I Can’t Get No Satisfaction – With My Claims
Satisfaction surveys in claims reportedly show that customers expect a speedy, intuitive technology platform as well as process transparency. That means the digital redesign of a claims journey needs to go much deeper than superficial process improvements.
As McKinsey explains, Adeslas, a Spanish company, has worked to complete an end-to-end digitisation of their claims journey, implementing features such as multichannel First Notification of Loss (FNOL), automated claims segmentation, and digital claims status tracking.
McKinsey says that digital technologies can unlock value and improve the claims customer journey from start to finish. Claims leaders should be able to examine each step of the journey and develop an “aspirational future state for claims that is unconstrained by potential short-term, technological barriers.”
DOCOflow, for example, is an analytics tool that provides both a data driven “as-is” view of a technology system and processes and a smart claims processing engine. The technology provides a visual overview of the whole claim journey, highlighting claims throughput, processing time, and turnaround time.
The tool also identifies and provides metrics on the real routes through a system, class of business and handler level. It also discovers the happy paths and the bottlenecks for improved resource management. The ClaimsTech perfectly highlights how an AI smart claims engine detects claims suitable for automated processing.
The visualisation component of DOCOflow reveals patterns and trends vital for efficient resource management. The AI component will take the same data to create a supercharged version of Lloyd’s of London’s Small Claims Auto Settlement (SCAS). Going beyond a blunt rules engine, DOCOflow’s processing prediction algorithm will identify which claims are suitable for automated processing while it removes the need for human touchpoints on high volume\low value claims. It pushes beyond these touchpoints depending on the risk appetite.
As DOCOsoft has outlined in previous blogs, A.I. can help infer as-yet-unknown characteristics of a claim, such as the likelihood of fraud, total loss, or litigation, to speed up its downstream handling. McKinsey cites the example of a European insurance carrier, which significantly improved its fraud detection accuracy implementing an AI-based fraud detection system, resulting in an 18 per cent increase in fraud prevention, as well as productivity gains in fraud investigation.
It seems that leading players in the automotive sector can now estimate a vehicle’s damage value in real time at FNOL based on customer pictures or a damage description, using the latest advances in A.I. and picture recognition.
AI can support in finding the optimal claims handling process for a specific claim. McKinsey reports that a global insurance carrier, for example, leveraged AI to derive business rules to identify clear and simple claims cases suitable for an automated process. An Italian insurance carrier has developed a “best-match” routing approach to find the best-experienced claims handler for a specific case, and this way significantly improves its claims handling accuracy.
In another example, Allianz’s Global Digital Factory has created a digital delivery hub to achieve change through digital projects, such as developing claims solutions, across its international operations.
DOCOsoft has now established a substantial European footprint servicing multiple tier 1 global clients. Our technology offers a complete one stop shop claims management solution with integrated analytics and regulatory functionality, such as sanctions checking modules.
For more information on DOCOsoft’s global claims management solution, email Graham Sheppard, Head of London Operations: firstname.lastname@example.org