The Problem
The global credit information provider faced difficulties in its research, making it harder for the company to provide complete and timely credit assessments. IR analysts were spending a lot of time researching companies, which required a lot more than just looking at the surface.
Complicated research needs:
Extensive Media Research
Going beyond basic search results to look at many different media sources
Cross-Verification
Checking facts across different sources of information to make sure they are correct
Monitoring Subtle Changes
Keeping track of small changes that could affect credit decisions
Resource Intensive
Taking up a lot of analyst bandwidth and operational resources
Our Approach
Automated Information Collection
Using web and media research agent to automate information gathering
Intelligent Filtering System
Advanced filters based on sources and regions for organized information
Streamlined Data Compilation
Complete and accurate datasets for faster analysis and decision-making
Overcoming Implementation Challenges
First, the problem is that our web and media research agent did a good job of automatically gathering information, but the client needed an extra layer to check the credibility of the sources. Making financial decisions necessitates careful consideration.
Two-Tier Verification System:
Official Source Citation
To be credible at first, all information must come from official, verifiable sources.
Cross-verification
Each piece of information must have at least one additional, independent source that aligns with and confirms the data.
This dual-verification approach effectively eliminated unreliable information while presenting a clear, validated view of official company information that analysts could confidently use for credit decisions.
Our Strategic Approach
Comprehensive Source Network
To make sure we had all the relevant company information, our system accessed a lot of different media sources, official databases, and verified information channels.
Smart Data Validation
The automated verification system checked information from different sources against each other and made sure that the information was reliable enough for financial analysis.
Analyst Integration
The solution made analysts' jobs easier by giving them pre-verified, complete datasets that they used to have to put together and check by hand.
Business Impact
Decrease in time
The research process was reduced from more than 12 hours to less than 10 minutes per company, resulting in a 98% decrease in research time while still maintaining accuracy standards.
Resource Optimization
With AI on the groundwork, analysts had more time to focus on high-value analysis and decision-making activities.
Scalability Achievement
Allowed the client to significantly increase their research capacity without needing to hire more analysts, which helped the business grow and improved the client's ability to serve customers.
Quality Improvement
The rule-based authentication system made sure that the information was more reliable while still covering all the bases needed for accurate credit assessments.
Strategic Business Value
As a result, the client's research operations transitioned from a time-consuming manual process to an efficient automated system that provides accurate and complete company information in minutes rather than hours. helped them expand their research capabilities while keeping the high accuracy standards that are necessary for credit information services by using smart automation with strong credibility verification.
The 98% decrease in research time, along with better information reliability, allowed the client to serve more customers with quicker turnaround times while still making sure that credit decisions were thorough and accurate.
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