– Case Study –
Text Annotation for Financial Risk Assessment
Global Insurance Services Firm Required Text Annotation of Earnings Call Transcripts and SEC Filings to Build AI Capability for Financial Risk Assessment
A leading global insurance services company had a goal of building an AI platform that could automatically evaluate companies and perform corporate risk assessment. For the AI platform to identify the critical information and events that informed the evaluations and assessments, training data of SEC filings and earning call transcripts was required.
Automated Corporate Risk Assessment
To ensure that our client would receive the highest quality datasets for training their AI platform, Innodata deployed SMEs with contextual knowledge of finance across 8 industries and multiple geographies. Once our client experienced the high level of quality our team was able to deliver, they doubled the volume and we scaled from 6 to 12 full time SMEs. These experts created a customized taxonomy to identify critical information and finance-related events within the financial documents and call transcripts. They also implemented an inter-annotator agreement process, in which two different annotators provide annotations and an adjudicator provides a judgement on any discrepancies between the annotations. This ensured that as hundreds of SEC filings and earning call transcripts were labeled with the highest accuracy.
With the delivery of high-quality training datasets, the AI platform was able to accurately conduct assessments of companies based on the data found in financial documents. This allowed a global leader in Insurance Services to perform automatic corporate risk assessments allowing them to stay ahead of their competitors and better serve their customers.
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