Data plays a bigger role in the shrinking distressed market
Thu July 20, 2017
Investors can accurately assess risk and price accordingly
Tony Peterson | Director of NPL/RPL operations at Clayton Holdings
The recovery of the housing market has seen price rebounds, decreased delinquency and foreclosure rates, and overall improvement in loan quality. As you’d expect, this has reduced the number of non-performing loans, but the universe of NPLs and re-performing loans is still large by historical standards.
According to CoreLogic, the number of distressed housing units was approximately 1 million in February 2017, well down from their peak at 3.7 million in January 2010, while the percentage share of sales for Real Estate Owned and short sales fell to 8.9% in 2016 versus a high of 32.3% in January 2009.
What does all this mean for the NPL/RPL trading market?
Both GSEs still have plenty of legacy NPL and RPL on their books, as do large banks, particularly those with footprints in judicial states. That results in relatively large deals hitting the market: often portfolios of tens of thousands of loans, with unpaid balances of $1 billion to $3 billion. Smaller trades have also remained steady as reperformers get sold and regional banks and other investors manage their balance sheets. And there is still plenty of demand.
Two new wrinkles that we are now seeing in the market are joint venture purchases where small to mid-sized players collaborate to compete against bigger firms on large trades, and more sophisticated use of data and analytics in the due diligence process to speed up decision making, assess risk and sort loans with different possible trajectories.
In joint venture arrangements, two or three entities join forces to bid and buy large pools. We also see niche buyers opportunistically seeking certain types of defects that deter other buyers, enabling them to buy, cure and monetize the assets.
Investors continue to perform due diligence in determining pool bid prices, and the “swim lanes,” or execution strategies, they expect for acquired loans. Some NPL will be cured to RPL, some resold as scratch and dent, some held in portfolio for projected housing price increases, while others will be liquidated in the normal course of servicing. There is a pretty good chance that we’ll continue to see this churn of distressed assets and perhaps a couple of NPL securitizations, more likely private than public.
So, given this backdrop, how has the role of diligence changed? The basic components and process of diligence have generally remained the same. However, the level of sophistication around data sources and the technology to help aggregate information are enabling traders to act more quickly and develop deeper insight around the borrower and the property.
NPL/RPL diligence encompasses risk analysis related to data and exceptions. Automation of data and analytics adds velocity to the process. Competitive advantage is provided by those with the breadth and depth of industry knowledge to evaluate how various exceptions or risk issues relate to a buyer’s overall investment strategy and its ability to service and exit the assets.
Developing a complete picture of each asset – property value, title, regulatory compliance, cash flow and servicing – allows investors to accurately assess risk, determine which loans fit their “swim lanes” and price accordingly.
Bringing technology, disparate data and qualitative information together leads to a holistic diligence process that aggregates results and data from multiple diligence components. Investors should look for companies that can provide end-to-end services for all due diligence components, collateral and title curative, servicing surveillance, asset management and REO disposition, which can be used by investors to evaluate their portfolios, carve pools that fit certain criteria, and maximize their execution when selling loans.
Yes, the volume of distressed housing units may be down, but the opportunity for the NPL/RPL market is alive and well, powered by data enhancement and technology.