Example: Investment banking

Algorithmics have taken a pragmatic approach to modeling the processes in operations
and measuring and modeling the exposures and expected losses associated
with processing the transactions in a financial firm (Figure 13.2). This provides a
consistent, relevant, and meaningful measure for day-to-day operations and executive
decision making. The explanation of the rationale behind capital allocation, loss avoidance measures, and loss-mitigation measures using this methodology will
benefit from its sound theoretical base. Subjective models and ad hoc rare events
can be added, subject to the individual client’s specification.