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AI title searches miss key title issues in 40.8% of cases
A DataTrace analysis of 200 residential title files found involuntary liens were missed at a failure rate above 36%, and public-record-only AI also could not search 16 files due to missing title-plant data.
HousingWire reports that a DataTrace analysis tested whether artificial intelligence relying only on fragmented county public records can meet the accuracy and completeness needs for insurable residential title decisions.
According to the report, AI missed at least one meaningful title matter in 40.8% of the 200 files when compared with searches supported by DataTrace’s structured title plant data. The largest gaps involved higher-risk issues, including involuntary liens, where the issue fail rate exceeded 36%.
DataTrace also found that public-record-only AI could not run searches for 16 of the 200 files because they lacked title-plant data or comparable normalized datasets required to complete the work.
HousingWire says the company estimated maximum potential liability of $489 billion and probable liability of $148 billion tied to missed title matters, and it emphasized that producing an insurable title decision requires tasks beyond retrieving records, such as validating ownership history and applying underwriting judgment.