Abstract: Systems and methods for contingency NAV pricing are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for contingency Net Asset Value (cNAV) pricing may include (1) receiving a daily Net Asset Value (NAV) for a fund and performance data for a plurality of benchmarks; (2) selecting one of the plurality of benchmarks that has a benchmark performance that is similar to a fund performance of the fund for a period of time; (3) determining a correlation factor between the fund performance and the selected benchmark performance; and (4) calculating a cNAV based on a prior day's NAV for the fund, a movement for the selected benchmark, and the correlation factor in response to a daily NAV for the fund being unavailable.

Abstract: Systems and methods for hierarchical dual-dynamic exception management are disclosed. In one embodiment, the system and method may provide: (1) hierarchical exception modelling, metric algorithms and aggregation; (2) node level exception metric algorithm and high-level status algorithm calculation; (3) node level investigation via “explain” of exception factors (e.g., focusing an analyst on a particular issue); (4) node level tracking workflow management through ability to add commentary, multiple-person signoff, and high-level status calculation overrides; (5) visibility, auditable compliance reporting; (6) dashboard for internal operational analysts/managers with full investigation view; (7) dashboard for external clients with sub views; (8) generic data interface to existing workflow management system; and (9) machine learning component such that the exception metric can be intelligently re-adjusted (for example, if there are too many false positives then make the thresholds more forgiving).