AI-powered data extraction is a convenient way to capture the details of bank statements and export them in a usable format. When appropriately implemented, bank statement data extraction technology can provide an efficient, forward-facing and highly user-friendly way to capture financial data from PDFs or scans of bank statements.
However, before embarking on an automated data extraction project, there are a few things to consider. It's easy to begin meeting with IDP vendors without considering the intricacies of extracting data from bank statements. Therefore, we've compiled five things to consider, which should provide a good starting point for planning how to make a success out of your automation project.
Though automation is quicker and cheaper than a team of manual data extractors, planning a data extraction automation project takes dedication and patience. First, there's choosing an IDP vendor based on the quality of their proof of concept, then setting up their solution and training the staff on how to use it. Therefore, it's helpful to take a longitudinal approach - once put in place, how will bank statement extraction software help your company scale up?
Every reputable AI data extraction company should offer the highest data security, such as being ISO 27001 certified. However, some companies are required by law or regulation to maintain strict control over the bank statements they handle, meaning they're prohibited from sharing documents with an external provider. In such cases, SaaS solutions like Evolution AI will not be suitable for their needs, and an open-source solution may be more appropriate.
Financial institutions that rely on swift decision-making generally prioritise speed over impeccable accuracy. However, in the IDP industry, there's often a necessary compromise between the accuracy rate and the time taken to receive the data from the bank statement extraction. For example, you may want the extracted transactions from bank statements to be 99% accurate with instantaneous processing.
Alternatively, some business processes require a practically error-free experience. If this is the case, the time taken to extract from a bank statement will rise, at least initially. While it should be entirely feasible for the IDP vendor to guarantee 100% accuracy, achieving this level of accuracy may add additional quality-checking time to the bank statement extraction process.
So it's important to go into a demo meeting with clear expectations: would you rather have faster and slightly less accurate data or completely accurate and meticulously checked data?
It's good practice to explain to a potential IDP provider the importance of each data point on the bank statement you want to be extracted and how it fits into your business process. That way, it's faster to configure the technology and add any post-processing rules that you may require.
Explaining how your data is valuable in a wider context is also a great way to ensure that a potential IDP vendor understands your business needs and will dedicate appropriate resources to ensuring the most critical data is captured perfectly from bank statements.
Though some IDP vendors offer faster deployment than others, consider the integration timeline. Implementing an IDP-powered automated workflow solution involves several stages that must be completed before the desired go-live date. These stages include configuration and training, which may take a few weeks depending on the project's complexity.
Another factor to consider is the tempo of uploads. Do you plan to release bank statements in batches or continually throughout the day? Predicting your company's pattern of uploading documents reinforces the importance of IDP users knowing how quickly they require the extracted data.
Finally, at a fundamental level, it's important to consider the most appropriate integration method for your current company architecture. For example, you may opt for a REST API, a no-code solution (such as Workato), or a lightweight integration approach, such as uploading documents to your vendor via SFTP. Each integration approach will have its own requirements, so it's essential to consider which aligns best with your company's pre-existing IT architecture. If this is something that you're unsure of, an IDP provider should be able to advise.
For most IDP providers, training models on the information you need is significantly easier than adding it to the model later. Our Head of Operations, Alex Stoyanov, describes this process as 'overengineering the taxonomy'.
"Suppose I train the model to extract three data points from 1,000 bank statements," he explains. "If you realise later that you need another data point too, the model would have no prior examples to learn from, and the setup process will take significantly longer".
Another consideration is how you would like the data structured for downstream integration. What format should the bank statement data be in to be immediately useful? For example, would it be more convenient to extract data from a bank statement into a Excel or JSON format?
Many data extraction tools offer flexible output solutions, so it's helpful to initially take a long-term approach by thinking about how the data will be best delivered into the company's existing workflows and systems.
In summary, though preparing for a sales meeting or demo with an IDP vendor may seem arduous, it will pay dividends when setting up your bank statement extraction project. With the right IDP provider, data automation can be a low-stress, high-reward project that allows your company to scale up. Try Evolution AI's award-winning ai-based data extraction technology today - book your demo or email hello@evolution.ai
