Greifenberg Risk Analytics Modules
Basic Module
Filter 1
Greifenberg Financial Score (based on annual and quarterly balance sheet and income statements)
Filter 2
Machine-learning algorithm assigns weights to more than 40 financial-reporting items and identifies pointers to credit distress or default
Filter 3
Daily-updated Contingent Claims Analysis (Merton model) of default probability using equity prices, equity volatility, and balance sheet data to measure default probability
Filter 4
Reliability of Financial Reporting with Big Data
– M-score Big Data compares each obligor’s reporting to peer group and assigns a reliability ranking
– Greifenberg’s proprietary Big Data algorithm detects possible reporting anomalies
Enhanced Module (includes Basic Module plus)
– Natural Language Processing of News and Social Media
– Portfolio optimization that includes both Credit Value at Risk and minimize tail risk due to default probabilities
– Beta testing of geographic expansion and additional model functionality