Trump hired executive for KC-based firm in failed search for $500m bond in fraud case
- Bias Rating
10% Center
- Reliability
70% ReliableGood
- Policy Leaning
10% Center
- Politician Portrayal
-32% Negative
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
-7% Negative
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
56% : He wrote that the team working for Trump reached out to "virtually every major surety" in the market and spent "countless hours" negotiating with one of the largest insurance companies in the world.49% : Trump, who effectively secured the Republican nomination for president last week, may go on trial in New York as early as April over charges related to hush money payments to an adult film actress during his 2016 campaign.
29% : If Trump is unable to obtain a bond by March 25, New York Attorney General Letitia James, a Democrat who brought the case against him, can begin to seek enforcement of the massive judgment against him.
27% : The civil fraud judgment against Trump is one in a string of civil and criminal cases against him.
26% : An executive of Lockton, one of the largest privately-held insurance brokerages, was hired by Trump to help him obtain a bond to cover the $464 million judgment entered against Trump, the Trump Organization and other defendants by New York Justice Arthur Engoron last month.
7% : Engoron found Trump had lied for years about his wealth.Lockton's northeast president, Gary Giuletti, in an affidavit filed in court on Monday, wrote that he and others had worked for weeks to try to obtain a bond for Trump.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.