In determining how prudent a company's risk management is, we look for evidence that management has historically anticipated potential company-specific or market-related setbacks and has taken necessary actions to ensure sufficient liquidity. Rating Model for Kurimoto, Ltd.: We estimate the credit risk parameters by Modified (Smoothed) Moving Average and ANOVA Credit Ratings for Kurimoto, Ltd. as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba1 Semantic Signals 47 78 Financial Signals 64 78 Risk Signals 47 76 Substantial Risks 51 88 Speculative Signals 78 40 *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.

Given the earnings volatility companies experience, we have specified for these issuers a more stringent decline in EBITDA percentage for each liquidity category to the extent our cash flow forecasts are not already assuming a downside scenario. Rating Model for Japan Post Insurance Co Ltd: We estimate the credit risk parameters by Ichimoku Cloud (IKH) and Pearson Correlation Credit Ratings for Japan Post Insurance Co Ltd as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba3 Semantic Signals 32 69 Financial Signals 36 52 Risk Signals 37 38 Substantial Risks 88 79 Speculative Signals 83 79 *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.

Other factors we consider include a company's frequency of debt issuance and market access, especially during times of company-specific stress or credit market turbulence. Rating Model for Peoples Bancshares, Inc.: We estimate the credit risk parameters by Average True Range (ATR) and Multiple Regression Credit Ratings for Peoples Bancshares, Inc. as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B1 Semantic Signals 50 50 Financial Signals 54 67 Risk Signals 34 88 Substantial Risks 83 45 Speculative Signals 36 30 *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.

Shared facilities with captive finance entities. When an issuer has a shared revolving credit facility with a captive finance entity, for purposes of calculating the issuer's liquidity sources, we net outstanding commercial paper at the captive from the revolver's borrowing availability. In these cases, we generally use an estimate of peak CP borrowings at the captive to avoid potentially overstating sources available to the issuer over a 12- to 24-month period. Rating Model for SOTSU CO., LTD.: We estimate the credit risk parameters by Price and Lasso Regression Credit Ratings for SOTSU CO., LTD. as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B3 Semantic Signals 57 52 Financial Signals 32 38 Risk Signals 32 47 Substantial Risks 82 63 Speculative Signals 53 32 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results

In determining how prudent a company's risk management is, we look for evidence that management has historically anticipated potential company-specific or market-related setbacks and has taken necessary actions to ensure sufficient liquidity. Rating Model for Kaman Corporation Common Stock: We estimate the credit risk parameters by Pearson-Anson Oscillators and Ridge Regression Credit Ratings for Kaman Corporation Common Stock as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba1 B1 Semantic Signals 81 46 Financial Signals 85 41 Risk Signals 80 70 Substantial Risks 56 62 Speculative Signals 54 82 *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.

For these reasons, although the criteria establish no rating threshold for liquidity, we typically expect: Instances of 'B+' and below rated issuers achieving liquidity descriptors higher than adequate to be rare and Few companies to qualify for the exceptional category, and these entities to typically have issuer credit ratings of 'BBB-' or above. Rating Model for BANK OF BEAVER CITY: We estimate the credit risk parameters by Armstrong Oscillator and Wilcoxon Rank-Sum Test Credit Ratings for BANK OF BEAVER CITY as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B2 Semantic Signals 39 35 Financial Signals 32 86 Risk Signals 85 58 Substantial Risks 35 35 Speculative Signals 71 39 *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.

We do not include potential future debt issuances as a source of liquidity because of the uncertainty of a company's ability to access debt markets in times of financial stress, even for investment-grade issuers. For instance, in the case of a proposed financing, with the intended use of proceeds to repay existing debt, we will assess a company's liquidity excluding the proposed financing until it's obtained or fully underwritten. Rating Model for Matador Resources Co: We estimate the credit risk parameters by Volume and Sign Test Credit Ratings for Matador Resources Co as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba3 Semantic Signals 59 45 Financial Signals 62 46 Risk Signals 31 61 Substantial Risks 46 80 Speculative Signals 77 76 *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

While we only include contractual acquisitions when calculating A/B and A-B, when evaluating qualitative factors, we focus more on a company's track record and our expectation for financial management. In this respect, the quantitative and qualitative factors under the liquidity criteria are meant to complement each other and produce a more comprehensive view of a company's future liquidity position. Rating Model for P&L Development Holdings, LLC: We estimate the credit risk parameters by Directional Movement Indicator and Wilcoxon Sign-Rank Test Credit Ratings for P&L Development Holdings, LLC as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B3 B2 Semantic Signals 32 41 Financial Signals 38 63 Risk Signals 37 51 Substantial Risks 77 37 Speculative Signals 73 82 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the res

While we only include contractual acquisitions when calculating A/B and A-B, when evaluating qualitative factors, we focus more on a company's track record and our expectation for financial management. In this respect, the quantitative and qualitative factors under the liquidity criteria are meant to complement each other and produce a more comprehensive view of a company's future liquidity position. Rating Model for Zhejiang Xinhua Chemical Co Ltd: We estimate the credit risk parameters by Ring Oscillators and Simple Regression Credit Ratings for Zhejiang Xinhua Chemical Co Ltd as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba2 Semantic Signals 87 44 Financial Signals 46 87 Risk Signals 80 68 Substantial Risks 30 61 Speculative Signals 73 83 *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 N

Asset divestitures. We do not include asset sales as a source of liquidity unless they are contracted and proceeds will be received in the time period being measured under the liquidity descriptor (even when the disposed assets are reported under discontinued operations in a company's financial statements). Rating Model for Envision Bank: We estimate the credit risk parameters by Commodity Channel Index and Wilcoxon Rank-Sum Test Credit Ratings for Envision Bank as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B2 Semantic Signals 87 58 Financial Signals 44 61 Risk Signals 47 50 Substantial Risks 82 55 Speculative Signals 50 52 *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.

While we only include contractual acquisitions when calculating A/B and A-B, when evaluating qualitative factors, we focus more on a company's track record and our expectation for financial management. In this respect, the quantitative and qualitative factors under the liquidity criteria are meant to complement each other and produce a more comprehensive view of a company's future liquidity position. Rating Model for US Bancorp Del Dep Shs Repstg 1/1000th Perp Pfd Ser H: We estimate the credit risk parameters by Running Moving Average (RMA) and Wilcoxon Rank-Sum Test Credit Ratings for US Bancorp Del Dep Shs Repstg 1/1000th Perp Pfd Ser H as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 B2 Semantic Signals 51 48 Financial Signals 79 79 Risk Signals 65 52 Substantial Risks 46 35 Speculative Signals 72 56 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utiliz

The EBITDA declines companies would have to withstand and still have defined sources cover defined uses are as follows for each liquidity descriptor: Adequate: Positive A-B, even if forecasted EBITDA declines by 30%.Weak: A/B or A-B reflecting a material deficit over the next 12 months. Rating Model for Empire HealthChoice Assurance Inc.: We estimate the credit risk parameters by EMR and Paired T-Test Credit Ratings for Empire HealthChoice Assurance Inc. as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba1 Semantic Signals 85 79 Financial Signals 52 84 Risk Signals 57 53 Substantial Risks 42 60 Speculative Signals 79 80 *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.

Given that it can be difficult to identify outstanding CP at any point in time, when considering coverage, we may include our expectations for peak outstanding CP during the year as opposed to CP balances as of the last filing date, especially if we believe reported balances are not reflective of typical borrowing patterns. Rating Model for Blackrock Municipal 2020 Term Trust: We estimate the credit risk parameters by Adaptive Moving Average and ANOVA Credit Ratings for Blackrock Municipal 2020 Term Trust as of 26 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 62 79 Financial Signals 39 55 Risk Signals 32 49 Substantial Risks 61 57 Speculative Signals 89 58 *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.

For companies in more volatile sectors, we assess the resiliency of liquidity through a cycle. If we do not believe the resulting descriptor reflects sustainable liquidity characteristics, we could adjust our liquidity assessment downward. For example, we could lower our liquidity assessment on a volatile company to strong from exceptional if we believe key quantitative measures typical of exceptional liquidity are not sustainable over the forecast period. This could especially be true if we believe there is a higher prospect of ratios weakening from the peak of an economic cycle. Rating Model for Planar Systems, Inc.: We estimate the credit risk parameters by Opto-Electronic Oscillators and Multiple Regression Credit Ratings for Planar Systems, Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 B1 Semantic Signals 72 72 Financial Signals 32 38 Risk Signals 45 51 Substantial Risks 85 57 Speculative Signals 83 64 *Machine Le

We do not exclude cash that the company needs to maintain to run the business and meet potential working capital requirements. Since working capital outflows are included under uses (B) of liquidity, system-related cash needed to run the business should be included in sources, along with items such as customer advances. Rating Model for YAMATO INDUSTRY CO., LTD.: We estimate the credit risk parameters by KDJ and Wilcoxon Sign-Rank Test Credit Ratings for YAMATO INDUSTRY CO., LTD. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 B1 Semantic Signals 41 43 Financial Signals 86 79 Risk Signals 70 39 Substantial Risks 87 68 Speculative Signals 54 71 *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.

Given that it can be difficult to identify outstanding CP at any point in time, when considering coverage, we may include our expectations for peak outstanding CP during the year as opposed to CP balances as of the last filing date, especially if we believe reported balances are not reflective of typical borrowing patterns. Rating Model for Confluent Health, LLC: We estimate the credit risk parameters by Ichimoku Cloud (IKH) and Simple Regression Credit Ratings for Confluent Health, LLC as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 Baa2 Semantic Signals 87 85 Financial Signals 36 76 Risk Signals 82 88 Substantial Risks 59 42 Speculative Signals 83 79 *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.

Other factors we consider include a company's frequency of debt issuance and market access, especially during times of company-specific stress or credit market turbulence. Rating Model for Shiseido Americas Corporation: We estimate the credit risk parameters by Meissner Oscillators and Beta Credit Ratings for Shiseido Americas Corporation as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Baa2 B1 Semantic Signals 88 39 Financial Signals 73 71 Risk Signals 63 57 Substantial Risks 69 90 Speculative Signals 81 35 *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.

Shared facilities with captive finance entities. When an issuer has a shared revolving credit facility with a captive finance entity, for purposes of calculating the issuer's liquidity sources, we net outstanding commercial paper at the captive from the revolver's borrowing availability. In these cases, we generally use an estimate of peak CP borrowings at the captive to avoid potentially overstating sources available to the issuer over a 12- to 24-month period. Rating Model for Main Street Capital Corporation: We estimate the credit risk parameters by Opto-Electronic Oscillators and Logistic Regression Credit Ratings for Main Street Capital Corporation as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B2 Semantic Signals 61 42 Financial Signals 39 59 Risk Signals 83 50 Substantial Risks 33 30 Speculative Signals 56 64 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our res

For new issuers, while our ratings are prospective, we will not include proposed financing as a source in our liquidity calculations until the financing has been obtained or is fully underwritten. Similarly, we would not include rights issues as a source of liquidity for a company, unless the rights issue is irrevocably guaranteed (for example, an underwriter agrees to buy any securities not taken up by existing holders). Rating Model for PSS Industrial Group Corp.: We estimate the credit risk parameters by Exponential Moving Average (EMA) and Multiple Regression Credit Ratings for PSS Industrial Group Corp. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba1 Semantic Signals 49 69 Financial Signals 80 79 Risk Signals 60 76 Substantial Risks 80 83 Speculative Signals 56 47 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the res

Other factors we consider include a company's frequency of debt issuance and market access, especially during times of company-specific stress or credit market turbulence. Rating Model for Premier Brands Group Holdings LLC: We estimate the credit risk parameters by Bollinger Bands Width and Spearman Correlation Credit Ratings for Premier Brands Group Holdings LLC as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 B2 Semantic Signals 87 30 Financial Signals 82 82 Risk Signals 46 50 Substantial Risks 52 55 Speculative Signals 80 32 *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.

For these reasons, although the criteria establish no rating threshold for liquidity, we typically expect: Instances of 'B+' and below rated issuers achieving liquidity descriptors higher than adequate to be rare and Few companies to qualify for the exceptional category, and these entities to typically have issuer credit ratings of 'BBB-' or above. Rating Model for American Bancorp Inc.: We estimate the credit risk parameters by Exponential Moving Average (EMA) and ANOVA Credit Ratings for American Bancorp Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B1 Semantic Signals 34 72 Financial Signals 81 34 Risk Signals 62 33 Substantial Risks 39 66 Speculative Signals 61 72 *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.

We do not treat repayments of leases as debt maturities (even if International Financial Reporting Standard 16 shows them as such in the cash flow statement) because we already have reduced FFO by such lease cash outflow. Rating Model for BATTLE CREEK STATE COMPANY, INC.: We estimate the credit risk parameters by Voltage Controlled Oscillator and Wilcoxon Sign-Rank Test Credit Ratings for BATTLE CREEK STATE COMPANY, INC. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B3 Semantic Signals 53 38 Financial Signals 51 54 Risk Signals 53 35 Substantial Risks 79 32 Speculative Signals 37 48 *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.

For these reasons, although the criteria establish no rating threshold for liquidity, we typically expect: Instances of 'B+' and below rated issuers achieving liquidity descriptors higher than adequate to be rare and Few companies to qualify for the exceptional category, and these entities to typically have issuer credit ratings of 'BBB-' or above. Rating Model for Perfect World Co Ltd: We estimate the credit risk parameters by Rating and Spearman Correlation Credit Ratings for Perfect World Co Ltd as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 Ba3 Semantic Signals 41 89 Financial Signals 76 38 Risk Signals 43 82 Substantial Risks 90 58 Speculative Signals 34 50 *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.

The various qualitative factors in the criteria help to identify strengths and weaknesses within a company's future liquidity position that numerical ratios might not fully capture. While there is no size bias in our liquidity assessment, generally, lower-rated entities might meet the quantitative requirements for strong or exceptional liquidity but fail to meet corresponding qualitative factors. Rating Model for BEXIMCO PHARMACEUTICALS LIMITED: We estimate the credit risk parameters by Rating and ElasticNet Regression Credit Ratings for BEXIMCO PHARMACEUTICALS LIMITED as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Ba3 Semantic Signals 65 44 Financial Signals 63 89 Risk Signals 36 49 Substantial Risks 59 51 Speculative Signals 68 88 *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 Supp

We do not treat repayments of leases as debt maturities (even if International Financial Reporting Standard 16 shows them as such in the cash flow statement) because we already have reduced FFO by such lease cash outflow. Rating Model for Westinghouse Air Brake Technologies Corporation Common Stock: We estimate the credit risk parameters by Triple Exponential Moving Average (TRIX) and Wilcoxon Rank-Sum Test Credit Ratings for Westinghouse Air Brake Technologies Corporation Common Stock as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 B1 Semantic Signals 82 57 Financial Signals 34 81 Risk Signals 50 39 Substantial Risks 69 40 Speculative Signals 79 66 *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.

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. Rating Model for CSG Systems International, Inc.: We estimate the credit risk parameters by Clapp Oscillators and Paired T-Test Credit Ratings for CSG Systems International, Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Ba3 Semantic Signals 85 57 Financial Signals 56 65 Risk Signals 38 30 Substantial Risks 58

Larger, investment-grade issuers that have access to both public and private debt markets have greater flexibility than companies that depend solely on private bank loans. In addition, we consider whether a company can borrow on an unsecured basis, has access to the commercial paper markets, and issues debt in multiple geographies. It is more costly to raise debt in the public bond markets and often requires a company to establish a track record among investors. These costs and information asymmetry issues sometimes make it impractical for smaller, speculative-grade issuers to raise small amounts of debt in public markets. Rating Model for StanCorp Financial Group, Inc. Common Stock: We estimate the credit risk parameters by Crystal Oscillators and Polynomial Regression Credit Ratings for StanCorp Financial Group, Inc. Common Stock as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B1 Ba3 Semantic Signals 43 36 Financial Signals 57 71 R

because of strategic positioning, operational performance, organizational effectiveness, risk and financial management, and governanceIf we believe a company would use cash trapped at a foreign subsidiary to meet debt maturities or other liquidity uses at that foreign subsidiary, we would include this cash as a source of liquidity up to the amount of the corresponding use. We generally haircut the cash to be included under sources when a material proportion of a group's cash is held in a different part of the structure than where the debt is located, and we believe the cash may not be fully fungible within the group. Rating Model for Genworth Holdings, Inc.: We estimate the credit risk parameters by RRS and ElasticNet Regression Credit Ratings for Genworth Holdings, Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 Ba3 Semantic Signals 69 33 Financial Signals 83 81 Risk Signals 37 57 Substantial Risks 84 55 Speculative S

If we believe a company would use cash trapped at a foreign subsidiary to meet debt maturities or other liquidity uses at that foreign subsidiary, we would include this cash as a source of liquidity up to the amount of the corresponding use. We generally haircut the cash to be included under sources when a material proportion of a group's cash is held in a different part of the structure than where the debt is located, and we believe the cash may not be fully fungible within the group. Rating Model for Tecta America Corp.: We estimate the credit risk parameters by Bollinger Bands and Pearson Correlation Credit Ratings for Tecta America Corp. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba3 Baa2 Semantic Signals 54 70 Financial Signals 79 61 Risk Signals 66 79 Substantial Risks 76 86 Speculative Signals 55 77 *Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we util

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 15:55:04 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model If a company has a credit put that causes debt acceleration or collateral posting due to a downgrade of three notches or less, we would include these requirements under uses of liquidity, per paragraph 30 of the liquidity criteria. For example, if a 'BBB' rated company had a credit put that was triggered with a downgrade to speculative grade, we would include the corresponding cash requirement under uses of liquidity. This is because the criteria evaluate a company's liquidity position during times of stress, when potential downgrades are more likely. Rating Model for China State Const. Eng. Corp Ltd: We estimate the credit risk parameters by Simple Moving Average (SMA) and Linear Regression Credit Ratings for China State Const. Eng. Corp Ltd as of 25 Jan 2022 Credit

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 15:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Larger, investment-grade issuers that have access to both public and private debt markets have greater flexibility than companies that depend solely on private bank loans. In addition, we consider whether a company can borrow on an unsecured basis, has access to the commercial paper markets, and issues debt in multiple geographies. It is more costly to raise debt in the public bond markets and often requires a company to establish a track record among investors. These costs and information asymmetry issues sometimes make it impractical for smaller, speculative-grade issuers to raise small amounts of debt in public markets. Rating Model for Discovery Communications, Inc.: We estimate the credit risk parameters by Price Channels and Stepwise Regression Credit Ratings for Discovery Communic

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 14:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model Under times of stress, such actions could include dividend cuts, suspension of share repurchases, or maintenance of minimum cash balances. This is particularly relevant for exceptional and strong assessments, where issuers are required to carry higher levels of excess liquidity even during times of stress. For example, when assessing liquidity, we would generally expect companies to be able to cover the full amount of dividends and share repurchases included in our base-case forecast, while still maintaining excess liquidity and achieving the required A/B and A-B measures under a stress case. Rating Model for Core Bank: We estimate the credit risk parameters by SMoothed Moving Average (SMMA) and Wilcoxon Rank-Sum Test Credit Ratings for Core Bank as of 25 Jan 2022 Credit Rating

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 14:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model While the existence of a commercial paper (CP) program can provide companies with alternative sources of short-term funding, such a program would not be considered a committed source of liquidity. Additionally, we do not require the presence of a committed facility to back up the full size of the CP program. For liquidity to be at least adequate, an issuer would need sources of liquidity (for example, committed facility and/or cash balances) to cover at least 100% of expected intra-year debt maturities, including CP, over the next 12 months. Rating Model for Pimco Corporate & Income Opportunity Fund: We estimate the credit risk parameters by Heikin-Ashi and Factor Credit Ratings for Pimco Corporate & Income Opportunity Fund as of 25 Jan 2022 Credit Rating Short-Term

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 13:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model While the existence of a commercial paper (CP) program can provide companies with alternative sources of short-term funding, such a program would not be considered a committed source of liquidity. Additionally, we do not require the presence of a committed facility to back up the full size of the CP program. For liquidity to be at least adequate, an issuer would need sources of liquidity (for example, committed facility and/or cash balances) to cover at least 100% of expected intra-year debt maturities, including CP, over the next 12 months. Rating Model for Novavax, Inc.: We estimate the credit risk parameters by Price Channels and Sign Test Credit Ratings for Novavax, Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* B2 B2 Semantic Sig

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 12:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model 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. Rating Model for Central Depository Services (India) Limited: We estimate the credit risk parameters by Rating and Multiple Regression Credit Ratings for Central Depository

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 11:55:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model In this scenario, we would still include the existing debt maturity as a use of liquidity in our A/B and A-B calculations, if the debt matures within the corresponding liquidity horizon. The rationale is that our liquidity assessment is essentially a stress test against a sudden and severe loss of capital markets access availability. For companies with an anchor of at least 'bbb-' that meet certain characteristics, as outlined in paragraphs 38 and 39 of the criteria, we may use a shorter three- to six-month time horizon when assessing upcoming maturities. Rating Model for Saturday Co Ltd: We estimate the credit risk parameters by Price Oscillator (PPO) and Factor Credit Ratings for Saturday Co Ltd as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Ra

BOSTON (AC Invest Credit Rating Terminal) Tue Jan 25 2022 11:25:02 GMT+0000 (Coordinated Universal Time) AI Credit Ratings today took the rating actions below: Credit Rating Rationales & Model We do not treat repayments of leases as debt maturities (even if International Financial Reporting Standard 16 shows them as such in the cash flow statement) because we already have reduced FFO by such lease cash outflow. Rating Model for j2 Global, Inc.: We estimate the credit risk parameters by Expectation and Spearman Correlation Credit Ratings for j2 Global, Inc. as of 25 Jan 2022 Credit Rating Short-Term Long-Term Senior AI Rating Class* Ba2 B1 Semantic Signals 73 80 Financial Signals 57 82 Risk Signals 67 31 Substantial Risks 67 57 Speculative Signals 83 50 *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