Financial data is crucial to any real estate venture. The intellectual property required for a real estate venture is significant to its validity. When buying, selling, leasing, or renting any property, crucial financial data is analysed to make the best decisions. Documents such as T12, Operating Statement (OS), and Rent Rolls are thoroughly analysed to determine the potential of a real estate opportunity. For every real estate venture, the financial data shows it’s performance and value.
The T12 statement comprises all monthly expenses and revenues of a rental property in the past year.
The Operating Statement or OS is one of the prime indicators of real estate legitimacy and value.
When an investor invests in a rental property, they are buying two parts of the real estate, the property and its rental income. To make an informed decision on rental properties, buyers analyze the Rent Roll.
Most real estate agencies or brokers spend hours to extract data from T12, analyse Rent Rolls and furnish a complete Operating Statement. Various documents required for a single real estate property can be hectic to manage, let alone extract, compile, and analyse.
Some of the key challenges faced with manually extracting real estate data are:
The complexity of extracting real estate data can be simplified. Automation technology has taken leaps into the documentation process for commercial real estate. Real estate documentation, extraction, analysis, and data projections have become easier through automated software like Docsumo.
Automated data extraction makes real estate operations easier, and the final outcome a result of thought-out and incisive decisions.
Docsumo is an advanced software designed to extract information into a structured format from unstructured PDFs, scanned documents, and images. Considering the large sets of documentation required, the process is simplified into a few steps to extract data and compile it, saving hours on data entry tasks.
In a few simple steps, the Docsumo intelligent software extracts data from documents within minutes. The data is presented in a structured format. This method is used for extracting financial data, report analytics, Rent Roll data, creating a T12, OS, and much more.
Almost every complication in data collection and analysis can be resolved if there is an efficient system to extract data and produce finished reports. That’s why real estate building managers, accountants, record keepers, investors, investment partners, and associates lean on technology like Docsumo for improved efficiency. To maintain the financial data securely and extract crucial sets of data in any volume, automated data extraction is useful.
With the best software designed to extract real estate data, Docsumo is revolutionizing the way we look at intellectual property. No more long hours of running through sets of documentation. In a few clicks, the data is fetched, organized, and compiled with an interface that’s easy to understand.
With a high-performance software, users get the best of both worlds, accurate data extraction and exceptional efficiency. It’s so much easier to analyze thousands of bank records and confidential statements and extract data from T12 in a few minutes. Users can even analyze multiple rental properties to decide how to generate more revenue. You can handle all your assets and intellectual property the right way with the ideal software. Automated data extraction results in seamless efficiency and timely real estate proceedings.
To discover how to make real estate proceedings easier, more convenient, and extremely accurate, book a free demo with us.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
Optical Character Recognition (OCR) is the technology to convert an image of text into machine-readable text. It is the underlying technology for various data extraction solutions including Intelligent Document Processing. However, OCR is not smart enough to figure out the context in a document - it works simply by distinguishing text pixels from the background and finding a pattern. This limitation could cause inaccuracy in captured data that could directly impact the output of your data extraction model.
Accounts payable is a key financial function for any business. Corporations can have thousands of suppliers; even for relatively smaller businesses, the number of suppliers could be in hundreds. All the invoices they receive from these suppliers come in multiple formats, layouts, and templates - some semi-structured, some unstructured. Therefore, firms expend time and resources to capture invoice information through manual data entry and verification of accounts payable. Manual data entry is not feasible in the long run, definitely not on a large scale. Before we talk about how intelligent invoicing solves the problems associated with manual invoicing, let’s discuss the challenges in much detail.
As most of an organization's information is available in an unstructured format, processing it requires an automated system that can handle documents with minimum human interaction. OCR is one such technology, but its scope is limited as it requires human interaction and is highly dependent on the layout and structure of the document to be processed.These limitations are overcome by Intelligent Data Extraction.Using artificial intelligence, the Intelligent Data Extraction technology extracts data from documents and transforms it into useful information through the extraction process. It functions as a singular tool for extracting information from any type of document and aids in optimizing company operations.