SUSESO ML-Based Medical Insurance Claims Processing

Overview

Chile's Superintendencia de Seguridad Social (SUSESO), the social security and medical insurance supervisory agency, is developing and deploying machine learning models to assist its claims processing staff in handling a high volume of medical insurance claims. SUSESO's claims processing division has approximately 80 staff, some of whom are doctors and health specialists, who process approximately 200,000 medical insurance claims per year.

The World Privacy Forum (WPF) documented two distinct ML projects at SUSESO in its November 2024 report. First, a gradient boosting model to optimise management of medical leave claims, which was in the development phase as of that reporting. Second, classification trees for occupational mental health claims, which was already in operational use and undergoing a bias audit. Both models are managed by Rodrigo Moya, who heads SUSESO's Digital Transformation, Innovation and Project Unit in the Technology and Operations Department.

The governance context is significant and well-documented. Chile has developed an 'AI bidding template' through its ChileCompra public procurement system -- a government procurement tool that includes responsible AI criteria for assessing AI vendors. SUSESO's experience implementing this tool highlighted tensions between traditional procurement evaluation (cost, technical capability) and responsible AI assessment (fairness, discrimination risk, transparency). Kate Kaye, Deputy Director of WPF, published a follow-up article in April 2025 examining how Moya changed his perspective on the AI governance tool through the process of applying it to the medical insurance claims models.

When medical leave payments are denied, those decisions can and often do have life-changing effects on claimants, making the governance of the AI component a high-stakes question. The fact that SUSESO is conducting a bias audit on the operational classification tree model indicates awareness of these risks.

SUSESO is one of seven public institutions piloting GobLab UAI's (Universidad Adolfo Ibanez) Ethical Algorithms tools, as confirmed by an official SUSESO press release. The ethical tools applied to SUSESO's ML projects include an Algorithmic Impact Assessment, an Algorithmic Transparency Report Card, and a Bias and Equity Measurement framework. The audit process covers data sources, variables, parameters, bias, equity, transparency, accuracy, counterfactual analyses, and explainability mechanisms. Superintendent Pamela Gana and project manager Rodrigo Moya presented SUSESO's AI initiative at the second State Modernization Experience Exchange session (SIEME) organised by Chile's Ministry of Finance in October 2024.

Reporting by Diario Financiero (November 2024) provided additional detail on the scope of SUSESO's AI ambitions. The agency is developing six AI-enabled projects with a combined investment of approximately CLP $550 million, funded through State Modernization Secretariat grants and the Research and Development Agency. The flagship initiative is the predictive model to optimise medical license dispute resolutions, expected to integrate by mid-2025. A second project targets fraudulent medical licensing, described by Superintendent Gana as a tool to identify, investigate and sanction health professionals potentially issuing unfounded documents. Additional projects use NLP for claim classification and data analytics for systemic failure detection. Full implementation across all six initiatives is anticipated by Q1 2026.

SUSESO processes approximately 180,000 complaints annually, with medical licenses comprising approximately 70 percent of the caseload. The agency's engagement with responsible AI governance from the earliest stages of development -- including formal bias auditing, algorithmic impact assessment, and transparent procurement through ChileCompra -- makes this case notable as an example of proactive AI governance in a Latin American social protection institution.

Classification

Programme Details

ML-assisted medical insurance claims processing system used by SUSESO to help approximately 80 staff evaluate approximately 200,000 annual claims related to medical leave wages and occupational mental health costs.

Implementation Details

Risk & Oversight

Deployment & Outcomes

Sources

1. SRC-001-CHL-003 Kaye, K. (2024) 'AI Governance on the Ground: Chile's Social Security and Medical Insurance Agency Grapples with Balancing New Responsible AI Criteria and Vendor Cost', World Privacy Forum, 1 November. Available at: https://worldprivacyforum.org/posts/ai-governance-on-the-ground-chiles-social-security-and-medical-insurance-agency-grapples-with-balancing-new-responsible-ai-criteria-and-vendor-cost/ (Accessed: 30 March 2026).
   https://worldprivacyforum.org/posts/ai-governance-on-the-ground-chiles-social-security-and-medical-insurance-agency-grapples-with-balancing-new-responsible-ai-criteria-and-vendor-cost/
2. SRC-002-CHL-003 Kaye, K. (2025) 'Why Rodrigo Moya Changed His Mind About Chile's AI Governance Tool for Assessing a Medical Insurance Claims AI Model', World Privacy Forum, 29 April. Available at: https://worldprivacyforum.org/posts/why-rodrigo-moya-changed-his-mind-about-chiles-ai-governance-tool-for-assessing-a-medical-insurance-claims-ai-model/ (Accessed: 30 March 2026).
   https://worldprivacyforum.org/posts/why-rodrigo-moya-changed-his-mind-about-chiles-ai-governance-tool-for-assessing-a-medical-insurance-claims-ai-model/
3. SRC-003-CHL-003 Zecchetto, M. (2024) 'La estrategia de la Suseso para identificar licencias medicas falsas y mejorar respuesta a reclamos con IA', Diario Financiero, 12 November. Available at: https://www.df.cl/df-lab/transformacion-digital/la-estrategia-de-la-suseso-para-identificarlicencias-medicas-falsas-y (Accessed: 30 March 2026).
   https://www.df.cl/df-lab/transformacion-digital/la-estrategia-de-la-suseso-para-identificarlicencias-medicas-falsas-y
4. SRC-004-CHL-003 SUSESO (2024) 'Suseso es parte de las instituciones publicas que participan del piloto para el uso responsable de inteligencia artificial', SUSESO. Available at: https://www.suseso.cl/605/w3-article-731254.html (Accessed: 30 March 2026).
   https://www.suseso.cl/605/w3-article-731254.html