Interview: How do SCOR and ReMark improve the customer experience and automate claims processing with VClaims?
SCOR y ReMark están transformando el sector de los seguros centrándose en mejorar la experiencia del cliente, la automatización de los procesos y la innovación digital a través de VClaims. Sophie Chapelain, Directora de Selección de Riesgos de SCOR L&H Francia, y Jérémy Speed, Director de Europa de ReMark, SCOR Digital Solutions, arrojan luz sobre los cambios trasformadores que podemos anticipar en el sector asegurador gracias a una mejor gestión de los siniestros para los clientes de seguros.
¿Cómo estás contribuyendo a la transformación del mundo de los seguros?
Jeremy Speed: SCOR, through its subsidiary ReMark (SCOR Digital Solutions), puts the customer at the heart of the insurance business. Our day-to-day work consists of simplifying and improving insurance products. By combining our expertise in risk management with our experience in customer engagement, we offer comprehensive digital solutions across the entire customer journey. We automate and optimise underwriting and claims processes, paving the way for a proactive, inclusive and convenient customer experience. Finally, we emphasise a human, personalised approach in all our interactions with our customers and partners. Whether it's through data analysis, honing our digital innovation strategies or developing our risk prevention expertise, we're committed to building strong, ethical partnerships with an emphasis on human relationships.
In your opinion, how is it possible to improve the customer experience at the claims level, particularly in life and health insurance?
Sophie Chapelain: Claims processes have not yet benefited from the same degree of digitalisation, optimisation and automation as underwriting processes. There's a striking contrast between the two, and it's all the more glaring when the same customers and insurance products are involved. The technology available today and the expertise acquired in personal insurance products are excellent levers for rethinking the claims process.
We emphasise a human, personalised approach in all our interactions with our customers and partners. Whether it's through data analysis, honing our digital innovation strategies or developing our risk prevention expertise.
Jeremy Speed Head of Europe, ReMark, SCOR Digital Solutions
In concrete terms, how can insurers benefit from this?
Jeremy Speed: In line with our ongoing success in medical selection via Velogica, number 1 in France for over ten years, we are now offering a white-label 'E-claims API' to facilitate claims declarations, particularly for work stoppages. Our solution, "VClaims", simplifies this process by combining automated decisions and simplified requests for supporting documents, making claims declaration more accessible and efficient for our partners and policyholders.
The technology available today and the expertise acquired in personal insurance products are excellent levers for rethinking the claims process.
Sophie Chapelain Head of Risks Selection, SCOR L&H France
Aside from improving the customer experience, what's in it for the insurer?
Sophie Chapelain: It significantly speeds up claims processing times and reduces the number of incomplete files. This optimization is achieved by asking for the right information from the outset, thanks to our rules engine, by using simple questions to increase the quality of customer responses, and by limiting manual errors thanks to automated data entry. Our solution, which, like the one we have developed for pricing, instantly proposes a decision to managers: here again, this saves processing time and ensures consistency in the decisions made.
How can such a solution be a strategic advantage for an insurer?
Jeremy Speed: It helps refine pricing, underwriting and reserving policies, thanks to improved structuring of claims data. Our solution can be coupled with other functionalities, such as an "augmented" document download area with OCR and fraud detection modules, and with the use of AI to improve rules and develop predictive models.