Asset Management and Financial Operations with Simulation Modeling

Product portfolio managenment model

Uncertain data values or dependencies are inevitable factors when you are carrying out long term financial planning. It’s often the case that the uncertainty factor is simply ignored, or relegated to footnotes or a discussion of assumptions, and decisions are made on the basis of deterministic models, which assume that all factors affecting the economical situation are either precisely known or fall within discrete ranges. Some of these values are merely “unknowns” and the best guess, group consensus, or most recent data is used as a proxy. But sometimes key variables are not included or assumed away in the analysis; perhaps important interactions between two otherwise minor factors can become the major cost driver? These are the “unknown unknowns” and their impact cannot be simply resolved by Monte Carlo combinations of the possible values of the key variables tested in a spreadsheet simply because the analysts’ mental model did not conceive of their importance. The laws of probability, not to mention experience, tell us that many of these deterministic models will lead to significant financial losses.

We use simulation modeling in these situations to cover the range of probabilistic results, to uncover hidden interactions in multiple scenarios, to test dependencies and sensitivities; in short, to inform our thinking rather than just to quantify our perception of the analysis. Our models allow you to uncover uncertainty and develop the “most likely” solution while still keeping an eye on, and developing mitigation strategies for, probabilistic risks and potential negative scenarios.

Via Simulation Modeling we offer the following services in the field of asset management and financial operations:

  • Financial and investment risks analysis and evaluation. Practice tells us: to benefit in a market economy it is necessary to run risks. These risks can be taken if a businessman is able to quantitatively estimate the assumed profits and corresponding risks.. Simulation Modeling allows you to quantitatively estimate profitability and risks the level of the investment project in the form of an index (NPV, IRR, PI, PB) statistical expectation to scatter (variance, coefficient of variation, etc.).
  • Project and investment portfolio management. Profitability and risk forecasting based on a simulation model will allow you to effectively manage an investment or project portfolio. This can be either shares and real estate, or complex technical objects like leased equipment. Simulation of investment strategies in competing research projects in your development pipeline is also an excellent simulation application with dramatic ROI potential.
  • Financial results evaluation and forecasting. Simulation models allow you to predict company’s operation over time in detail, to evaluate liquidity and profitability metrics and to make a business activity and investments decisions based on selected output parameters (net present value, project payback period, internal rate of return, etc.).
For different asset and project management models, please refer to the models gallery.

Case Studies

  • Modeling of Banca d'Italia Back Office System
    Banca d'Italia processes a certain amount of manual credit transfers every year. These transfers cannot be processed automatically and require two divisions of employees in the back office of the bank. The bank wanted to determine if merging these two divisions would be beneficial.