The following article was written by freelance writer Jeff Broth.
Over recent decades, student loans have become a common means of financing a university education for all but the wealthiest families. In the US alone, student debts now amount to more than $1.4 trillion, making them second only to mortgages as the largest source of consumer debt.
While this is driven in part from a higher proportion of the population attending university, academic institutions in both the US and the UK have also been steadily increasing tuition fees over recent years. However, the increasing debt burden that this has put onto the millennial generation is being felt elsewhere in the economy, one of the most notable being in the property market.
The state of the mortgage lending industry
Ever since irresponsible sub-prime mortgage lending led to the 2008 global financial crisis, mortgage companies have been subject to heavy regulation governing what they can lend, and to whom. Studies have shown that a steady decline in home ownership among the younger generation is at least partly attributable to an increase in student loans. A heavy debt burden combined with low graduate starting salaries will often preclude millennials from obtaining a home loan. With student debts often taking 10 years or more to pay off, even those who are the most diligent in meeting repayment obligations could see themselves locked out of the housing market long after they graduate.
Peer-to-peer (P2P) lending has increased in popularity over recent decades, spurred on by the age of connectivity. Blockchain startups have been quick to recognize the benefits that the new technology can bring to P2P finance, directly connecting individuals who wish to exchange value without the need of any intermediaries such as banks.
Now, one startup plans to use artificial intelligence (AI) and machine learning in combination with blockchain technology to create a P2P lending platform for home loans. This could prove to be an ideal solution for frustrated millennials, who may be more open to using new technology to achieve their property ownership goals.
AI in the mortgage application process
Homelend is an Israel-based company developing a platform for P2P home loans that could prove disruptive to the mortgage industry. In many ways, it is an industry that has remained unchanged for decades. The introduction of mortgage-backed securities in the late 20th century transformed the way in which mortgages were funded. However, the overall process of obtaining a mortgage remains paper-based, lengthy, and grueling for all involved–mostly due to the background checks required. Rigorous checks consume time and effort, but they serve three fundamental purposes: verifying that the property can be purchased by the borrower, ensuring that the loan can be repaid by the borrower, and assessing whether the value of the property is sufficient to cover the loan in the event of default.
Homelend foresees that the use of AI and machine learning can replace the extensive human effort involved in the information gathering required for background checking. Currently, these checks are largely reliant on credit rating agencies. By bringing background checks onto the blockchain together with AI and machine learning, the process can be fully automated, eliminating the need for paperwork.
Most crucially, background checks can be extended to analyze the online presence of the borrower considering additional factors in the creditworthiness score such as education level or future earning potential. Such checks would be robust enough to avoid sub-prime lending. However, by widening the lending criteria beyond a credit check, millennials with outstanding student debt obligations could be seen as a safer credit risk for a long-term loan than using credit ratings alone.
It’s not just millennials who could benefit from this kind of AI-driven extended background check. One of the ironies of our current credit scoring system is that the achievement of a good credit rating depends on individuals having held debts and having repaid them without default. Individuals with insufficient credit experience would be denied a mortgage using traditional credit checking means. P2P mortgage lending may therefore be a more attractive prospect than accruing and paying debts in order to achieve a satisfactory enough credit score to procure a mortgage.
Smart contracts to manage the mortgage funding process
Smart contracts will form the backbone of the process by which mortgages are approved and closed. The platform will feed the outcome of background checks, together with the property appraisal (sourced externally by more traditional means due to the physical assessment required), into smart contracts. Assuming all conditions are met, a pre-approval of the loan is issued.
The loan will then be crowdfunded through the Homelend platform, by slicing it into smaller portions that can be purchased by individual investors. The loan will be confirmed only once it is funded in entirety, again by utilizing smart contracts on the blockchain. With enough investor participation, the time from application to closing the loan could also be significantly reduced.
Upon closing the mortgage, the transfer of funds from the lenders to the seller of the property will also be managed by smart contracts and executed in cryptocurrency. In order to offset the risk of volatility in cryptocurrency values, the seller will have the option to receive the funds in fiat currency.
Homelend foresees that managing the deeds and servicing of the mortgage will be done by groups of lenders forming non-profit vehicles (NPVs) according to the jurisdiction of the countries in which they operate. Payment collection and the management of defaults will be done through a third party agreed upon by the NPV members, who will distribute repayments among the members of the NPV. Eventually, it is even possible that loan servicing could be managed on the blockchain by the use of smart contracts.