benefits go beyond protecting your customers’ information, though!

Automated document extraction has many advantages. It frees up bank staff’s time so they can focus on other tasks that are more critical to the operation of the bank—something that’s especially helpful for smaller banks. Automated document extraction also decreases the risk of costly mistakes caused by manual extraction of data from documents, which could happen if an employee was rushed or missed important details.

But before you start automating this process, here are some things you’ll want to know!

The challenges of extracting data from documents

Data extraction is one of the most time-consuming tasks within a bank. Every document has to be looked at and carefully analyzed to see if it’s necessary for the task or not. The process can take hours or even days depending on how many documents there are and how much data needs to be extracted from each one.

This can lead to mistakes, which can result in costly lawsuits.

Additionally, document extraction is very monotonous and doesn’t require the skills that many bankers hold. Large banks often find themselves having to employ people who can do this work, rather than relying solely on staff members who would rather put their skills elsewhere.

With all these problems, banking institutions should consider investing in automated document extraction solutions. Let’s take a look at why!

What to consider before automating document extraction

First, you’ll need to assess how much data extraction is currently taking place in your organization. This will help you figure out whether the process should be outsourced or automated.

The next step is to determine which method of document extraction you want to use: manual or automated. Manual methods include human operators reading and typing information from documents while automated methods involve extracting text by using optical character recognition (OCR) software and databases that store previously-extracted data. Recent advances in Natural Language Processing (NLP) provide novel solutions to data extraction of very high quality.

Finally, it’s time to automate documents with a system that works best for your specific needs. You’ll need to find a system that can extract data from various formats, such as unstructured documents, PDFs, and scanned forms.

The D2 platform from DeepDatum.ai allows organizations to define data elements that need to be extracted, which is then used to build NLP based models which extracts high precision data from documents and images.

Conclusion

Extracting data from documents is an important part of keeping up with the latest technology as well as making sure your bank is as secure as possible. Luckily, it’s not too complicated to do and it doesn’t take a lot of time at all. The key is to understand how and why you need to extract data from documents and then choose the right software that will do the job for you.