01
Sources come in as they are
Files, database tables and webhook events are registered as data sources. Each one feeds a dataset, with no manual conversion.
NDD · Reconciliation at scale
More than 100 million records reconciled
NDD uses Nexus to reconcile more than 100 million records. Data comes in by file, database or webhook, the rule set matches both sides and every pair comes back with a decision and a score, with no manual queue for what already matches.
How the data moves
- 01Data sources
- 02Rule set
- 03Matching
- 04Pairs with a decision
- records reconciled
- 100M+
The challenge
Why it's hard.Reconciliation at scale.
Once an operation reaches millions of records, reconciliation stops being a rules problem and becomes a scale problem. The files are too big for a spreadsheet, the two sides live in different systems, and even a small exception rate turns into a queue nobody can work by hand. What solves it is a process that runs on its own for what matches and hands over only the mismatches.
Two datasets, one rule set
- Record 000184R$1,284.90Record 77A1R$1,284.90
- Record 000185R$312.00Record 77A2R$312.00
- Record 000186R$4,790.15Record 77A9R$4,790.51
- Record 000187R$96.40No match
Sample data.
How it works
How Openi solved it.In 3 steps.
- 02
The rule set compares both sides
Each dataset's fields become canonical keys, such as amount and document, and the rule defines what counts as a pair and with what score.
- 03
Only exceptions go to a person
Every pair comes back with a decision and a score. MATCH moves on; POSSIBLE and NO_MATCH are set aside for review.
For the team
What's in plain sight.No digging.
- Record with no pair on the other side
- Amount or date mismatch
- Pair below the minimum score
Demo
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