You know the moment. A lease looks fine on paper, but the tenant is a regional operator, the guaranty is thin, and the only recent financials are a few PDFs. You need a risk view you can defend, not a gut feel. The usual path is to stitch together ratings if they exist, read statements if they do not, and write a memo that tries to hold it all together. It takes time and still leaves gaps about how the tenant could miss and what might offset that risk. Underwriting ~10 min to run Assess Tenant Credit Risk Vic prompt Use Vic to assess the credit risk of a tenant and any guarantor for a lease, using available financials or public ratings. Purpose A human analyst needs about 90 minutes for the same work. This version completes the assessment in about 10 minutes and gives decision-ready risk details for lease underwriting. Inputs Tenant Name Required Guarantor Optional Lease Terms Optional Tenant Financials Optional Property Type And Location Optional Output Format Optional Include Discount Rates Optional Outputs A tenant credit risk assessment that names the obligated parties, states the analysis path, gives a likelihood of performance with a credit rating equivalent, ranks specific default reasons with mitigants, and includes an explicit caveat. An optional net-lease discount rate adjustment is available. The output arrives in chat or as a Word memo. Time saved Turns roughly 90 minutes of manual work into about ten minutes. How it works Run the task with a simple instruction: "Use Vic to assess the credit risk of a tenant and any guarantor for a lease, using available financials or public ratings." Then attach what you have. At minimum, a tenant name. Add a guarantor if there is one, lease terms if they affect risk, and any tenant financials. Property type and location help frame exposure. You can ask for a Word memo or keep it in chat, and request a net lease discount rate adjustment if you need it. Vic picks an analysis path based on the inputs. If there is a public credit rating, it uses that. If not, it works from the financial statements you provide. The output names the obligated parties and states which path it used so you can see the basis for the conclusion. You get a clear estimate of the chance the tenant will meet lease obligations over the full term, paired with an equivalent credit rating. The probability is easy to read. The rating lets you line it up with how your team already talks about risk. The most useful section is a ranked list of why the tenant might fall short. These points are specific. Each includes a potential mitigant so you can move from diagnosis to action. If a guarantor is part of the deal, the analysis treats that obligation directly, not as a footnote. There is also a plain statement of limits. Credit work has boundaries, and stating them up front keeps the memo honest and easier to defend in a credit committee or investment meeting. If you are underwriting a net lease, you can include a discount rate adjustment tied to the assessed risk. That keeps the credit view connected to pricing instead of living in a separate document. The output arrives in chat or as a clean Word memo you can drop into your file. It reads like it came from an analyst, with the structure most teams expect. This is not a black box that spits out a score. It shows its work so a broker, an asset manager, and a lender can all follow. You still need judgment, but you start from a consistent baseline that takes about ten minutes instead of an hour and a half. For deals with thin data, it forces clarity on what is known, what is inferred, and what could go wrong. For deals with strong data, it tightens the story and keeps everyone aligned on the same risk drivers. Either way, it replaces the scramble with a repeatable, decision ready view.