Prediction is difficult, especially about the future!
Use MyFinModel to determine financial feasibility.
Most start-ups in the software space are, naturally, founded by folks whose area of expertise is technical and not financial; they are more likely to be comfortable writing or debugging computer code than to think about income statements or balance sheets. In the early stages of a start-up it is not uncommon to not have a single person on the team who can understand a full set of financial statements let alone create them.
In this article we provide a brief overview of project finance modeling and compare the traditional spreadsheet based approach to using a web based tool. Full disclosure — we are the developers of the web based tool. The web based tool we describe alongside the spreadsheet based approach is called MyFinModel and this tool provides options for multiple financial models including project finance models.
In this article, we develop a Value at Risk (VaR) type framework for project finance modeling. The approach can help quantify the likelihood of default and provide a probability distribution of potential loss in case of default.
This article provides an introduction to the various public data sources that exist at the Federal, State, County and local levels that can help enhance the typical data analysis assignment.
The regulatory regimes that govern the permitting and authorization processes that are required prior to initiation of major infrastructure projects in the United States are quite complex. It can take significant time and effort to obtain the necessary permits and authorizations. In this article, we look at time to complete some of the most common permitting actions for major projects using data available from the Federal Infrastructure Permitting Dashboard.
This article provides an overview of the crop insurance program in the US provided by the Federal Crop Insurance Corporation via a network of private firms. We review the evolution of the program during the past two decades and suggest an approach to model the loss to liability ratio. We show that the Weibull distribution provides a reasonable option to model the loss payments between 0% and 100% of the liability levels, a finding consistent with prior research on insurance claims modeling.
The flood insurance program in the US is managed by Federal Emergency Management Agency through the National Flood Insurance Program. In this article, we review the claims filed during the period 1970 – 2019, and examine how the claims payments can be modeled. We look at the claims both at a global level and at an individual event level. We suggest an approach to model the payout coverage ratio and show that the log-normal distribution provides a reasonable option to model the payments between 0% and 100% of the total policy coverage levels.
Insurance claims forecasting for extreme weather events that result in large scale destruction such as hurricanes, wildfires, floods, etc. is an important planning activity for insurance firms and any process improvements that can enhance the accuracy and quality of the forecasts should be welcome. This article provides an introduction to the forecasting methodology for insurance claims payouts and then discuss potential use of machine learning techniques to enhance the forecasting process.
The Maryland Department of Transportation is in the process of soliciting proposals from private sector developers to design, build, operate and finance the construction of additional lanes on I495 and I270 highways in Maryland. These additional lanes will be developed as “managed lanes”, i.e., toll lanes where certain high occupancy vehicles are allowed to use for free.
Please access the paper here.