RiceBran Technologies Credit Rating

BOSTON (AI Credit Rating Terminal) Thu Jul 30 2020 17:19:03 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Rating Action Overview


We downgraded RiceBran Technologies because of a weaker market position, higher risk, or more confidence-sensitive mix of business is only partially offset by any strengths, and this leads us to expect weaker revenue stability relative to peers, thus demonstrating modest incremental risk above what is captured in the anchor. We use econometric methods for period (n+1) simulate with Trend Pearson Correlation. Reference code is: 4108. Beta DRL value REG 15 Rational Demand Factor LD 4496.259599999999. Additionally, we exclude revolver borrowing availability that we believe would be inaccessible due to covenant constraints. For revolving credit facilities with extension options, we include the extension period(s) under sources of liquidity only if the option is at the discretion of the borrower. If lenders have the option to terminate commitments at each extension point, we only include the borrowing availability under the facility up to the first extension date. Credit Rating AI Process rely on primary sources of information: Sec Filings, Financial Statements, Credit Ratings, Semantic Signals. Take a look at Machine Learning section for Financial Deep Reinforcement Learning.Oscillators are used for generating credit risk signals by using the semantic and financial signals. The value of the oscillators indicate the strength of trend. Using the correlation matrices, the credit rating risk map for RiceBran Technologies as below:

Credit Ratings for RiceBran Technologies as of 30 Jul 2020


Credit Rating Short-Term Long-Term Senior
AI Rating Class*B1B2
Semantic Signals4777
Financial Signals8330
Risk Signals3167
Substantial Risks8335
Speculative Signals4742

*Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from the Neural Network and Support Vector Machines.
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