Creditinfo Group
English
Get a Clear Picture of the Current State of Your Data
Inaccurate data leads to inaccurate decisions. Eliminate errors by evaluating and boosting your data quality through a comprehensive review created by Creditinfo experts. Our skilled analysts and consultants will use a proven framework to review the data identifying weak points and areas for improvement. Report with findings and recommendations will be given to credit bureau along with a set of recommendations for each data provider submitting erroneous data with specific information on errors in their data and changes to be made to improve data quality.
get in touchHow can Data Quality Review benefit your credit bureau operations?
Impact of Your Data
Understand the impact of erroneous information on your products such as credit bureau reporting or scoring.
We Know Where to Find the Error
Identify main error types and financial institutions causing them.
Quality Credit Bureau Services
Dramatically increase confidence in credit bureau services.
Advanced Analytics
Lay a strong foundation for advanced analytics and credit bureau products.
Boost Data Quality
Design short and long term plans to boost data quality.
How does it work?
Skilled analysts and consultants will use a proven framework to review the data identifying weak points and areas for improvement. Report with findings and recommendations will be given to credit bureau along with a set of recommendations for each data provider submitting erroneous data with specific information on errors in their data and changes to be made to improve data quality. Creditinfo will also outline areas where no change is required with the benefit of an independent confirmation that the current data quality is appropriate.
Subjects’ Data Quality
Evaluation of the quality of personal information of subjects from Id fields to demographic information.
Contracts’ Data Quality
Analysis of the data quality within one snapshot and its consistency against previous snapshot(s) (logical checks of amounts, statuses and phases).
Subject Matching Efficiency
To evaluate the performance of existing matching rules – does current matching algorithm allows the system to identify unique customers submitted by different data providers.
Search Efficiency
Percent of successful searches and breakdown by subscribers. Search parameters commonly used, success rate. Identification of the sources of unsuccessful queries.
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