With the Dataiku Solution for Reconciliation, set up your choice of matching strategies, test approaches and automate to reduce the volume of manual reviews.
Once defined, you can automate in a matter of clicks and send regular notifications of new records ready for review or approval via integrated, automated reporters.
Your process experts benefit from a dedicated interface to manage all pending matches, add comments and apply sign-off for auditability.
Thanks to the matching strategies implemented, they focus on where their expertise is needed, and new matches can become new running rules in your reconciliation strategies.
With an integrated and automatic cell-level audit trail, ensure transparency for every manual adjustment and streamline manual verification.
Every interaction with a manually matched record is written to an audit log separated from the final matched dataset, automatically creating the ideal compliance proofpoint.
Get all the summary metrics and data quality insights you need to evaluate how many records require manual review and their current status.
Integrated analytics show your current matching logic, allowing for improvements to clear more matches automatically without impacting quality.
Go the extra mile: Quickly create multiple reconciliation engines tailored to each business process — from trade matching and entity resolution to billing management. Easily enrich upstream strategies through integration of LLMs in data extraction, process mining to uncover systematic bottlenecks, and more.
A composite organization in the commissioned study conducted by Forrester Consulting on behalf of Dataiku saw the following benefits:
reduction in time spent on data analysis, extraction, and preparation.
reduction in time spent on model lifecycle activities (training, deployment, and monitoring).
return on investment
net present value over three years.