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Land development risk

Estimated reading time: 5 minutes

Municipalities have many responsibilities. They aim to create a pleasant and functional living environment for their citizens, adequate infrastructure, city attractiveness to visitors and lower crime rates, among others. To achieve these goals, public resources need to be distributed efficiently, costs and revenues need to be balanced and budgets need to be kept in check. Land development risk plays an important role in these goals.

land development risk

Reality check

We often note that reality can be quite different than what we planned for. Especially in periods when the macro-economic environment changes. After the financial crisis in 2008 substantial distress occurred both within housing organizations as well as in municipalities. Especially if they heavily invested in land purchases in the period before the crisis.

In the period of 2009 to 2015 municipalities in the Netherlands lost more than 3 billion euro in value of their land development projects. One example is the municipality of Almere that had to write off 104 million euro on the land investments in 2014. When markets recovered in the decade after, many of the unsold lots could still be sold. This meant that losses could be more than recovered by subsequent gains. Still, at the time of the write off it did pose a problem for the budget in these municipalities. It meant cost cuts were needed and many goals could not be met.

In such situations it is often easier to establish what went wrong in hindsight. However, it is not so easy to predict those big failures in advance and to come up with appropriate control measures to be able to limit the loss to manageable levels.

Data driven risk management

Following this event, the municipality of Almere decided to embark on a journey to improve its risk management process. The process included reassessment of both qualitative and quantitative methods for risk measurement by learning from practices in the financial sector. We were asked to assist in this process.

The goals of this project were to ensure that risk estimates:

  • become an integral part of the considerations
  • will be based on statistical data for a defined negative scenario and horizon
  • will be validated

The expected advantages will be:

  • less surprises
  • a continuous view on the risks and not only in hindsight

Land development financial risk project

In this article we focus on the delivery of a solution for measuring the financial risks for land development.

The project consisted of the following main steps:

  1. Identification of the main risk drivers
  2. Creation and validation of the risk models
  3. Creation of business logic
  4. Creation of an automated risk report for each development or subdivision

The last step combines all prior steps to create a risk report for a bird’s-eye view of what drives the risks.

The previous existing process also gave insight into the risk estimates. In this case, the negative scenarios were based on experience from employees in the land development department. While these estimates can be very useful as a first indication of the risks, it is not possible to make statements about the level of certainty that such an estimate would entail.

Advantages of data driven approach

The data driven approach provides the following advantages:

  • We obtain an objective and statistical estimate of the chance that a negative scenario materializes (based on historical data, context and correlations)
  • The business logic becomes explicit instead of implicit in the minds of the experts
  • The decision making process becomes easier and more transparent for ultimate stakeholders
  • We become better prepared and will be able to respond faster with control measures when needed
  • Eventually, this will result in a lower chance of big surprises and a bigger chance of realizing the goals

Lessons learned and challenges

During the project we learned that multiple aspects play a role when it comes to the financial aspects of land development. Some key learnings include:

  • multiple risk factors play a role on the income side (land prices and volumes on homes and businesses),
  • land price risk differs for developments with different land value ratios
  • volume risk is an important factor
  • there are multiple risk factors on the cost side (site preparation, preparation for residential use, planning costs)
  • there is an opposite effect of deferred sales in a negative scenario for the revenue and cost side
  • budgets might contain already priced-in revenues and costs that needs to be corrected for
  • the need for net present value at the regulatory horizon and at end of the project
  • the inclusion of remaining land in the calculation
  • simulation aspects and sensitivity of the results

This meant that we needed to have extensive and regular consultations with the land development department about the methodology and the business process. Multiple iterations were involved to obtain automated risk tooling that would:

  • be easy to use
  • fit in the operational processes
  • lead to more efficient work processes (eg. to directly load information from the source system (TotalLink))

As proper land development risk models do yet not exist in the financial sector, we needed to perform extensive literature, data research, validations and backtests to be able to obtain appropriate models. We noted that especially for land development, risks are not constant over time so it was relevant to do additional research on macro-economic drivers.

Current state of the land development risk tooling

We are now in a stage where the land development risk tooling passed the user acceptance test and is able to simulate all aspects of the land development practises. The municipality has committed to shadow run in 2024 alongside the previously used tooling.

It is good to know that we have succeeded to obtain a clear and user-friendly process to get objective estimates of the chance and impact of the land development risk estimates.

If you want to know how this would work practically, you can read more about this in the technical article about the land development risk tooling.


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