5 Interesting Applications of Intelligent Data Extraction in Different Industries

What is intelligent data extraction, and how is it empowering businesses?

While traditional data extraction tools only automate the basic data entry process, intelligent data extraction software goes a step further to offer additional features, courtesy of the power of artificial intelligence.

These include document indexing, as a result of natural language processing and machine learning, among others.

Companies today are barely coping under the enormous weight of big data. Consequently, there is a rush to adopt intelligent data extraction systems to take the pressure off employees.

In the banking sector, intelligent Data Extraction is beefing up ATM verification processes, while in insurance, agents are relying on these systems to make faster and more accurate claim assessments.

And that doesn’t even cover half of the possibilities.

In this article, we’ll be discussing 5 interesting applications of intelligent data extraction in different industries, so you can get a couple of ideas for improving your business’s workflows.

Let’s get started.

1. Banking Industry

How can intelligent data extraction help banks improve document processing?

Workflows in the banking sector involve a tremendous amount of physical documentation each day.

So intelligent data extraction tools are necessary to minimize the amount of processing time bank officers spend on each customer.

By alleviating the need for manual data entry in loan forms and account opening forms, customers can be served faster, not to mention more accurately.

Intelligent data extraction facilitates faster loan processing by strategic bank statement analysis.

AI-powered OCR Software, in this case, is fitted with a couple of important search criteria to highlight from the statement including:

• Recurring income
• Defaulted payments
• Existing deductions

By filtering out important information from the statement, loan officers get a summary to quickly look through and make loan approval decisions.

Additionally, intelligent data extraction, and specifically, computer vision technology, also comes in handy when banks need to provide an additional layer of security at ATM vestibules.

In conjunction with facial recognition software, some banks in China are using computer vision software to offer a multi-layered authentication process.

After a successful facial scan, the software prompts input of the customer’s physical ID, which it reads to add his name to facial results.

2. Healthcare Sector

Healthcare is another document-intensive industry where paperwork drowns a health institution’s fundamental goals.

What’s more, the problem is compounded by the often unstructured nature of data found in most hospitals, which exists in image clips, handwritten medical records, and printed files.

As a result, many healthcare providers are using intelligent data extraction tools to lay the foundation for Electronic Health Records.

At Cleveland Clinic, EHR systems enabled the migration of patient data to digital formats and cloud storage media. This is made possible by a computer vision software bridge that performs the digitization of the files.

Non-resident physicians can, therefore, access patient history for diagnosis across the hospital’s branches.

But that’s not all intelligent data extraction does for the healthcare sector.

In addition to patient onboarding, medical billing outsourcing services can also be sped up through the intelligent collection of data.

Nurses typically add to a patient’s bill by manually taking down real-time data on the patient’s utilities and cumulative admission days. By the end of the process, the billing department has tons of paperwork to sift through to come up with a final amount.

To avoid that, these basic data entry chores are delegated to an automated data entry OCR software. These work in the same way barcode scanners do at grocery stores to process clients’ goods and quantify items used to the patient’s tab.

3. Insurance Providers

Did you know fraud costs the US insurance industry $40 billion annually?

Yes, that’s right, according to an insurance fraud report by the FBI.

Without proper data analytics, it becomes hard to identify figures that aren’t adding up, and general smoking guns. That’s because insurance agents handle dozens of claims in a day, each involving dizzying paper trails.

However, intelligent data extraction steps in to smoothen the process by speeding up the verification of claims and attached documents supporting the claim.

Fukoku Mutual Life is already using AI-powered data extraction to sort medical files.

The insurance company relies on ML software to filter details from attached medical files to better inform the accurate calculation of payouts. As a result, pay-out accuracies improved, as did staff productivity, which shot up by 30%.

Machine learning software takes in the associated data and analyses it much faster than an agent for a quicker settlement.

Thanks to deep learning facilitated by an in-depth training database, ML algorithms can pick out pricing discrepancies.

For example, if medical procedures do not match the average market pricing, intelligent data extraction systems flag this down as an anomaly. The claim consequently goes into review to be looked at by a human agent.

4. Ecommerce & Retail

I’m guessing the last time you bought an item from an e-commerce retailer, perhaps even your local store, you probably signed a proof-of-delivery (POD) form.

The modern-day retailer has taken the proof-of-delivery concept up a notch, complementing it with electronic proof.

When processing POD documents, an intelligent data extraction tool is the first line of the system. It scans the POD into an intelligent document processing platform for further analysis.

After which, the system automatically extracts the metadata containing the details of the recipient like:

• Paid amount
• Customer name
• Delivery time and date
• Product condition

The overall transportation management system receives all this information, which becomes available to the company’s branches for future reference.

As an example, NFT Distribution Operations Ltd has implemented intelligent data extraction to automate the processing of over 100,000 PODs every week.

The food and beverage giant was able to handle a large volume of PODs, by relying on intelligent data extraction tools to scan client’s metadata, thus saving the company more than £100,000.

5. Legal Industry

How can lawyers use intelligent data extraction for better case handling?

For lawyers, paperwork is a part of the day-to-day work at the office. That not only includes the actual case files, but also the reference material to establish precedence, among others required for the preparation.

To ease paperwork stress, some law firms have turned to intelligent data extraction software to scan voluminous legal documents.

Via Intelligent Document Processing Software, paralegals can find what they need in contracts or files by highlighting search criteria.

Machine learning algorithms point out case-relevant files, and further use this as a reference for finding similar files.

What’s more, the searchability of documents is enhanced thanks to comprehensive document classification features, which employ natural language processing to pick and place files in appropriate digital archives.

Clifford Chance is already benefiting from the legal convenience of intelligent document processing. The law firm has been able to improve case reviews and contract analysis as a result.

Intelligent data extraction tools enable Clifford Chance lawyers to find clauses detrimental to their clients and guide better negotiation for new terms.

Conclusion

Is big data holding your business back?

Intelligent data extraction could lower the burden of your information-heavy workflows, as we’ve seen in these 5 interesting applications of intelligent data extraction in different industries.

Law firms like Clifford Chance have improved productivity immensely as a result of intelligent data extraction. Meanwhile, banks in China are adding to the security of ATM withdrawals and are also benefiting from faster loan processing rates.

Additionally, retail stores are speeding up the proof of delivery process, while the healthcare sector and EHR systems are only possible as a result.

So what can intelligent data extraction do for your business?

It can fast-track your Digital Transformation and automate data entry tasks to give core business functions more attention.

About Adlib Software:

Adlib unlocks insights hidden within unstructured data to accelerate digital transformation. Our purpose is to create intelligent data that amplifies human potential and maximizes business performance. How do we get there? Our content intelligence and automation solutions make it easy to discover, standardize, classify, extract, and leverage clean structured data from complex unstructured documents. In doing so, our global customers reduce risk, simplify compliance, automate processes, and enter a whole new level of performance. Adlib’s AI powered Contract Analytics platform elevates unstructured data into business intelligence: