There are two ways to enter the Simio Student Case Competition. You can either enter directly or through class participation. This contest, we had 28 teams enter directly (82 students) and 32 instructors with 223 teams (794 students) for a total of 251 teams (876 students).
We also had representation from the following 13 countries:
The 876 students came from these 36 schools:
SafeBank is a major custodian bank in the global financial market. One of the services SafeBank provides is changing currencies for their clients. For example, if a client wants to buy equity in a German company denominated in EUR, and the client wants to spend USD, SafeBank will take the USD and give out EUR, which allows the client to conduct their transaction. SafeBank makes money by charging the client a small percentage on each exchange. There are thousands of random, unpredictable transactions every day, and they require SafeBank to hold cash in each type of currency. At the end of each day (6:30PM ET), SafeBank conducts a settlement with CLS Bank (Continously Linked Settlement Bank) to reset the quantities of each type of currency. For example, if over the course of the day the sum of all transactions causes SafeBank to have a net increase in USD and a net decrease in EUR, they will give the excess USD to CLS and CLS will return the equivalent amount of EUR. CLS charges SafeBank a small percentage on this exchange. This confines the risk to SafeBank to a single day (known as intra-day liquidity risk). If SafeBank runs out of any type of currency prior to 6:30pm ET, they can conduct a swap with one of their counterparties. This is essentially the same service provided by CLS, but it can occur anytime throughout the day. Swaps help mitigate risk, but they are expensive relative to CLS.
In addition to financial considerations, SafeBank is legally obligated to manage risk. If they are unable to support client transactions for any reason, it can cause a major disruption in the global financial market. Accordingly, they must prove to the government that they have sufficient cash on hand to avoid this situation across a range of stressing scenarios. Choosing the amount of each type of currency to keep on hand is a difficult problem. Students will be asked to simulate system activity (e.g., cash flows from transactions, swaps, and settlements) in order to find the profit maximizing quantities subject to acceptable risk. This will include analysis of revenue, cost, and risk. These analyses will be completed across a range of scenarios including:
The judging was based on:
For more detail, see the Contest Judging Criteria.
Angelo Innamorato |
Bonnie Yue Simulation Developer at Clearpath (Canada) |
Ed Williams Senior Technical Specialist at PMC and Lecturer II, Business Analytics at College of Business, University of Michigan – Dearborn (USA) |
Ernest Bhero Advocate of the High Court of South Africa & a Professional Engineer at University of KwaZulu Natal (South Africa) |
Laura Silvoy Healthcare Systems Engineer at Array Architects (USA) |
Luis Enrique Herrera Del Canto Associate Professor at the Monterrey Institute of Technology (Mexico) |
Mustafa Gocken Assistant Professor at Adana Science and Technology University (Turkey) |
Paolo Renna Professor in Manufacturing and Production Systems at University of Basilicata (Italy) |
Chinnatat Methapatara Operations Research Advisor at FedEx Corporation (USA) |
Raul Zuniga PHd at Universidad Arturo Prat (Chile) |
Radu F. Babiceanu Associate Professor of Systems Engineering at Embry-Riddle Aeronautical University (USA) |
Dr. C. Dennis Pegden Founder and CEO |
Christine Watson Senior Application Engineer |
Anthony Innamorato Senior Consultant |