Kawasaki Kisen Kaisha, Ltd. Credit Rating

BOSTON (AI Credit Rating Terminal) Fri Jul 31 2020 16:49:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below:

Rating Action Overview


We downgraded Kawasaki Kisen Kaisha, Ltd. because explicitly excluded by regulation from those liabilities that may be bailed in if the obligor enters a bail-in resolution. We use econometric methods for period (n+1) simulate with Profit Spearman Correlation. Reference code is: 1809. Beta DRL value REG 35 Rational Demand Factor LD 4294.2522. If, for example, a facility matured in 18 months, we could include the borrowing availability as a source of liquidity in year one, but exclude the amount in year two under the exceptional and strong descriptors (as well as include any drawn portions as debt maturities under uses of liquidity). This is because we do not assume an extension of bank lines--regardless of the company's perceived credit strength or issuer credit rating. For instance, whether the issuer credit rating on the company is speculative grade or investment grade, we do not assume bank lines will be extended beyond the current stated maturity. 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 Kawasaki Kisen Kaisha, Ltd. as below:

Credit Ratings for Kawasaki Kisen Kaisha, Ltd. as of 31 Jul 2020


Credit Rating Short-Term Long-Term Senior
AI Rating Class*B3B2
Semantic Signals8871
Financial Signals4146
Risk Signals4432
Substantial Risks3536
Speculative Signals5080

*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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