Manual data entry is a tedious and time-consuming task that requires not only time but also resources. Expensive resources that guarantee no error-free results. Inefficiencies, regulatory risks, and slowing down innovation are some elements characterizing this process. While this way of doing business was once the only option, we’re glad it’s not anymore.
With the advent of technology, new ways of doing business have emerged. Nowadays, everyone is switching to digitization, especially in industries that require efficiency. Industries like fintech. Companies automate their operations to boost productivity, reduce errors, and stay ahead of the competition. How can you do that? With AI-powered OCR!
But what is OCR, and how do you choose the right OCR solution for your business? More importantly, how can it benefit the fintech industry? In this blog, we’ll explore these questions and dive deeper into the role of OCR in fintech.
Let’s get started!
What is AI-powered OCR?
OCR is the abbreviation for Optical Character Recognition. A technology that identifies the targeted text from a wide range of documents, extracts it and converts it into a searchable and readable computer format.
Here’s an example to get a better idea of how OCR works. Let’s say you need to process an ID document. The first step to take would be to scan it and save the scanned image in your computer as an image file. In this format, you can’t edit or search the document. That’s where OCR comes in. If you use it you’ll convert the scanned image into a text document, and all information will be stored as text data.
Whether it’s a PDF, a scanned document or a low-quality image, OCR tools are capable of extracting text and converting it into valuable digital data.
OCR technology is still a work-in-progress tool which means that the more time you dedicate to training it, the better possible results you’ll get. How do you achieve this? By feeding it a lot of data, text recognition will be improved in terms of accuracy and document coverage.
The Hidden Costs of Manual Data Entry in Fintech
Manual data entry is a common practice in many companies, but it comes with a bunch of challenges that influence negatively productivity, efficiency, and accuracy. Human input seems like a straightforward task but it leads to significant disadvantages. Below, we’ll highlight some of them:
Prone to errors
Manual tasks rely on human intervention which can often make mistakes. Inaccurate information is a result of mistakes that happen in the starting phase of data entry and can lead to wrong decisions and financial losses.
Time-consuming
Inputting data one by one is a tedious process that takes a lot of time. It can slow down your business’s operation, lower productivity, and increase frustration.
Labor costs
Manual data entry requires human resources which leads to higher labor costs. Employees require salary and benefits, making manual data entry a costly option, especially when companies grow and their data increases.
Employee burnout
Repetitive tasks such as data entry can damage mental health. Research has shown that when someone engages in monotonous and repetitive tasks is more likely to experience high levels of stress and consequently burnout.
Benefits of AI-Powered OCR for Fintech
OCR has proven itself to be a game changer, helping businesses in different sectors and industries become more efficient and accurate, intending to improve their overall performance. Fintech is not an exception. Here are some of the key benefits of OCR for fintech companies:
Enhanced efficiency
Manual traditional methods are time-consuming, and so is manual data entry. A very important step of document processing. OCR automates this process for financial documents such as receipts, bank statements, and invoices, reducing manual tasks and speeding up financial activities.
Cost reduction
Human resources are required when companies decide to use manual methods for data processing. By leveraging OCR tools, businesses reduce labor costs, allocating funds to vital strategic activities.
Improved data accuracy
High accuracy is OCR’s most important feature, since it reduces manual errors in data entry, ensuring accurate and trustworthy financial data. This results in better regulatory compliance and reliable financial reporting, two crucial aspects in the finance industry.
Fraud prevention
With OCR discrepancies are easily detectable during audits and expense reporting. Suspicious activities are also more likely to be detected due to the improved real-time monitoring.
Streamlined customer onboarding
OCR allows document processing and verification to be faster, due to quick and easy access to data. This reduces waiting times, resulting in overall customer satisfaction.
Real-Life Applications in Fintech
Fintech tries to make financial services more inclusive, efficient, and personalized for all people. OCR can help fintech in a wide range of use cases. Let’s take a look at some of them:
Mobile Payments
Transactions and instant payments can now be made via smartphones, through apps like Apple Pay and Google Pay. These processes are both fast and secure, ensuring a better customer experience.
Digital Banking
Banking services such as checking accounts, premium saving accounts or secured credit cards are now available without the traditional fees, making financial activities accessible to everyone.
Investment Platforms
Investment platforms make investing more accessible to ordinary people, as they usually offer low or even no commission.
Peer-to-Peer Lending
Borrowers can connect more easily with lenders for microloans through platforms such as Prosper Marketplace and LendingClub.
Personal Financial Management
Financial management apps offer users personalized financial advice, which, then, results in saving money and managing budgets more efficiently.
Choosing the Right OCR Solution for Your Business
Have you decided to embrace automation and elevate your business’s performance? That’s great! Now it’s time to choose which OCR tool is best for you. Selecting the right tool is crucial since it has a direct impact on your company’s business outcomes. Below, we highlight some of the most important features an OCR tool should have:
Text recognition accuracy
Identifying and converting text is the main OCR feature. When choosing an OCR tool take into account whether it utilizes machine learning to enhance recognition accuracy and character recognition techniques for accurate character identification.
Easy to use
Choose an OCR tool that has a user-friendly interface, allowing employees to use it without getting extensive training.
Compatibility
Ensure the OCR tool you choose incorporates APIs and SDKs. This will guarantee compatibility and enable seamless integration with your existing systems.
Document processing capabilities
When searching for an OCR tool, you need to take into account specific features like language support, document formats, document quantity and low-quality images. These features will support your operational requirements and enhance your overall document management process.
Security and Compliance
Data security is really important especially when dealing with sensitive information. Selecting an OCR tool that offers security features such as encryption and secure data storage, ensures both compliance with regulations while protecting your data.
Conclusion
While not everyone has yet embraced automation processes, OCR use is growing as businesses realize its countless benefits. Operational efficiency, accuracy, and cost-effectiveness are just a few of them.
If you’re ready to embrace automation and integrate OCR into your daily business operations, selecting the right OCR tool should be your next step. Although selecting an OCR tool seems easy and simple, it’s important to carefully include all the key features that best fit your needs.