evidoria

← Back to browse

Good practice Imported

Ernst — Trelleborg's Automated Welfare Caseworker Cuts Social-Assistance Decisions From Days to Minutes

Sweden · Trelleborg · See the Sweden profile

Evidence: Observational / pre–post Top 62% 53/100 · Ask Evidence Copilot about this practice

Trelleborg's automated caseworker 'Ernst' cut social-assistance decisions from days to under a minute; OECD found overall case time fell from 10 days to 24 hours and a vendor study reports 94% faster processing, but an audit found 250 citizens' data exposed since 2017.

~10 days -> within 24 hours
Case-handling time
94%
Processing-time improvement (vendor)
22%
Additional citizens served with 2 fewer staff
~70%
Online-channel usage share
~250 citizens (names + national ID numbers)
Citizens' data exposed since 2017

Details

Maturity
Scaling
Promoter
Trelleborg Municipality (Trelleborgs kommun)
Period
2015–2018
Keywords
social welfare, digital government, robotic process automation, public administration

Context

Trelleborg became the first Swedish municipality to fully automate decisions on reapplications for social assistance, digitalising benefit administration from 2015 and introducing a rules-based automated case handler, 'Ernst', from 2016, pulling data from seven agencies to approve, adjust or forward cases.

Results

The OECD found overall case-handling time fell from roughly 10 days to within 24 hours; UiPath's case study puts the improvement at 94%, with the municipality serving 22% more citizens using 2 fewer front-line staff; roughly 70% of applicants now use the online channel. Vinnova and SALAR used Trelleborg's model as the basis for a rollout to 14 further municipalities.

Conclusions

AlgorithmWatch's Automating Society project found the decision logic ran to 136,000 lines of rules across 127 XML files, difficult to audit, and separately found roughly 250 citizens' names and national ID numbers had been left exposed in the source code since 2017.

Implementation
Indicative cost
Low (< €50k) — Rules-based RPA system (UiPath); low set-up cost relative to hiring additional caseworkers, per the vendor's own cost comparison.
Time to results
Medium (1–3 years) — Digitalisation began 2015; automated case handler 'Ernst' introduced 2016; since replicated in 14 more municipalities via Vinnova/SALAR.
Staffing & skills
front-line social-assistance caseworkers (reduced by 2 through automation), municipal IT/RPA team

Conditions for success

  • data integration with 7 external agencies (tax authority, student loan board, etc.)
  • high online-application channel adoption (~70%)

Common failure modes

  • 136,000 lines of rules across 127 XML files difficult to audit
  • ~250 citizens' names and national ID numbers exposed in source code since 2017

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.

Similar practices you may find useful