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