← Back to browse
Good practice
Imported
DGII's AI Anomaly Detector — Flagging Irregular Patterns in the Dominican Republic's Billion-Invoice E-Invoicing System
Dominican Republic
· Santo Domingo
· See the Dominican Republic profile
· See the Santo Domingo profile
Evidence: Descriptive / self-reported
Top 83%
40/100
· Ask Evidence Copilot about this practice
The Dominican Republic's tax authority added an AI anomaly detector to its e-invoicing system, which has processed over 1 billion electronic tax receipts. It flags simulated or unusual invoicing patterns for audit, but no independent fraud-catch figures are published.
1,000,000,000+
Electronic fiscal receipts processed (e-CF) (2023–Aug 2025)
8,000+
Registered electronic invoicing emitters and receivers (as of Aug 2025)
Details
Maturity Scaling
Promoter Dirección General de Impuestos Internos (DGII)
Period 2023–present (AI detector added 2025)
Keywords taxation, fraud detection, digital government, e-invoicing
Context
The Dominican Republic made electronic invoicing mandatory nationwide under Law 32-23 (effective May 2023). By August 2025, the tax authority DGII had processed over 1 billion electronic fiscal receipts (e-CF) from more than 8,000 registered electronic emitters and receivers. In 2025, DGII added an AI-based 'Detector de Anomalías en Facturación Electrónica' on top of this dataset, which analyses invoicing patterns to flag simulated transactions, atypical volumes and other fiscal-risk signals for human inspectors to review.
Implementation
Indicative cost Medium (€50k–€500k)
Time to results Short (< 1 year)
Staffing & skills DGII Technology Manager (technical/AI oversight), Fiscal inspectors (review flagged cases)
Conditions for success
Mature underlying e-invoicing dataset (mandatory nationwide since Law 32-23, 2023) Integration with existing audit/inspection workflow Ongoing tuning of anomaly-flagging patterns as fraud tactics evolve
Commonly funded by
National / regional programmes
Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.
Do you run this practice?
Claim it —
verified implementers get a public contact pathway and can propose corrections.
Data sources
Where this practice's information was retrieved from, and when.
Attachments
Quality score: 40/100
How is this calculated?
Evidence: Descriptive / self-reported
Top 83%
in this catalogue (512 scored practices)
Scores cluster high, so position within the catalogue is often more telling than the number alone.
Evaluation
Evaluated by C-NAPSE
Score profile — the dimensions behind the score — how it's computed
Evidence of impact / measured public value 1/3
Officials describe the detector's function and it runs atop 1B+ real invoices, but no fraud-caught, false-positive, or revenue-recovered figures specific to the AI layer have been published.
Transparency, fairness & accountability 1/3
Named officials (Eusebio García, Luis Valdez Veras) speak publicly about the tool, but its scoring methodology and any appeal process for flagged taxpayers are undisclosed.
Transferability / demonstrated replication 1/3
The detector is built directly on DR's own Law 32-23 e-invoicing infrastructure; it is cited as a regional model but no other tax authority is confirmed to have replicated it.
Scalability beyond pilot 2/3
It already operates across the full national e-invoicing base of 1B+ receipts and 8,000+ electronic emitters, well beyond a pilot.
Governance, capability & sustainability 1/3
The tool sits within DGII's broader 'Tax Administration 3.0' digitalization plan, but no independent oversight body or data-protection review specific to the AI component is documented.
Cite this
Evidoria. DGII's AI Anomaly Detector — Flagging Irregular Patterns in the Dominican Republic's Billion-Invoice E-Invoicing System . Persistent ID: e01ba55f-b5f8-4fb5-92ca-6e40f29ca068.
Export as decision brief (PDF)
Similar practices you may find useful
★ 73
Hungary
Hungary requires all businesses to report invoices to NAV in real-time XML since 2021; ML risk-scoring targets suspicious companies before …
★ 53
Angola
Angola's tax authority AGT used AI to cross-reference e-invoices and import records, flagging 15,000 of ~40,000 firms that filed zero-revenue …
★ 40
Algeria
Algeria's customs authority launched ALCES, a clearance platform whose risk module uses AI to flag import/export fraud risk. It processed …
★ 87
Malaysia
Bank Negara Malaysia (BNM) and PayNet's National Fraud Portal (April 2024) links 53 institutions via FNA graph analytics to trace …