{"id":1271,"date":"2019-09-26T04:44:57","date_gmt":"2019-09-26T08:44:57","guid":{"rendered":"http:\/\/94.153.243.18:9292\/?p=1271"},"modified":"2019-09-26T04:44:57","modified_gmt":"2019-09-26T08:44:57","slug":"risks-to-consider-in-private-lending","status":"publish","type":"post","link":"https:\/\/staging.canadianlending.ca\/investors\/risks-to-consider-in-private-lending\/","title":{"rendered":"Risks to Consider in Private Lending"},"content":{"rendered":"

In all investments, including ones in mortgage loans, there are inherent risks. Since there is no way to avoid all investment risk, the wiser investor must develop strategies to manage and minimize it. Following good investment practices by working with an experienced mortgage investment team is the first step in eliminating and reducing investment risk.
\nA professional mortgage investment team will have in place a risk management plan that assesses all the factors creating the various types of risk and determines the level of risk that is appropriate for the particular investment opportunity. A solid understanding of all the variables that drive the risks and benefits of a deal is integral to maximizing an investor\u2019s returns.<\/p>\n

Operational Risk<\/h3>\n

Whether you are operating independently or as part of an elaborate team, scalable systems and procedures are vital to maintaining streamlined operations that mitigate risk and maximize your investment returns. Business or operational risk can sometimes be more challenging to assess as it requires a thorough assessment of the capability of team management, facilities, and staff to sustain profitable operation and growth.<\/p>\n

The team\u2019s evaluation should include an assessment of the strength, depth, and delivery track record of the management and key decision-makers. Does the management team have credible plans in place to deliver on projected targets? Are initiatives backed up by a well-formed architecture allowing for smooth implementation and execution? Let\u2019s put this into relative context. If the mortgage origination team\u2019s pipeline dries up with a minimal volume of deals flowing, but there is a strong demand of capital awaiting deployment, then do the underwriting criteria become more lax, allowing more deals to flow through a less stringent qualification process?<\/p>\n

Originating quality mortgages<\/h3>\n

A well-balanced team requires a balance between supply and demand channels to manage not only the investment capital it has at hand for deployment but also the availability of quality investment product. If the deal pipeline is robust and consistent, the team then has access to a better, more substantial selection of quality investment mortgages. After all, investors want to be skimming the top-grade investments and not scrambling amongst junk mortgages just to relieve their capital pipeline.<\/p>\n

A detailed quality control procedure will include the development of a quality assurance plan, the designation of a quality assurance manager apart from the origination role, the documentation of results, and a review of a sample of mortgages to monitor the quality of mortgage production. A professional investment team that adheres to these procedures and follows through with consistent implementation has a strong foundation for operational risk mitigation.<\/p>\n

Credit Risk<\/h3>\n

As part of the underwriting process, evaluating loan affordability based on the payment history and capacity of the borrower, including employment and credit history, is a crucial aspect of mortgage underwriting and a pillar in credit risk management. Underwriting basically entails approving or denying the mortgage application.
\nTechnology plays an integral role in boosting efficiency and helping measure and monitor credit risk. Once an applicant submits an application, the gathered information from the borrower is transmitted into the lender\u2019s loan origination system. Scoring systems enable underwriters to effectively price the risk and charge borrowers on the basis of their fully quantified creditworthiness. A credit report is then typically ordered, and the borrower is subsequently prequalified.
\nTo qualify a borrower, the underwriter must determine if internal guidelines are met for the requested loan amount as well as whether debt service and collateral coverage sufficiently meet agency and investor standards. This rigorous process varies amongst different lenders, and the models utilized in this process continue to evolve and adapt to changing circumstances.
\nQuantitative models and automated underwriting systems not only take the manual checking out of the equation but also streamline the application pipeline, allowing for scalability. As loans need to first be properly classified and then risk-rated, an independent mortgage investor\u2019s manual review process takes a toll on the pipeline bandwidth. This effectively means that the investor can only process so many applications at a time, resulting in a smaller selection of deals to choose from.
\nHaving an inadequate automated underwriting system results in incomplete risk analysis and subpar underwriting standards that lead to a decline in loan quality. Of course, there are limitations with these models as they do not account for the borrower\u2019s every variable and circumstance.
\nAn ideal model would take into account a broad spectrum of factors influencing a borrower\u2019s loan affordability and be able to incorporate future scenarios, including changing economic conditions. Until that day comes, an underwriter will have to leverage their experience and expertise to manually review the deal after the automated underwriting system has completed the initial leg work.
\nAs an independent investor without access to such technology and tools, building a basic model consisting of several variables to consider for your loan evaluation criteria is an initial step in the right direction. There is also the dilemma of how much weight to attribute to each variable.
\nOnce an initial model is established, the quality of the data coming into your system is vital. If you feed your system garbage data, then you will have garbage output. That applies not only to input data but also to input assumptions. For example, a borrower who missed five payments but paid last month could be considered current, and that may or may not be passable based on your policy.
\nCredit scoring models typically assign point values to a number of factors in the qualification equation. This scoring system methodology has the ability to:<\/p>\n