In February 2021, Zillow, the largest online real-estate marketplace in North America, announced huge investment plans in 20 markets betting on Zestimate.
Ten months later, in December 2021, Zillow shut down its homebuying business, iBuying, laying off 2,000 workers as its market cap fell from USD 48 billion to USD 13.5 billion. Zillow was paying above market value for homes and selling them for less than their initial market price, ending with USD 1 billion in unsold home inventory. Meanwhile, the Federal Housing Finance Agency (FHFA) announced its plans to make desktop appraisals permanent from March 2022 for certain types of transactions.
Though desktop appraisals are expected to reduce cost and turnaround time, they have a high potential to be less accurate since there is no in-person inspection as in the traditional process. Incorrect property valuations can lead to long-term risks to lenders and investors. We discuss the key challenges in mortgage property valuation, the different types of valuation practices, and ways to make the process more effective and efficient by leveraging technologies such as artificial intelligence (AI), distributed ledger technology (DLT), and blockchain.
Understanding the current property valuation process
As part of the mortgage loan application process, lenders evaluate the risk involved in the subject property as it is the collateral for the loan.
Lenders often liaise with appraisal management companies that have licensed appraisers to perform field inspections and prepare appraisal reports – this takes around seven to 10 days. The appraisal report comprises all the property details, location maps, market value definitions, sale history, taxes, environment details, flood hazards, and assessed value. It also includes methods of valuation, the sales comparison approach, and detailed pictures of the property structure. There are standard requirements based on property types such as single-family homes, manufactured homes, condominiums, multi-family residences, and appraisal types such as exterior and interior. Traditionally, the property value is assessed from three viewpoints – the current cost of reproducing, the value from recent sales of nearby comparable properties, and the income that the property can earn.
When COVID-19 broke out at the beginning of 2020, the US mortgage market, especially the appraisal industry, underwent a significant change. While appraisals were waived off in several cases, some lenders allowed exterior-only appraisals and many employed innovative ways to assess the values with support from investors and regulators. The pandemic’s impact on property valuation led to different types of appraisals being proposed and used, such as hybrid appraisals and desktop appraisals (see Figure 1). In hybrid appraisals, a third party conducts an in-person inspection and provides inputs to the assigned appraiser, who then sends a report to the lender. The desktop appraisal is a step further, where the valuation is completed at the appraiser’s desk, using information, such as tax records and multiple listing services, instead of in-person inspection. This makes desktop appraisal faster and more affordable compared to other appraisal types. However, the accuracy can be called into question in this case, especially for complex property transactions.
Figure 1: Hi-level appraisal process flow
Bogged down with challenges
Various stakeholders, such as customers, lenders, investors, and appraisers, are involved in the existing appraisal process.
When it comes to the customers – the loan applicants – a significant concern is the delay in appraisals which can further slow down loan approvals. The appraisal cost is passed on to the customer even though the lender chooses the appraisal company and orders appraisal. Apart from this, inaccuracy in value assessment can impact eligibility, as loan-to-value (LTV) is a key parameter to determine affordability.
For lenders or investors, delays in the appraisal process, and in turn, loan decisions, impact productivity. Moreover, inaccuracy in value assessment affects the decision quality and increases collateral risk, leading to loss of customers and revenue.
For appraisal management companies, the primary challenge is the shortage of certified appraisers. Another concern is the delay in scheduling appointments for traditional field inspections or the hybrid model. However, in the case of the desktop model, the insufficiency of data available to make an accurate assessment forces appraisers to make assumptions.
A simplified valuation process will enable real-time access to required data and reduce decision-making cycle time for lenders and investors.
Simplifying the appraisal process
In 2021, the US government created an inter-agency task force called Property Appraisal and Valuation Equity (PAVE).
The task force was entrusted to deliver a final action report in early 2022 on the consequences of mis-valuation of properties and propose policies and actions. Most of the inaccuracies are due to the lack of timely updates on property details. Once a property is purchased or built, the owner enhances the property by building additional features over a period of time. These enhancements can include swimming pools, backyards, additional parking space, or extra floors. At the same time, values can go down due to natural hazards like hurricanes, earthquakes, and forest fires; normal wear-and-tear, pests or insect infestation; or other property damages. Values can spike or decline due to neighborhood changes like a new township, school district, recent sales on similar properties, and other upgrades. Delays in the process are mostly due to factors such as the unavailability of appraisers, scheduling time for in-person inspections, follow-ups in case of any disputes, and data collection.
Meanwhile, the industry is evaluating the latest technologies for remote inspection, allowing the appraiser to access the customer’s smartphone camera remotely to take pictures. Lenders can also explore technologies such as DLT and AI solutions. DLT is a highly transparent, secure, tamper-proof, and immutable protocol that allows decentralized databases to be shared and managed across networks. By leveraging data pipelines and algorithms, AI can combine market data, public records, and buying trends to find the best price range. AI solutions have many in-built statistical and machine learning models to validate data points for properties. However, for extracting insights from huge repositories of data, neural network-based models can be used.
We envision a simplified process, which is:
Figure 2: Simplified appraisal process flow
Figure 2 illustrates how this simplified process can deliver faster decisions on loan applications and lower appraisal costs, which in turn make it cheaper for customers. Moreover, there will be no surprises in assessed value, down payment requirements, and affordability, eliminating purchase price disputes with the seller.
In the case of appraisers and appraisal management companies, the process will ensure data integrity and availability, which means, appraisers won’t need to make any assumptions. The system will automatically identify discrepancies and assess values, bringing in the flexibility to review and waive exceptions, as well as over-ride and edit. This will help improve appraisers’ productivity and drive faster turnaround for appraisal reports.
The simplified landscape will allow real-time access to required data and reduce decision-making cycle time for lenders and investors. In addition to lowering operations costs, increasing productivity, and minimizing collateral risk, it can also reduce disputes, leading to higher customer satisfaction.
Making appraisals effective and efficient
Valuation of property is most critical as it defines the risk in the loan process, which can potentially impact every stakeholder.
Technologies such as DLT and AI can help the mortgage industry reduce turnaround time significantly and enhance quality, productivity, and customer experience by ensuring the integrity and availability of data. Several global banks are exploring DLTs in areas such as payment management and AI in almost all cognitive decision-making processes. Blockchain and AI technologies have the potential to revolutionize the mortgage process, making it a lot more effective and efficient than what it is today. Predictive analytics tools, distributed ledger-based solutions, AI tools, and virtual reality-based transactions are set to transform the industry significantly. Timely identification of new opportunities and emerging technologies will help businesses gain a competitive advantage.