Processing condo mortgage review applications is extremely data-intensive. When Tim Bradley, CEO of Condo Analytics, started his company to improve the accuracy and efficiency of these procedures, his team collected data in Excel spreadsheets. Each order included a multi-page spreadsheet, with thousands of files linked to a master spreadsheet. Naturally, this system was extremely inefficient: data entry efforts were duplicated, and staff members were locking each other out of files. As Condo Analytics grew and processed more data, the need for an automated system became increasingly evident.
Unfortunately, none of the workflow and productivity tools Bradley found online could handle the full data and document acquisition and review lifecycle, or provide the customization required. Bradley assumed that he would need to cobble together a web form creator, relational database, PDF solution, project tracker, and report tool, each automating a specific piece of the process.
Enter Agiloft whose scalable and flexible platform would allow Condo Analytics (and its data load) to grow. Bradley was particularly impressed by the product’s configurable forms, reports, data integrity manager, rules, and end-user interface, which would allow him to extend the system to loan officers at mortgage institutions. In particular, Bradley was able to create several automated, templated tasks for each order, with ad hoc follow-up tasks staff could create as needed.
According to Bradley, Agiloft has streamlined the company’s processes by 80%, allowing it to handle more orders and offer more full-fledged services to clients—with fewer staff members and no extra fees. For instance, thanks to Agiloft’s pre-flagging of potential trouble spots (such as pending litigation) in applications, Condo Analytics now follows up before submitting reviews back to lenders. As a result, the number of orders sent back by the client for follow-up has been reduced from 30% to 10%. Bradley expects to further cut this percentage down.
With Agiloft’s robust reporting, which provides key insights into the sources of bottlenecks and other issues, Bradley has been able to further improve the system. For instance, after reviewing the history of follow-up tasks, he identified categories of standard actions to build into the process workflow.
Inspired, Bradley began creating a national database, with background information on each property from every homeowner association (HOA), co-op, condo association, and planned unit development (PED). Since about 10% of orders are for HOAs already in the system (with more being added regularly), this has dramatically reduced the order processing time.
“Agiloft can do everything—it’s even become my alarm clock,” praises Bradley. Thanks to its flexibility and scalability, Agiloft will help Condo Analytics further improve the efficiency and accuracy of the mortgage review process. The sky is truly the limit.
Read the Condo Analytics case study: https://www.agiloft.com/condo-analytics-case-study.pdf
