Extraction of Data from Multiple File Formats (pdf,xls,scans) for CRE

Extract complex data formats from financial documents of different layouts

The responsibility of presenting unimpeachable information which enables companies to make business decisions is primarily of a real estate analyst. But to present unassailable information, real estate analysts spend a large amount of time doing administrative tasks.The sheer volume of data which has to be converted into consumable data, takes hours of time.

Technology is now making this easy for real estate analysts, eliminating the grunt work from processes so that they can spend more time on what they do best: Analyse. Real estate analysts have to adopt the technology, so they can focus on improving their judgment and enhance their creativity to make confident recommendations.

It is undoubtedly true that technology, and most prominently, the advancement of computerized technology, has disrupted many professions and business,  but smarter people and companies transform their practices according to the technology to enjoy broader responsibilities with better monetary benefits.

Companies should engage their analyst while deciding on which technology to adopt.

The small improvement in the big lending process can have a huge impact on your bottom line. Here is an idea — A real estate analyst approx. earns 70000 USD per year. If he spends 2 hours daily on administrative tasks, he will spend total = 2 X 261(Working Days)= 522 hours in non-value add work. The per hour cost of an analyst is around $35.  Hence the total loss per analyst is approx. $ 18000/yr - which is around 25% of the total cost. We haven’t even started on the chances of human errors while inputting the data from the financial statements and rent rolls.




Keeping in mind this productivity loss, technologies such as artificial intelligence, machine learning, and NLP have numerous applications which easily automates processes to save time and money. One of the best application is OCR.

Optical character recognition (also optical character reader, OCR) is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example from a television broadcast).Source — Wikipedia

OCR can be effectively used to automate the process of manual data extraction from financial statements while analyzing a deal.


Analyzing (2)

We at clik.ai have been working on improving data extraction from Operating Statement and rent rolls for a year. Our engine has been trained by processing more than thousands of Rent Roll and Operating Statement to perform data extraction on any type of document format. It is also trained to remove non-relevant information available on documents and provides data in a proper consumable format. Our machine learning models are well trained to classify the line items while analyzing operating statements. The platform has the flexibility to customize classifications.  

Based on the feedback received from underwriters and analysts progressively using our platform, we have added features to increase the confidence on the engine. Analysts can verify the accuracy of extraction, verify the classification and make custom changes in the final loan model.

There are a few other options out there in the market which analysts have been using to extract data from PDFs, but they have their own limitations. Many analysts use PDF to Excel Converters such as PDFTables, Nitro’s PDF to Excel Online. Your decision and choice of software may depend on the extraction accuracy and extraction time.

CRE lending process is lengthy and data-intensive. To thrive in today’s world, it is almost mandatory to adopt the technology and be ready for future opportunities. Here is how you can extract Operating Statement, Rent Roll data in loan models instantly using Clik.ai.


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