How did the Latvian tax authority use data analytics for smarter tax administration?

The challenge

The State Revenue Service – or SRS – in Latvia launched an ambitious program to make it easier to pay taxes and optimize the tax administration process. A key part of this process was the consolidation, modernization and simplification of technologies that SRS and citizens use every day.

The total volume of tax payments handled by SRS was approximately 10 billion Euro in 2020. After assessing a range of technologies and providers at the end of the previous year, the organization agreed to improve its analytics capabilities by adopting SAP HANA. However, there were several major infrastructure obstacles lying in the way.

Many of the databases that SRS relied upon for analytics (some of which included redundant information) had been built on different platforms, which created a lot of manual work. Data exchanges or updates had to follow the Extract, Transform, Load (ETL) process and this led to delays in making new data available.

In some cases, it would take several days or even a week before the new information could be analyzed. With legacy analytical capabilities, there were also only limited opportunities to apply automation, machine learning (ML), fuzzy logic or other contemporary approaches to data analytics.

All of these infrastructure challenges meant long waiting times for updated data, poor business continuity for the multiple public bodies that relied on SRS data, and higher chances of fraud. Tax Risk Reports would take up to four weeks to produce and this resulted in missed prevention activities. Meanwhile, due to typically lengthy lead times for analytics reports, SRS tax specialists had only a few days to complete their tasks – adding extra pressure on the workforce.


SRS appointed Emergn to support a smooth migration to SAP HANA and implement better Data & Analytics capabilities. Despite working closely with SRS since 1995, we still needed to demonstrate we were competitive, understood how the organization operated, and could build out a proof of concept (PoC) to reassure other stakeholders of the merits of change.

Following our principles of VFQ (Value, Flow, Quality), we started with a sandbox test environment to run an experiment. We took one small SRS process and ran a PoC that would demonstrate value early and often. During this initial activity, we continually gathered feedback from SRS business and IT team members to check that the experiment was delivering value.

After a successful pilot, we set up a full environment based on a concept that we created by working hand-in-hand with the SRS team. The transition to SAP HANA is a multi-year project and so this was imperative for understanding the key priorities for each stage.

The project has already seen notable progress. We have integrated the entire business logic of calculating taxpayer ratings into the SAP HANA Rule Framework. This enables business users to adjust or replace any parameters as needed rather than waiting for centralized changes. Fraud control algorithms are now included as Business Rules and, with SAP HANA Smart Data Integration, SRS can virtually integrate multiple sources of data without using ETL processes. Plus, with the SAP BusinessObjects universe, users can organize information into a simple business layer and produce Web Intelligence reports that visualize taxpayer evaluation indicators.

Now that we are using SAP HANA, data selection works instantly.

SRS business user

Our impact

The transition to SAP HANA is not a big bang approach. But by following Emergn’s VFQ principles, SRS is able to create value at every step.

To-date there have been five significant benefits for SRS:

1. Instant data updates

Instead of once-a-month updates, users now have near real-time access to data with automated processing and the capability to introduce ML analytics. This offers more flexibility in managing the SRS Taxpayer Rating Systems, which in turn enables SRS to better understand taxpayers and reduce any errors when providing services.

2. Business continuity for SRS clients

On January 1, 2021 Latvia introduced the most radical reforms to the tax system in decades. A single tax account replaced the previous 40 different accounts that taxpayers had been using. The SRS SAP HANA platform ensures that all of the other public agencies that rely on its tax data receive a faster and uninterrupted service.

3. Better fraud detection

Since moving to SAP HANA, the SRS has reduced lead times in the fraud detection process from nearly a month to a matter of minutes. High-risk or suspicious transactions are instantly flagged and potential fraud can be averted. With the ability to perform a wider range of data analyses on the same information, the SRS can implement modern approaches and user-friendly visualizations.

4. Faster reporting

Previous lead times for analytical reports were around four weeks. These are now just a day and new types of reports can be created with little effort. Any new or additional information that is required can easily be set up using the intuitive SAP HANA controls.

5. Simplified infrastructure

With SAP HANA as the central platform, SRS users have online access to all core SRS systems and databases. Data can be uploaded from a centralized toolset and segregation is available, while redundant information is simple to remove. This unified platform for data integration, analytics, applications and microservices gives SRS the future-proofed infrastructure it needs as Latvia’s taxation system continues to evolve.

In minutes

Fraud detection, reduced from 1 month

Real time

Data access, compared to monthly update

1 day

New reports, previously 4 weeks

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