6 steps to build an automated annual report data extraction process05 February 2021
No investment research is complete without reading annual reports.
Many investment firms are chasing a vicious cycle in automating data extraction from annual
Problem #1 is complexity.
Annual reports come in 1000s of templates. These templates vary in structural aspects such as design, layout, and text formats, and they may contain highly complex inter-dependent tables.
The technologies such as RPA or OCR fail miserably to extract the vital data confined in these long complex documents, requiring human-like comprehension.
Automation without contextual understanding generates inaccuracy and inefficiency. Even a minor error might lead to a business loss or wrong investment call.
No matter how many rules are applied, they fail to augment humans in capturing data based on the context. Annual reports vary and for a rule-based process to work, they should either stay consistent in their format or change by a pre-determined amount.
Let’s go ahead and see how Botminds can help you to solve those challenges and extract data from those complex annual reports in a few minutes.
Step 1: Upload – Estimated time – 2 mins
Upload the Annual Reports in the Botminds platform from which you would like to extract the information. The source of documents could be cloud storage, local disk, web, or even directly from the SEC.
Step 2: Taxonomy definition – 5 mins
Define the data points that you want Botminds to read and understand and also arrange them a structure that you would like to see the final output. We call them “taxonomy”.
The taxonomy can also have multiple level hierarchical structures. For example, you can build a hierarchial taxonomy like Financial Information –> Income Statement –> Sales.
Step 3: Training – 120 mins
For the document uploaded, using the generated taxonomy, start annotating the values just by point and click. Replicate the same old manual reading and understanding of annual reports but within Botminds.
Every activity made inside our platform is captured by Botminds as a “learning”.
Step 4: AI Model Generation – 5 mins
Now, the training phase has been completed successfully. The next step is to create an AI model that comprises all of your training data. An AI model is the critical component that mimics the human-intelligence. The effectiveness of an AI model is determined by the quality of training.
A high-quality training by an SME usually scores 80% accuracy within the first few days. Iteratively, the model gets improved day by day and reaches almost 100% accuracy in no time.
Unlike any other automation solutions, creating an AI model requires no coding in Botminds. All you need is a single click to stitch the humungous training data into an AI model.
Step 5: AI Model in action – 2 mins
Once the model generation is over, it’s time to see the Botminds in action by uploading a new annual report. Once you upload a new annual report, like magic, Botminds will have all the essential data extracted as a summary without losing the context.
All the values extracted are deep-linked with the source. The moment an extracted value gets clicked, it leads us to the exact location of the source for a side by side quick validation.
The business user can simply approve, or correct the values(in case of errors) which again turns into learning through feedback.
Step 6: Export – 1 min
Finally, the processed documents could be exported into a PDF(Excel or any other formats) along with deep-link. Anytime, the output document can be put for an easy cross-verification.
Botminds AI platform uses ML & NLP to extract context and data from Annual Reports, just like a human would, but 10x faster.
Complex tables and inconsistent document layouts are no hurdle to Botminds
With a context-aware platform, set up an end-to-end automation pipeline of Annual Reports in a few hours and make investment recommendations with highly reliable data.
Botminds helps you accelerate your business decisions – save money, increase revenue, and drive up business innovation.