Evaluating Loan Underwriting and Extraction Software For Commercial Real Estate
Commercial real estate deal making is about timing and moving fast. The faster companies evaluate and prospect, the more deals they win. Winning the transaction doesn’t just necessarily mean sourcing more deals but have the infrastructure and support team to evaluate deals correctly and expediting the process of getting the term sheets and LOIs signed up with clients.
In a cut-throat competitive landscape of commercial real estate deal making, all the involved parties want the transaction to process as faster as it can get.
Nevertheless, a tremendous amount of time is spent on the brute force grunt work involved in manually extracting information from financial statements, loan documents, analyzing the deals and underwriting commercial real estate manually. This must sound exasperating to you if you are a broker or a lender. Well, there exists a duly sizeable solution to your headache of scrutinizing source documents and fine details.
Evidently, the foundation of CRE industry is human interaction followed by labor-intensive negotiations, authentications, and financial transactions. This is the point where the industry is currently witnessing phenomenal operational refinement and automation, and it seems to be effectuated by Artificial Intelligence and self-learning software. One of which is a loan underwriting software-based analysis.
Current picture of commercial real estate industry
The CRE professionals are soliciting technology to build solutions towards automation pathway. Most large CRE corporations have either created their own dedicated innovation teams or back the technology incubators and participate with a dedicated real estate tech VC fund to be on the right curve.
Most small to mid-segment brokers and lenders either don’t have the bandwidth or the time to explore such innovation and new technologies that are coming to market. Seemingly, the prevailing processes of CRE are laden with recurrent operations that are highly non-automatic in nature. Technology implementation here ultimately reduces production time.
Take for example, a document extraction technology for commercial mortgage; which automates manually performed, time-consuming activities like extracting financial numbers and line items from multiple formats of Operating Statements, T-12, Rent Rolls.
Span of automation in Loan underwriting
Currently, the way loan underwriting is performed is intermittent. For a human eye, it would take a great deal of time to scan the financial documents and extract the information. Amongst major operations loan evaluation, mortgage review, and document processing consume time the most. Simultaneously, they require ultimate precision and expertise.
This is where new AI and machine learning technologies can help. A loan underwriting automation solution allows clean-cut scanning of the multiple formats like PDF, Excel, Scanned images and extraction of data for further processing; that is, automation of the entire recurrent process.
What to consider while evaluating a loan underwriting software, if you were to buy a one?
Listed below are some key factors that you should keep in mind:
- Eliminate the manual export of line items and financial numbers from source documents to workflow (loan models).
- Setup simplicity and user-friendliness of UI
- How fast it can underwrite commercial real estate deals
- Document scanning, and accurate recognition of inserted data that eliminates manual entry of data
- Accepts multiple files at once in various formats like pdf, excel, scans? (A drag and drop utility here wins brownie points)
- You should be able to upload financial documents, download loan models in excel spreadsheet, everything in a standard format (This is a must)
- Does it extract and accurately classify the data like roll rent, OS, and TTM for further analysis?
- Privacy and data security and utility of your own personal storage
- Customisation: Can you integrate your own loan model into the system?
- Does the service provider offer 24/7 support? Where would you seek help if you run into any technical trouble?
- Lastly, figure out the business value you can achieve from it. The expected ROI will show you the financial worth of the solution you intend to implement.
All in all, you need to check how easy it is to upload-extract-download of cash flow items. Based on this evaluation checklist, whichever solution scores highest on your list should be your choice.
Clik.ai is one of the first to introduce machine learning and automation in loan underwriting. They recently appeared at #4 in the list of top 25 commercial real estate tech companies to watch for in 2018.