The mortgage industry has become information-centric and highly competitive. Firms that understand mortgagor behavior and industry trends are managing to survive better than the others. Sophisticated big data analytics is central to this trend.
‘Big Data’ involves large and complex data sets, which yield surprisingly detailed insights. But the immensity of data necessitates special technology to process it and draw meaning out of it. Big data includes customer data captured from various sources, data bought from third parties like credit-rating agencies, and data from web, mobile, and social sites.
To comply with regulations, there is a need to maintain account-holder information in the system for seven years. But for better reporting at the loan level and borrower level, data needs to be maintained for longer periods. Thus, data at all levels—origination, underwriting, fulfillment, servicing, modifications, bankruptcy, and foreclosures—keep swelling into terabytes.
Then there are numerous variables that influence property value. Data keeps growing massively at micro and macro levels. Big data helps appraisers, lenders, and investors to estimate the present and future values of any real estate. It helps to better understand where markets are headed and make smarter decisions.
With legacy systems, 80% of an appraiser’s time is spent on data entry. The process is tedious and prone to errors. The support of big data in an appraiser’s software helps make accurate valuations many times faster than it is possible with legacy systems. That will transform the nature and productivity of the appraiser’s job.
Let’s see how big data helps the valuation process:
- It provides better insights on market environments that enable appraisers to comprehend growing and sinking markets in depth.
- It helps appraisers to address inconsistencies. Currently, the dependence on too many data sources creates misalignment between appraisers, lenders, and investors. Big data technology can collate all the different data sets, and create better objectivity and transparency.
- It helps them create detailed and compelling graphs and illustrations that make information more digestible.
So what happens if an appraiser chooses to ignore big data?
There are huge implications related to market risk. Big data can provide immensely insightful predictive reports that highlight dangerous or favorable trends like high debt-to-income ratios, unusual spikes in value and more. However, big data intelligence is not a substitute to human intelligence. Rather, it is a highly powerful supplement to it. Machine intelligence can do huge volumes of complex calculations at astounding speed and deliver reports. But to understand the implications of those reports and to take wise decisions, human intelligence and practice are important for appraisers. Big data helps them do their job better with respect to speed, efficiency, and accuracy.
Efficiently performed big-data analysis through SaaS (Software as a Service, also known as cloud-based software) can be used by anyone with internet connectivity. This facilitates data entry from the verification site, and it can be continued seamlessly outside the office setup or during travel. Many data fields can be auto-filled or imported from databases. This eliminates redundant data entry and manual errors. Overall, it reduces manual labor, processing time, and rate of errors, thus reducing the need for review appraisals. That means huge leaps in efficiency in spite of difficult market conditions.
