Insight
Hey ChatGPT, write a blog post about AI, document processing, and private market workflows
Streamlining private market workflows with intelligent document processing
There are detail-oriented tasks that are enjoyable, like cooking, solving a puzzle, correcting someone’s grammar. And there are detail-oriented tasks that are not, like taxes, putting together an IKEA desk, or...taxes.
Falling firmly into the “not fun” category for institutional investors is document processing. No matter how important it is that all of the data is copied correctly, there’s just no wow factor to this painfully mundane and repetitive process.
Yet the need for clean and accurate data is not going to diminish anytime soon. Data integrity is an essential ingredient for sound investment decisions. Alternative investors must pull highly specific datapoints from a vast amount of PDFs, increasing the need for an automated data extraction and data organization tool.
Intelligent document processing is your golden ticket to streamlining this workflow. It reduces the amount of time spent on manual reporting and dealing with mixed data formats. As a result, your team can focus more of their attention towards making strategic investment decisions. Plus, it increases mental sanity as you no longer have to do the same thing over. And over. And over again.
Intelligent document processing (IDP) is an AI-based process that organizes information from any unstructured source into structured, readily-accessible, validated data. In other words, it can quickly and accurately identify key pieces of information from a document or set of documents. By utilizing this technology, institutional investors are able to quickly analyze large volumes of data in order to make informed investment decisions.
The main benefit of document processing for investment data is that it cuts down the amount of time spent on manual reporting and dealing with mixed data formats. It also helps to reduce errors, as the technology is able to identify inconsistencies or incomplete information quickly and accurately.
Let’s start by understanding what it is not. IDP is not CMD/CTRL + F. It’s also not the same as searching a keyword in your inbox or any sort of database. The job of the computer in the “search” use case is to find exact matches for the term you provided. If you misspell something, or use the wrong keyword, the search will be unsuccessful. This is not IDP.
Intelligent document processing is more intelligent than CMD+F for a variety of reasons, but let’s focus on three.
While OCR assists with extraction and digitization, NLP and ML solve the mapping problem. Written language, tables, and numbers need to be combined and organized appropriately—in other words, the text needs to be given meaning. If OCR extracts the phrase “The Return of Fund 1 for Q1 2023 is 7%,” the NLP and ML process recognizes that “Q1 2022” is a reference date, “Fund 1” is the relevant fund, and “7%” is the return. The combined use of OCR, NLP, and ML produce a powerful intelligent document processing tool.
IDP can be used to process a variety of private market investment documents, including cash flow notices, capital account statements, and quarterly financial statements. This provides your team with consistent and timely access to crucial intelligence at the company, fund, and portfolio level.
With a clean foundational dataset, your team can confidently consider analytics for performance, liquidity analysis, cashflow forecasting, exposure management, and portfolio company detail.
One of the main challenges associated with intelligent document processing for alternative investments is that the technology is still relatively new, and there are a limited number of vendors offering solutions. This makes it difficult to find a solution that meets the specific needs of each investor. Additionally, there are still some issues with accuracy when it comes to extracting information from complex documents (but remember, if the algorithm is properly set up, it has the capacity to “learn”).
However, these obstacles can be overcome by working with experienced document processing vendors who have the knowledge and expertise necessary to develop solutions that are tailored to each investor’s unique needs. Additionally, investing in quality datasets and training algorithms can help improve accuracy when dealing with complex documents. By addressing these concerns, institutional investors can ensure that they get the most out of their document processing solutions.
If you live under a rock, you may not have heard about OpenAI’s launch of ChatGPT. If you manage to explore the currently free service when it’s not at capacity, you’ll see it can perform a variety of stunts such as: summarize the life of Abraham Lincoln, rattle off the recipe for dairy free Mac ‘n’ Cheese, debug your code, write your final term paper, or produce a heartfelt letter to your grandma.
AI even wrote the first draft of this blog post (in case you’re getting freaked out, this section was all us). We of course enriched, refined, and added some flair, but it did indeed save time with content production. Rather than taking the “AI is coming for us” approach, consider how AI can save time on the more mundane day-to-day tasks—leaving the most intellectually stimulating tasks for the humans.
If you’re interested in incorporating the benefits of IDP into your team’s workflows, we’d love to show you what this looks like with SEI Novus.
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SEI Novus is not an investment advisor, broker dealer, or financial institution and does not offer or provide advice regarding analysis of securities or effecting transactions in securities. SEI Novus does not endorse or promote any mentioned investment management firm or any fund managed by any such firm. The purpose of the information herein is to demonstrate the capabilities of the SEI Novus Platform.