Live Demo
AI-powered leakage service

Identification of
potential recovery claims

No integration effort.
Realisation within few weeks.

Discover the efficiency revolution in recovery processing with omni:us’ AI-powered Leakage Service.
Our solution combines advanced AI with deep industry understanding to identify hidden recovery potential automatically and efficiently – without integration effort and thus even under intense time pressure and with a lack of specialised personnel.

Have you ever thought about claims recovery?

0 %
of all claims are not recovered on industry average
  • Recovery identification is complex
  • Many insurance companies have a shortage of qualified staff
  • Time pressure of employees often prevents sufficient recovery identification
Up to€ 0 M
Annual
savings potential
with omni:us 1)
  • No integration effort: An analysis of the closed cases is sufficient
  • Potential analysis within 2 weeks
  • Realisation within 8 weeks
    (depending on the number of claims)

1) A German insurance company with approx. 130,000 composite claims and a GWP of EUR 2.3 billion serves as a reference. Average claim amount € 2,923.-

It’s that simple

In two easy steps
to new savings

Step 1

Potential Analysis

  • Automated "closed file review" of approx. 1,000 claims with subsequent comparison to the realised recovery rate
    AI
  • Calculatory identification of the potential
Step 2

Implementation

  • Claims from the past 3 years are analysed by omni:us
    AI
  • The identified recovery claims are then handed over to the insurer (minus the list of recovery claims that were previously recognised manually by the insurer)
  • These additionally identified recovery claims are processed and claimed by the insurer
0
Integration effort

An analysis of the closed cases
is sufficient

< 0 weeks
Realisation time

Depending on the number
of analysed claims

Lines of Business/risks offered
Household/Property
Storm/Elemental

Tap Water
Motor & third party liability
Business case example

Recovery claims can be made up to 3 years after the damage.

Number of claims per year (with focus on glass, tap water, storm, motor vehicle)
0
Share of unidentified
recourse receivables
0 %
in numbers
1’560

Annual savings potential
with omni:us

Up to € 0 M
Key focus of the AI-powered recovery service
recovery for

Negligence

The deliberate violation of reasonable precautions is regarded as gross negligence and can lead to recovery claims by the insurer. One example is causing an accident under the influence of alcohol.

Recovery claim for

proven intent

If the policyholder intentionally causes damage, this may mean that the insurance company is not obliged to pay for the damage. If it does so anyway and recognises the intentional act at a later date, this may result in a subsequent right of recovery.

 

Violation of

Insurance conditions

If damage is caused by a breach of safety regulations or legal provisions, this can also lead to recovery claims.

 

Division-specific questions for property, as well as motor comprehensive and liability insurance, are added as required.

Live Demo

Experience the AI-powered recovery service in action..

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relied on by leading insurers

"omni:us AI settles 70% of the submitted claims end-2-end, without manual intervention."

Wolf Gerlach
Board Member Operations
UNIQA

"We already produce millions of dollars of gross written premium – new business for us, just through this technology.”

Ariel Gorelik
COO
AmTrust Financial

“There were no structured data inputs required for getting to as much as 80% automation level just by using the technology omni:us has in place.”

Andreas Nemeth
General Partner
UNIQA Ventures

“Thanks to the technology developed by omni:us, we will be able to make our core business even better throughout all country subsidiaries.”

Adrian Honegger
Lead Group Strategy & Digital Transformation

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omni:us is proud to be one of Europe‘s Horizon2020 SME-Instrument and Fet Flag Champions.
We are grateful to have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 820323; 850053.

Co-financed by European Fund for Regional Development (EFRE)
Pro Fit-Project “Vollautomatisierung der Wertschöpfungskette im Digitalisierungsprozess von Archivdaten” with support of IBB/EFRE in 2016/2017.

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