Financial institutions deal with a lot of data from various sources like forms, emails, invoices, PDFs, etc. daily. Processing this unstructured data manually is time-consuming and requires a lot of effort. It can also be prone to errors, which can have costly consequences. This can take away from the time and energy that employees could be spending on more strategic tasks.
Automation technologies like IDP (Intelligent Document Processing), RPA (Robotic Process Automation), and OCR (Optical Character Recognition) can take manual document processing off your hands.
If you are wondering which one you should choose among IDP vs. RPA vs. OCR for the digital transformation of your financial institution, you are in the right place. Here we break down each banking automation technology to help you choose the best one.
What is RPA?
RPA is a technology that allows organizations to automate repetitive, routine tasks typically performed by humans. These tasks include data entry, document processing, customer service interactions, and back-office functions such as compliance, risk management, and accounting.
What is possible with RPA, and where does it fall short?
Banks are known to be heavily regulated, and compliance is a critical part of banking operations. This is where RPA can play a significant role by automating compliance-related tasks, such as KYC (Know Your Customer), AML (Anti Money Laundering), and other regulatory data management. It can also automate data migration, trade execution, data validation, data updates, and perform simple copy/paste functions.
However, RPA in banking automation also has some limitations. RPA requires a developer or GUI window to operate. Thus, RPA can only be used to automate simple screen-related tasks. It is limited to automating tasks that are highly structured and rule-based and is not suitable for tasks that require human judgment or decision-making.
Also, the entire automation process can break if there is an update in the user interface of a linked software. It is an outdated technology that relies on OCR and is not built for modern end-to-end integration.
What is Intelligent Document Processing (IDP)?
IDP is a next-generation technology designed to tackle the limitations of RPA. It is a system created to process documents just like humans. If you compare IDP with RPA for banking automation, you will find that IDP is the ideal combination of OCR, Artificial Intelligence (AI), machine learning, and natural language processing.
IDP is independent of strict rule-based approaches. Due to its flexibility, it can reach and process unstructured data not reachable via RPA. IDP tools also reduce the margin for errors by validating the data and informing the team in cases that need human intervention.
Here are some reasons why banks need Intelligent Document Processing.
How can IDP help in banking automation?
IDP can be a valuable tool in banking automation in several ways:
Account Opening
You can use IDP to automate extracting information from account opening forms and other related documents. It can reduce the effort and time required for manual data entry and improve the accuracy of the data.
Document Management
IDP can index, classify and route documents to the appropriate systems or individuals. Thanks to intelligent document processing, financial institutions can manage documents effectively and quickly retrieve the necessary information.
Compliance
IDP can help automate extracting information from compliance-related documents for processes such as KYC, AML, and other regulatory requirements. This way, banks can comply with regulations more quickly and efficiently while reducing the risk of non-compliance.
Loan Processing
IDP can enable the extraction of information from loan applications and other related documents such as income statements, credit reports, and real estate appraisals. It can help automate the loan review process, making it faster and more accurate.
Fraud Detection
IDP can be used to extract information from documents and match it with other sources to detect potential fraud. In this way, banks can reduce the risk of fraud and losses.
Read more: The Top Use Cases for Banking Automation
IDP vs RPA
The choice of automation for document processing boils down to IDP vs. RPA. RPA and IDP are two different technologies used in automation but are sometimes confused with the other.
The main difference between RPA and IDP is that RPA does not have the native intelligence of AI. RPA cannot consume and analyze data on its own. RPA is limited to mimicking repetitive actions performed on computer screens with a mouse and a keyboard. It is helpful for tasks that don’t require high-level decision-making and is largely outdated. It is often said that AI is ‘the brain’ while and RPA is ‘the hands.’
On the other hand, IDP takes automation up a notch by automating documents and absorbing and understanding data to extract actionable insights. Thus, IDP can be considered the future of banking automation.
RPA works better with structured documents (e.g. claim forms, tax forms ) where IDP works better with unstructured documents (e.g. contracts, handwritten notes). Ideally, an organization should use a combination of RPA and IDP to achieve better operational efficiency.
What is OCR?
OCR is a technology used in both RPA and IDP, that reads, extracts, and converts data from images and scanned documents into text for electronic automation and importation. When integrated with automation solutions like IDP or RPA, OCR can efficiently process structured data, eliminating the need for manual data entry and thus minimizing errors. OCR technology also enhances image quality to produce more accurate results.
While OCR is a step towards automation, it is not very effective in processing unstructured data that most banking institutions deal with every day in large volumes.
IDP vs RPA vs OCR
Blanc Labs’ Document Processing Solutions for Banks
Blanc Labs’ helps financial institutions like banks, and credit unions fast-track their way to digital transformation. We can help you integrate powerful automation technologies into your processes to increase productivity and reduce manual labor and the scope for errors.
Our team provides a customized combination of machine learning and artificial intelligence for automating complicated tasks like document processing so that you can save your resources and provide faster and better financial services.
If your financial institution deals with a ton of documents every day, let us help you put your processing on auto. Book a discovery call with us today, and we will create a seamless document processing solution unique to your needs.