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Case Study #9 – UK Debt Advisory Firm Modeling Test (Case + Solution, Updated June 2024)

This is the 9th real estate case study in a series of commercial real estate case studies shared by A.CRE. These case studies are meant to help you practice mastering real estate financial modeling. In this case study, you play the role of a job candidate interviewing for a Capital Markets Associate role and must complete a Debt Advisory Test at a major UK firm. This modeling test is true-to-life, and is great practice for anyone interested in commercial real estate investment, debt advisory, UK-based underwriting, and office investments.

Practice makes perfect! This is a real scenario based on actual properties and situations. Names and locations have been changed for confidentiality reasons, but the fundamentals are real-to-life.

Each case study shared in this series mirrors real world situations, either in terms of the types of deals you will look at in various roles or the types of modeling tests you’ll be required to perform as part of the interview process. You can browse this and other case studies in the A.CRE Library of Real Estate Case Studies.

Are you an Accelerator Advanced member? Download this case study and solution files for free in the Career Advancement Endorsement. Not yet an Accelerator member? Consider enrolling today in the Accelerator, the industry’s go-to real estate financial modeling training program used by top companies and elite universities to train the next generation of CRE professionals.



This test was shared with us by an A.CRE Accelerator member. We’ve modified the test slightly to remove any personal or company identifying information. But otherwise, this is a modeling test that a UK Debt Advisory Firm uses as part of its interviewing process. Give the test a try and then share your results and/or ask questions in the Q&A section.


You are a Capital Markets Associate supporting a team of debt origination professionals at a top Debt Advisory firm based in London. A borrower has approached your team with a financing request and provided the following information:

  • Single let office building in Central London
  • Total area –150,000 SF (13,935 M2)
  • £66.7 PSF per annum and 2yr WAULTE with assumed annual rental uplifts of 3.00%
  • Purchasing the building value today is based on a 5.00% cap rate
  • Borrower plans to hold the asset for 10 years and exit at a 4.25% cap rate

What is the borrower’s base case unlevered IRR and equity multiple?


After a few weeks of performing financial analysis, creating a financing memorandum, and preparing a target list of potential lenders, your team takes the borrowers offering to market. A week later the borrower receives three financing proposals:

Option A: 50% LTV @ SONIA + 1.40% with 0.50% upfront and no amortisation

Option B: 65% LTV @ SONIA + 2.00% with 0.75% upfront and 1.25% per annum amortisation

Option C: 70% LTV @ comprising:

    • Senior: 55% LTV SONIA + 1.60% with 1.00% upfront and no amortisation
    • Mezzanine: 70% LTV at SONIA + 7.00% with 1.00% upfront and 1.5% amortisation per annum
  1. What is the borrower’s levered IRR & Equity Multiple in each case?
  2. What is the incremental cost of debt between the proposals (Margin, Total £ and Lender IRR)?
  3. Which proposal do you think is more attractive and why?
  4. What loan terms / structural points should the borrower be on the lookout for?


For those that are no UK-based, there are various terms that may be foreign to you. Additionally, the test leaves out a few assumptions that merit commentary. And so, in this section I will share the definition of terms that are UK-specific as well as fill in assumptions that were missing from the test.

UK-specific Terminology

  • Single let. Refers to a property with just one tenant. In the United States, this is synonymous with Single Tenant.
  • WAULTE. Weighted average unexpired lease term. This refers to the weighted average remaining lease term for any tenant currently in the building. The term is synonymous with WALT (weighted average lease term) and WALE (weighted average lease expiry). In the case of this test, there is only one tenant and so the WAULTE is the same as that one tenant’s remaining lease term.
  • Annul rental uplifts. Refers to the amount contract rent will increase from one year to the next. Also known as ‘rental increase’ and ‘rent bumps’.
  • Leasing Commission. It’s not uncommon in the UK and Europe to calculate leasing commission on “the gross average annual rent”, rather than on the total contract rent amount as is common in the United States. Consequentially, for this test a 15% leasing commission is calculated on the gross average annual rent rather than on the total rent.
  • Tenant Incentives. Monetary incentives offered to tenants to induce them to sign a new lease. This can be in the form of tenant improvements, rent reductions, etc.
  • SONIA. The Sterling Overnight Indexed Average measures the rate paid by banks on overnight funds. The SONIA rate is a benchmark used in the UK and meant to replace LIBOR. Click here to learn more.

Additional Assumptions Necessary to Complete the Test

While modeling tests provide the base assumptions necessary to evaluate the case, these tests often leave out certain assumptions that are necessary to complete the test. This is not uncommon of modeling tests. It’s a way to test the candidate’s proficiency in various concepts and to make them think a bit.

When a modeling test does not include certain assumptions, fill in your own assumptions. Just make sure to note the additional assumptions you made. That way, when you sit down with the hiring manager afterwards, you can discuss your justification for making those additional assumptions.

In the case of this modeling test, we were not provided the solution to the test. As a result, we filled in the missing assumptions on our own. Thus, the additional assumptions we made in the solution file may not match the assumptions in the actual solution file.

Here are the additional assumptions we made:

  • Analysis start date. The modeling tests makes no mention of what date the analysis begins, which is important for calculating IRR using Excel’s XIRR() function. We assumed an analysis start of Jan 1, 2022.
  • Per annum amortization. We assumed that per annum amortization referred to the percentage of the initial loan balance that amortized (i.e. decreased) in each year.
  • Contract rent = market rent. The test provides the current contract rent but makes no mention of market rent. Market rent is necessary to calculate the contract rent for subsequent tenants (i.e. 2nd+ generation tenants). We therefore assume that contract rent is equal to market rent.
  • Contract rent growth = market rent growth. Simply to item b, the test makes no mention of market rent growth. We therefore assume that the provided contractual rent growth (i.e. annual rental uplifts of 3.0%) is equal to the annual market rent growth.
  • Tenant responsible for all operating expenses. The test makes no mention of operating expenses or reimbursements. We therefore assume that 100% of operating expenses are borne by the tenant, and that during downtime there are no operating expenses.
  • 2nd Generation Lease Length. The test makes no mention of how long the lease for the 2nd generation tenant would be. We assumed a 10-year lease, which would put the expiration of that lease beyond the analysis period.
  • Variable rate based on SONIA forward yield curve. The case calls for interest to be paid based on some spread over the SONIA rate. No further details on methodology were provided. We downloaded the SONIA forward yield curve from Chatham Financial, grabbed the quarterly rate, and arrived at a variable quarterly rate based on that curve together with the spread.

Try Another Case: In the same way that A.CRE has made publicly available over 60 institutional-quality real estate models, we're now on a mission to build the largest library of free real estate case studies. Browse the library today.

Create Your Own Case Study

This case study offers a view of the decisions involved in a job interview debt advisory test. As you apply the provided data and strategies in your career interviews and financial models, you’ll gain insights into optimizing asset value and ensuring investment criteria are met, key skills for any CRE professional. For those looking to deepen their expertise, our Real Estate Case Study Creator provides a platform to test and enhance your modeling skills in a controlled, realistic setting. This GPT creates completely custom real estate case studies from scratch and allows users to craft case studies to simulate scenarios they are interested in or expect to encounter in their professional lives. This customization allows users to focus on particular areas of interest or challenge, making the practice sessions as relevant and effective as possible. We encourage both seasoned practitioners and newcomers to use this resource to refine their approach and decision-making in commercial real estate investments.

  • Note: Custom GPTs are now available to both paid and free users of ChatGPT. Click here to learn more.

Download the Case PDF + Excel Solution

In addition to the web-based case, we’ve created a PDF version to download and use offline. Additionally, we’ve added a solution created by Spencer and Michael. Note that the solution may contain errors – if you spot an error, please let us know and we’ll roll out an update.

As with our real estate financial models, this case study and solution are offered on a “Pay What You’re Able” basis with no minimum (enter $0 if you’d like) or maximum (your support helps keep the content coming). Just enter a price together with an email address to send the download link to, and then click ‘Continue’.

We occasionally update these cases and solutions (see version notes). Paid contributors will receive lifetime access to the case, solution, and all updates.

Version Notes


  • Updated Debt Service calculation to use beginning loan balance for interest calc rather than ending loan balance


  • Initial release

About the Author: Born and raised in the Northwest United States, Spencer Burton has over 20 years of residential and commercial real estate experience. Over his career, he has underwritten $30+ billion of commercial real estate at some of the largest institutional real estate firms in the world. He is currently President and member of the founding team at Stablewood. Spencer holds a BS in International Affairs from Florida State University and a Masters in Real Estate Finance from Cornell University.