Greifenberg Digital Limited launches Credit AI, an innovative AI/Big Data suite of corporate bond analytics focused on the Chinese market
Greifenberg Digital, part of IMTE Group, launched Credit AI, a sophisticated suite of risk analytics focused on nearly 30,000 Chinese local-currency corporate bonds. The system features advanced tools such as a financial scoring model, machine-learning algorithms, and Natural Language Processing to assess default risks and gauge sentiment about bond issuers. With rigorous testing indicating proven predictive value, Credit AI aims to enhance credit risk management in China's volatile bond market. The service is available to institutional investors, supported by a White Paper detailing its performance.
- Launch of Credit AI, a suite of risk analytics for nearly 30,000 Chinese corporate bonds.
- Innovative tools including machine learning and Natural Language Processing for assessing default risks.
- Proven predictive value demonstrated through extensive back testing.
- Support for institutional clients through comprehensive analytics and portfolio management.
- None.
HONG KONG and NEW YORK, Dec. 27, 2021 /PRNewswire/ -- Greifenberg Digital, a member of the IMTE Group, today launched Credit AI, a groundbreaking suite of risk analytics for corporate bonds with an initial coverage universe of nearly 30,000 Chinese local-currency corporate bonds. The analytics are delivered via Internet on an interactive website.
"We've done comprehensive back testing, including rigorous out-of-sample tests," said Uwe Parpart, Greifenberg's managing partner. "Our system has provable predictive value for China's corporate bond market. And it performed particularly well in forecasting distress in China's property bond sector."
"The volatility in China's high yield bond market during the past year underscores the need for better navigational tools," Parpart added. "We set out to create the state of the art in credit risk management for China and, eventually, many other corporate bond markets."
The new system includes an innovative financial scoring model, a machine-learning algorithm that detects default risk in corporate financial reporting, an Artificial Intelligence model to assess the probability of misstatements in corporate balance sheets and income statements, and a Contingent Claims Analysis model that derives default risk from real-time equity and option market data.
In addition, Greifenberg uses Natural Language Processing, a form of Artificial Intelligence analysis of news and social media to gauge changes in sentiment about corporate bond issuers. The NLP system presently covers the whole spectrum of Chinese-language public sources, and will be available to website users by January 1.
Greifenberg also offers matrix pricing of infrequently-traded bonds. This methodology allows investors to identify profit opportunities in the less liquid part of the Chinese corporate bond universe. Greifenberg's proprietary matrix pricing model identifies reference bonds from the liquid universe and estimates the fair value of illiquid bonds by comparing the risk characteristics of illiquid bonds to the characteristics of comparable liquid instruments. The matrix pricing system provides a reference point for relative value for a large part of China's onshore bond universe.
In addition, Credit AI provides a portfolio management system that calculates Value at Risk and expected loss from default for corporate bond portfolios. The portfolio module translates the risk measurements of each bond into a default probability and uses the correlation of bond performance to calculate risk at the portfolio level.
"The whole of our analytic suite is greater than the sum of the parts," said Parpart explained. "We have introduced some true innovations, especially in the application of machine learning to credit analysis and in Natural Language Processing. But what makes the system so robust is the combination of diagnostic tools. We process the entire spectrum of market signals, from balance sheet anomalies to equity market volatility to social media commentary, and extract risk and relative value signals that portfolio managers can use in a timely fashion."
The Greifenberg website is now available to institutional investors. Along with the inauguration of the analytics website, Greifenberg released a White Paper detailing the performance of the analytics suite during the Chinese property bond crisis of August-October 2021. "To a great extent, the shakeout in China's corporate bond market was predictable. We examine in this White Paper the case histories of defaults in the Chinese corporate bond market that prompted the distress in property and other credit. In most cases, default events were forecast accurately by Greifenberg's combination of credit valuation tools," the White Paper states.
Greifenberg's team includes Uwe Parpart, former head of research at Reorient Group and of Asia strategy at Bank of America (Hong Kong); David Goldman, former head of fixed income research at Bank of America and developer of widely-used quantitative credit models; Jerry Lucas, former chief interest-rate strategist at Bank of America and Deutsche Bank; and Michael Peng, who has built credit models for J.P. Morgan, Bank of America Merrill Lynch, and Boston Consulting Group.
About Greifenberg Digital Limited ("Greifenberg")
Greifenberg is a Canadian company engaged in the business of the credit research on China's fixed income market. Greifenberg has developed an innovative AI/Big Data suite of corporate bond analytics focused on the Chinese market. For more information, please visit www.greifenbergcapital.com.
About Integrated Media Technology Limited ("IMTE")
IMTE is an Australian company engaged in the business of the manufacture and sale of nano coated plates for filters, the manufacturing and sale of electronic glass and financial research. For more information, please visit www.imtechltd.com.
Safe Harbor Statement
This press release contains certain statements that may include "forward-looking statements." All statements other than statements of historical fact included herein are "forward-looking statements."These forward-looking statements are often identified by the use of forward-looking terminology such as "believes," "expects" or similar expressions, involve known and unknown risks and uncertainties. Although the Company believes that the expectations reflected in such forward-looking statements are reasonable, they do involve assumptions, risks, and uncertainties, and these expectations may prove to be incorrect. You should not place undue reliance on these forward-looking statements, which speak only as of the date of this press release. The Company's actual results could differ materially from those anticipated in these forward-looking statements as a result of a variety of factors, including those discussed in the Company's periodic reports that are filed with the Securities and Exchange Commission and available on its website (http://www.sec.gov). All forward-looking statements attributable to the Company or persons acting on its behalf are expressly qualified in their entirety by these factors. Other than as required under the securities laws, the Company does not assume a duty to update these forward-looking statements.
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FAQ
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