A whole loan investor wanted to improve the prebid process, focusing their team’s time on analysis and decision making about questionable property values, rather than on data gathering and validation. HouseCanary helped solve this challenge by providing an integrated and accurate source of data and analytics which allowed the team to make quick decisions about the validity and usefulness of seller provided collateral values. Analysts are now able to focus their time on individual properties that require greater scrutiny, using HouseCanary’s desktop analysis tools.
Whole loan investors have a limited amount of time to evaluate hundreds of loans. Analysts must filter and prioritize which loans to scrutinize thoroughly — and which lower-priority loans don’t require as much investigation. Without an effective process, analysts will waste valuable time on low-risk collateral and may
miss high-risk loans, and they require tools that allow them to quickly understand the property within its geographic context.
Our client used HouseCanary to determine whether the LTV provided by the seller was accurate, quickly identifying which homes might require additional analysis. HouseCanary provided additional details about properties. Historical price growth and home price forecasts, among other details, were available at analysts’ fingertips. This enabled analysts to filter and focus on the highest-risk homes, which comprised a portion of the entire pool — about 300 homes in 1,000. Each analyst shaved hours off the total time spent on each pool.
HouseCanary’s valuation tools and market-health information gave the client deeper insights into a large pool of loans, saving analysts time. The client was able to determine whether and by how much to adjust their bid amount quickly and with confidence. The client was able to submit a competitive, realistic bid that incorporated the data elements they needed to understand while also protecting the client from risk.
Analysts have a short amount of time in which to evaluate many loans, so it makes sense to focus on loans that require the most attention. If the LTV falls within established standards, then the analyst likely doesn’t need to prioritize the loan for scrutiny. But if the value of the home is less than the outstanding loan balance, the loan has a higher potential for default, and the bidder needs to know how to adjust bid price accordingly. Analysts were using consumer real estate portals to search for information on the current value of a home, but these sources were not reliable and did not contain the data and information that the client needed to help calculate its ultimate bid. HouseCanary’s API data points included the details that analysts needed to determine whether the LTV was accurate, in addition to several other endpoints that prebid analysts might need to consider in order to assess the bid. These include:
We build groundbreaking technologies to improve and accelerate residential real estate operations.
