# Regulatory transaction reporting reconciliation (EMIR, MiFIR)

> Regulatory transaction reporting reconciliation (EMIR, MiFIR): Reported vs booked trades; fields right Checked: proven by code. Produces breaks, resubmissions.

Source: https://www.sumarity.ai/library/regulatory-transaction-reporting-reconciliation/

Legal and compliance 

# Regulatory transaction reporting reconciliation (EMIR, MiFIR)

Reads regulatory reports, the trade books. Produces breaks, resubmissions. Code works out every figure, the Judgement Engine answers the narrow questions, and whatever stays uncertain goes to a person.

Proven by codeFilings, returns and reporting
Start from this workflowMore for legal  

What it decides

## Narrow questions, each with a check behind it.

Reported vs booked trades; fields right
Proven by code. Code proves the answer from the data itself: totals tie, a match is exact, the quote is on the document. Most of these judgements settle without a person.

| Reads | Regulatory reports, the trade books 
| Produces | Breaks, resubmissions 
| Who signs | A person on your team, with every figure traced to its document and every call on record 
| Process | Filings, returns and reporting 
| Industry | Legal and compliance    

See it run

## Every line, decided where it's safest.

An example run. Each stage lights up as a line is decided there; pick a stage to see its lines.

ReadsRegulatory reports, the trade booksCodeReads, matches, ties out and works out every figure.JudgementReported vs booked trades; fields right. Settles only when it clears the cutoff and code proves it.A personGets whatever stays uncertain, with the evidence. Their ruling tunes the next run.ProducesBreaks, resubmissions  
Regulatory transaction reporting reconciliation (EMIR, MiFIR) · example run Example run  

| Ref | Item | Value | Decided by  
| EM-1201 | Swap 5512 reportedFields match the trade |  | Code · matched 
| EM-1202 | Counterparty LEILapsed LEI, renewed since · 0.92 |  | Engine · proven 
| EM-1203 | Trade not reportedBooked, missing from the report |  | Code · missing 
| EM-1204 | Notional differsPartial termination not reported? |  | To a person 
| EM-1205 | Venue fieldOTC, correct · 0.95 |  | Engine · proven  
|  

Settled 4 To a person 1 Settled wrong 0      Illustrative lines. Amber rows are the Judgement Engine's calls; each settles only above its cutoff and when its check agrees.    

What it could save

## Your volumes in. Your hours out.

In our tests, between 24% and 42% of items still went to a person after tuning. Set your own share; a pilot measures it on your data.

Items per run 
Runs per month 
Minutes per item by hand 
Cost per hour

Share of items that still need a person: 30%  

By hand today80 ha month 
With Sumarity24 ha month, for the items people decide 
Saved56 hCHF 53,760 a year    

Related

## Start from what's closest.

### Filings, returns and reporting in other work

Accounting firms

### UK VAT return for a small business (pub VAT)

Each document's VAT treatment; what's missing

Proven by codeTestedAccounting firms

### Swiss VAT (MWST) return

Rate and method per line; input tax recoverable

Proven by codeAccounting firms

### German VAT advance return (USt-Voranmeldung)

Treatment per line, reverse charge

Proven by code

### More for legal

### Contract review against the playbook

Clauses present, deviations, risk

Proven by code

### Legal invoice review against billing guidelines

Fees and expenses allowed

Proven by code  

Questions

## What buyers ask

What happens when Sumarity isn't sure?

Nothing settles below the cutoff, or when the check disagrees. The item goes to a person in the inbox with what the engine saw, its best answer and the runner-up. The person's ruling is kept and tunes the next run.

How are its judgements checked?

Code proves the answer from the data itself: totals tie, a match is exact, the quote is on the document. Most of these judgements settle without a person.

Can we change it to fit how we work?

Yes. Start from this workflow and describe your differences in plain words. The design assistant revises it, the validator checks it, your expert reviews it on the canvas, and your admin publishes it.

Does it read our files as they are?

Yes: spreadsheets and CSV in any layout, PDFs, bank formats and e-mail attachments. Sumarity suggests how each column maps, proves the mapping on a sample and remembers it once a person confirms it.

Where does our data go?

Sumarity runs in Zurich. Your data, backups and logs are stored in Switzerland.

How does it get better?

Your team's rulings become an answer key. Better questions and cutoffs are proposed, tested on data they haven't seen, and published only when your admin approves. It improves itself, with permission.

## Start from this workflow. Run it on your data.

A pilot runs alongside your own process for a few weeks, at our cost, and ends in a line-by-line comparison.

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