Intelligent automation tools allow the people engaging in the day-to-day processes to build models that automate large portions of their jobs. This frees them up to work on more rewarding, strategic things. Here are some of the use cases that intelligent document processing can be used for.
Automate commercial debt document review: Financial service companies hold and issue commercial debt. This means they review documents to look over the interest rate index, economics of debt, debt maturity dates, and more. All of this detailed data can’t really be automated by IPA because there is so much intricacy involved.
However, intelligent document processing builds on existing AI technologies and builds models that are trained to identify and extract specific data from these kinds of debt documents.
Streamline financial document analysis: Financial firms rely on the data found in SEC earnings reports so that their analysts can offer more informed advice. They study quarterly 10-Q and annual 10-K to look for actionable data, pull it from the reports, and record it into various kinds of spreadsheets.
Effective intelligent document processing could take on this task instead, giving human employees more time to analyze the results that are found.
Know Your Customer requirements: Know Your Customer, also known as Know Your Client, is a regulation that requires banks and financial firms to understand key information about their client. This information includes their financial profile, risk tolerance, and anyone who may have the authority to do something for them on their behalf.
If the client is a corporation, the bank will need to know who the officers are, how much equity they hold, where the company’s operations are located, and more. Intelligent document processing can be used to help automate the collections process for all of this data, ultimately saving large amounts of time for an employee.
ISDA master agreement process automation: ISDA Master Agreements define the terms between parties involved in a transaction. To process these transactions, financial firms must review the ISDA documents that are a part of each trade.
The process is very long, and a standard ISDA document is 28 pages long and contains a bunch of variables from the transaction. It can take two hours or more just to process one document, and thousands of them are processed every year. Because of this, ISDA agreements could benefit from IPA and document processing.
Anti-money laundering compliance: KYC also factors into US financial regulations because banks and financial firms must comply when it comes to detecting money laundering. Compliance means that banks collect documents from clients so that they can prove they’re legit.
It also means that there is consistent monitoring for negative things that could lead to legal issues. Back in the day, these processes were manual, but today’s intelligent automation solutions allow financial services to automate large portions of their anti-money laundering programs.
Trade order confirmation automation: Financial services that are involved in trading understand how much time it takes for the confirmation process.
Now, many of them are looking into intelligent document processing so they can streamline their processes. Any trade with over-the-counter stocks, stocks traded by exchange, and others all require a settlement process and trade confirmation. These steps are important and show how the terms of the trade were executed so both parties can see whether the trade matched their price, quantity, and timing expectations.
Automate LIBOR loan updates: At the end of 2021, the LIBOR interest rate benchmark was retired, and many financial institutions are still trying to find all of their loans that reference it.
This is an incredibly time-consuming task because usually, it required a whole team of employees to read a bunch of unstructured documents in search of LIBOR-related terms. IDP could be used to boost efficiency in this area. An IDP model can search thousands of documents, extract LIBOR-related terms, and enter them into a downstream tool. Overall, automating this process would simplify the job of dealing with LIBOR.