The next housing bubble will be affected by elements that were nonexistent seven years ago, such as the composition of the portfolio shifting toward nonbanks; the role played by regulators; skyrocketing operational and compliance costs for lenders; and an increasingly complex market in terms of volume, leverage and stakeholders and their interactions.
The ability of the housing finance market to absorb a second potential housing bubble may depend upon two key factors. The first is a market participant's ability to individually invest in long-term strategic initiatives that address the foundational issues of enterprise data. Risk management at an individual level is a first step toward mitigating risk at a more macro level. It will be a challenge for market participants to do this without getting distracted by more tactical and reactionary goals.
The second is the market's ability to create value networks through partnerships between regulators, primary and secondary market parties and their technology partners. These value networks have the potential to diminish future financial crises through a combination of risk frameworks and regulatory measures backed with advanced analytics technology.
Financial markets have generally shown an inclination toward integration (e.g., swaps clearing process), and if properly executed, there is a possibility that the housing markets could benefit from this. In any event, technology and the power of data will be key factors in either helping spark a second housing bubble, or making it just a passing reference in the history of housing finance.
The rise of nonbank alternative lenders — also known as "Six-Minute Lenders" because of their ability to gather electronic documents directly from financial institutions and approve or deny borrowers for loans within minutes— includes lending clubs and peer-to-peer lenders leveraging high-end technology platforms. Participants in these entities are no longer restricted to small organizations funded by venture capital. In fact, some of the biggest financial organizations (especially larger hedge funds) are getting on the bandwagon through other conduits, for example, Goldman Sachs' new consumer lending unit offering financing to middle-class Americans and directly competing with Main Street banks.
Naturally, the presence of these nonbank institutions creates a potential area for systemic risk — one not necessarily accounted for in the current regulatory framework. However, just as technology has served as a force for disruption, it may also enhance measures put into place in the aftermath of the crisis and this is an opportunity to leverage that capability.
Technology has made rapid strides in the combination of data and analytics. By running big data analytics, organizations are able to analyze a mix of structured, semi-structured and unstructured data in search of valuable business information and insights.
It is widely recognized that inconsistent and ambiguous terminology and poor data quality exacerbated the crisis through inaccurate classifications and reporting. One example of this is the classification of subprime loans as prime, based on their acceptance by the government-sponsored enterprises, even though these were accepted by lowered underwriting standards as part of the affordable housing programs/acts.
Post-crisis regulators, industry groups and market participants have acknowledged the need to enhance data quality, including the clear definition of regulatory reporting guidelines and the consistency of definitions and attributes at loan, borrower and security levels. Most stakeholders have recognized that good quality data is beneficial to the market because it allows for improved correlation analysis and predictive modeling, which in turn improves efficiency.
There has been a concerted focus in not just borrower classification (i.e., clearly defining a first-time homebuyer), but also counterparty standards like primary mortgage eligibility requirements, and servicing standard guidelines such as the Servicer Total Achievement and Rewards program. Another great example of the industry moving towards standardizing data and protocols is the success of the Mortgage Industry Standards Maintenance Organization.
There is no guarantee that the increasing amount of available data will necessarily help investors correctly value what they buy, or allow regulators to properly measure systemic risk. Market participants must develop clear strategies for ensuring data availability and quality in their organizations — data consolidation and adoption, strategic prioritization of modeling initiatives and an overhaul or consolidation of reporting frameworks and tools are all steps in that direction. An organization's ability to develop early warning signals based on historical trend analysis would be a definite competitive advantage.
While regulations and processes help manage risk, they will never completely eliminate it. Since 2008, several steps have been taken to manage credit risk, such as the launch of credit risk transfer initiatives to distribute risk across investors, lenders and insurers, and the defining of documented standards and guidelines for counterparties like insurers and servicers. Similarly, interest rate risk management for the portfolio of loans the GSEs retain on their books has also seen several advances to manage both extension risk as well as pre-payment risk.
However, with the high focus on partnerships in terms of risk distribution, the counterparty risk in terms of exposure and the number of counterparties has significantly increased.
The improvement of risk model sophistication, regular disclosures, defined guidelines and frequency of stress testing and reporting have been put in place to manage causes that led to the 2008 crisis. It remains to be seen if these measures adequately manage systemic risks.
However, for any of this to work, incumbent participants must have clear strategies as well as the will to boldly execute those strategies.
Further, the ability of technology to outstrip the bounds of regulation is readily apparent from the rise of nonbank financial entities. Regulators must also develop proactive strategies that leverage technology and data as a means to mitigate systemic risk when guidelines fail to do so.
Adi Ghosh focuses on the primary and secondary housing finance markets as a director at Sapient.
