Fraud
187 whitepapers and resources
Fraud
Process automation momentum calls for real-time insurance fraud detection
In our fast-moving world, insurance customers demand real-time decisions. With automation and digitisation firmly on the agenda for insurers, this content highlights why investments in real-time risk assessment and fraud detection are required to modernise underwriting and claims processes.
Case study: Enterprise automation saves an insurer millions
EXL helped a leading insurance company achieve an end-to-end claims transformation leveraging RPA, data analytics and a claims center of excellence. Download this case study to find out how the insurer saved $21M of potential fraud and reduced average claims processing times by 40%.
Finding the value: The role of Communisis Ai in streamlining the insurance claims process
Analysing large volumes of unstructured, human-generated content can make the insurance claims process both time consuming and costly. Watch this video to discover how Communisis Ai is helping firms to reduce manual effort and quickly direct complex or potentially fraudulent claims to human agents.
FRISS customer story: Malta Insurance Association
This case study sheds light on how the Malta Insurance Association collaborated with FRISS to provide its members with a platform to share knowledge, potential fraud incidents and claims history. The platform’s adoption also resulted in a major fraud network being uncovered.
FRISS customer story: UNIQA Insurance Group AG
UNIQA Group is one of the leading insurance groups in Austria and Central and Eastern Europe. This case study looks at how UNIQA Group leveraged the FRISS Solution for automated claims fraud detection to achieve total fraud savings of €18.4 million within the first two years of being live.
How adding authorised media to the claims process prevents fraud and saves costs
In this content, Wouter Joosse, product manager at FRISS focuses on how insurers can leverage authorised media such as photo and video materials in the claims handling process in order to prevent fraud, save costs and speed up the process.
How the coronavirus pandemic impacted the insurance industry in both predictable and unexpected ways
Several months in, we can start to see how the coronavirus pandemic has affected the insurance industry and our customers. This content sheds light on claims trends and new policy requests both during and after lockdown, as well as the factors driving a rise in suspected fraud.
Commercial insurance: Fighting fraud with one hand tied behind our backs
Given the disparity in data gathered, is it any wonder that there is a migration of fraud from personal lines to the soft underbelly of commercial insurance? This content highlights how commercial insurers can better understand the ownership structures of organisations in order to combat fraud.
A view on the future of insurance fraud analytics
Now is the time for insurance companies to revolutionise their fraud analytics capabilities. Download this content to find out how insurers can leverage artificial intelligence to serve honest customers exceptionally fast, while instantaneously flagging bad risks for further investigation.
Keeping predictive fraud models accurate In exceptional times
Covid-19 proved that data science models have their shortcomings and can be less than reliable when deviations occur. In this content, Richard Bakker, head of data science for FRISS highlights the actions the business has taken to ensure its fraud fighting models are reaching optimal performance.