Customer Service Automation · Document Processing · Enterprise Knowledge Search · Risk Management
Mapfre wanted to improve customer experience and streamline insurance operations such as claims handling, risk assessment, underwriting support, document management, internal knowledge access, and digital content creation while keeping AI use governed responsibly.
Reported impact
Mapfre reports faster and more effective responses, streamlined internal and customer-facing processes, automated claims handling, stronger risk analysis, and improved digital engagement and satisfaction. Generative AI also increased visibility and traffic to digital channels.
Mapfre describes a portfolio of in-house and partner-supported AI systems embedded across insurance operations. Inputs include customer emails, vehicle damage images captured during policy issuance, claims data, rehabilitation information, insured-portfolio risk data, cyber-risk signals for SMEs, and internal knowledge sources such as product sheets, conditioning factors, and operations content. Processing is handled through deep learning, generative AI, and partner solutions including Shift for end-to-end home-claims automation in Brazil, ControlExpert for real-time vehicle-damage verification, Trak for AI-supported digital physiotherapy, Lobelia for climate-risk prediction, Cyberwrite for cyber-risk assessment, and MIA GPT for agency query resolution. Outputs are served into claims payments, underwriting and risk workflows, employee assistance, customer interactions, and digital marketing content. Governance is enforced through Mapfre's group AI governance model and Holistic AI for transparency, fairness, and risk mitigation.
Mapfre ingests customer emails, vehicle images, claims information, internal agency knowledge, and portfolio or cyber-risk data into AI services. Deep-learning and generative-AI components classify, verify, predict, or answer questions, then feed results into claims validation and payment, underwriting and risk assessment, rehabilitation monitoring, internal agency support, and digital content publishing.
"All AI solutions (both proprietary and third-party) are subject to the Mapfre Group’s AI governance model."
"Among the many uses we have for AI, we apply it to manage and understand customer emails, detect damage in images of vehicles when taking out a policy, and throughout the entire claims process, for example."
"Currently, the company has identified over 200 AI use cases and has more than 90 projects in development."
"Mapfre employs MIA GPT, a virtual assistant that streamlines the management of queries in its network of agencies and optimizes the resolution of questions related to specific topics"
"Mapfre has 75 use cases under study for the application of generative AI, nine of which are already underway and operational on a daily basis."
"This strategy has resulted in a more than 40% increase in the rate of access to both networks and search engines."
"This technology enables innovations such as automated content creation for digital platforms, efficient document management, and customer service through virtual assistants."
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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