IS WORK OVER?

Automation index

How much of a Insurance underwriter’s job can AI already do?

A form and a rating come earlier. Saying no to a risk you cannot see does not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Insurance underwriter

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Forms, rating and terms.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Analyse risk, claims and reinsurance.
Estimate

No public source provides a precise figure. This is our estimate.

16%32%+5.1
Brokers, agents and negotiation.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Surveys, clauses and exclusions.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Rules, reserves and documentation.
Estimate

No public source provides a precise figure. This is our estimate.

18%16%+2.9
Not taking a risk that sinks the company.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%25%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Forms, rating and terms
  • Analyse risk, claims and reinsurance
  • Brokers, agents and negotiation
  • Surveys, clauses and exclusions
  • Rules, reserves and documentation
  • Not taking a risk that sinks the company
  • suscriptor de seguros
  • underwriter

Sources for this job· O*NET 13-2053.00· ESCO/ISCO 3321

Last-mile manager

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Zones, capacity and route cuts.
Estimate

No public source provides a precise figure. This is our estimate.

16%44%+7
KPIs, first attempt and incidents.
Estimate

No public source provides a precise figure. This is our estimate.

16%36%+5.8
The courier, the lobby and the one who will not open.
Estimate

No public source provides a precise figure. This is our estimate.

18%16%+2.9
Peaks, rain and hiring too many or too few.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The angry customer and not dressing delivered.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Cover the peak, and not leaving the neighbourhood orphaned.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%26%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • delivery zones
  • first attempt
  • delivery KPIs
  • last-mile peaks
  • lobbies
  • delivery incidents
  • courier capacity
  • cut routes

Sources for this job· O*NET 11-3071.00· ESCO/ISCO 1324

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