Greifenberg Digital Limited Launches Credit AI, an Innovative AI / Big Data Corporate Bond Analysis Suite Focused on the Chinese Market

HONG KONG and NEW YORK, Dec. 27, 2021 / PRNewswire / – Greifenberg Digital, a member of the IMTE Group, today launched Credit AI, a revolutionary risk analysis suite for corporate bonds with an initial coverage universe of nearly 30,000 Chinese corporate bonds in local currency. Analyzes are provided via the Internet on an interactive website.

“We have performed comprehensive retrospective testing, including rigorous out-of-sample testing,” said Uwe Parpart, Managing Partner of Greifenberg. “Our system has provable predictive value for from China corporate bond market. And he performed particularly well in anticipating distress in from China real estate bond sector.

“The volatility of from China High yield bond market over the past year underscores the need for better navigation tools, ”added Parpart. “We set out to create the state of the art in credit risk management for China and possibly many other corporate bond markets. “

The new system includes an innovative financial rating model, a machine learning algorithm that detects the risk of default in companies’ financial reports, an artificial intelligence model to assess the likelihood of anomalies in balance sheets and corporate accounts. corporate earnings, and a potential claims analysis model that derives default risk from real-time stock and options market data.

In addition, Greifenberg uses natural language processing, a form of artificial intelligence analysis of news and social media to assess changes in opinion about corporate bond issuers. The NLP system currently covers the full range of public sources in Chinese and will be accessible to website users in January 1st.

Greifenberg also offers matrix pricing for lightly traded bonds. This methodology allows investors to identify opportunities for profit in the less liquid part of the Chinese corporate bond universe. Greifenberg’s proprietary matrix pricing model identifies benchmark bonds from the liquid universe and estimates the fair value of illiquid bonds by comparing the risk characteristics of illiquid bonds with the characteristics of comparable liquid instruments. The matrix pricing system provides a benchmark for the relative value of a large part of the from China onshore bond universe.

Additionally, Credit AI provides a portfolio management system that calculates value at risk and expected loss given default for corporate bond portfolios. The portfolio module translates the risk measures of each bond into a probability of default 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,” Parpart explained. “We have introduced real innovations, notably 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 full spectrum of market signals, from stock market volatility anomalies track record to social media commentary, and extract risk and relative value signals that portfolio managers can use in a timely manner. “

The Greifenberg site is now accessible to institutional investors. Along with the launch of the analytics website, Greifenberg released a white paper detailing the performance of the analytics suite during the August Chinese real estate bond crisis.October 2021. “To a large extent, the upheaval in from China corporate bond market was predictable. In this white paper, we examine the cases of defaults in the Chinese corporate bond market that caused the crisis in real estate and other credit. In most cases, default events were accurately predicted by Greifenberg’s combination of credit scoring tools, ”the white paper says.

The Greifenberg team includes Uwe Parpart, former research director of the Réorient Group and Asia strategy at Bank of America (Hong Kong); David Goldman, former head of bond research at Bank of America and developer of widely used quantitative lending models; Jerry lucas, former chief interest rate strategist at Bank of America and Deutsche Bank; and Michael peng, who built credit models for JP Morgan, Bank of America Merrill Lynch, and Boston Consulting Group.

About Greifenberg Digital Limited (“Greifenberg”)

Greifenberg is a Canadian company engaged in the field of credit research on from China fixed income market. Greifenberg has developed an innovative suite of AI / Big Data corporate bond analysis focused on the Chinese market. For more information, please visit

About Integrated Media Technology Limited (“IMTE”)

IMTE is an Australian company engaged in the manufacture and sale of nano-coated filter plates, the manufacture and sale of electronic glass, and financial research. For more information, please visit

Safe Harbor Declaration

This press release contains certain statements which may include “forward-looking statements”. All statements other than statements of historical fact included in this document are “forward-looking statements”. unknown risks and uncertainties. Although the Company believes that the expectations reflected in these forward-looking statements are reasonable, they 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 actual results of the Company could differ materially from those anticipated in these forward-looking statements due to various factors, including those discussed in the Company’s periodic reports which are filed with the Securities and Exchange Commission and available on its website ( All forward-looking statements attributable to the Company or to persons acting on its behalf are expressly qualified in their entirety by these factors. Except as required by securities laws, the Company assumes no obligation to update these forward-looking statements.

SOURCE Integrated Media Technology Limited

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