The omni:us Digital Claims Adjuster enables seamlessly integrated end-2-end claims automation within existing insurance systems.
Integrated reference claims processes and a comprehensive, AI-powered claims decision catalogue, help reduce process costs by up to 35 percent – while drastically increasing customer satisfaction and efficiency.
Out-of-the-box reference processes allow rapid implementation and optimized claims processing
Pre-trained AI & rule models make complex settlement decisions to process claims in an automated manner – and alert adjusters to red flags that require human attention.
Easy integration with major core & legacy systems to access relevant policy and claims information.
The omni:us Digital Claims Adjuster enables seamlessly integrated end-2-end claims automation within existing insurance systems.
Integrated reference claims processes and a comprehensive, AI-powered claims decision catalogue, help reduce process costs by up to 35 percent – while drastically increasing customer satisfaction and efficiency.
Out-of-the-box reference processes allow rapid implementation & optimized processing by simply adapting them to the your needs.
Pre-trained AI & rule engines make complex claims decisions, provide next-best-action recommendations & alert adjusters if human attention is required.
Standardized connectors into all relevant core insurance platforms , including legacy applications.
No longer is it a choice between saving costs and improving the customer experience.
Better decisions with data driven insights. Automate manual processes.
Empower your claims personnel. Invest in your customers’ happiness.
With omni:us.
Scale Document uses machine learning to automatically classify documents and apply OCR transcription. Combined with our human-in-the-loop workflow, SLA turnarounds can be as fast a few hours to meet business requirements.
Scale Document can anonymize personally identifiable information (PII) with name blurring or the placement of dummy names to ensure compliance with data privacy principles from a range of international privacy regimes.
Scale Document can anonymize personally identifiable information (PII) with name blurring or the placement of dummy names to ensure compliance with data privacy principles from a range of international privacy regimes.
Rely on available omni:us connectors to reduce IT efforts, e.g. for Guidewire ClaimCenter.
Library of claims workflow, adjudication checks and AI-Models to get started quickly.
Rely on available omni:us connectors to reduce IT efforts, e.g. for Guidewire ClaimCenter.
Automate claims and enable decision support as per your business requirements.
Expand robust & stable modules
within your enterprise architecture.
Build end-to-end claims journeys
by combining AI modules.
Automate claims and enable decision support as per your business requirements.
Expand robust & stable modules
within your enterprise architecture.
High impact process & decision automation from FNOL to claim resolution.
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“Automated categorization of incoming documents & structured data extraction, is essential when it comes to process optimization.
Thanks to the technology developed by omni:us, we will be able to make our core business even better throughout all country subsidiaries.”
“To meet today’s customers’ expectations insurance carriers must not digitize existing claims processes but radically reinvent them.
Our investment comes with the strong conviction that omni:us’ outstanding team and cutting-edge AI will deliver unprecedented customer experience by pairing expertise, efficiency and empathy”
omni:us is the leading provider of AI-powered End-2-End insurance claim automation. We are here to deliver the ultimate claims experience: for policy holders, as well as claims adjusters with adaptive processes to deliver speed, instant feedback & transparency, whilst drastically reducing process costs and reducing leakage across all channels.
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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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