Project AURIONAI Use-Cases Research & Innovation
Finance

Insurance Claims Automation

OCR, AI fraud detection on claims and claims analysis; no named model found.

Named Models

The research names no model for this use case.

Where this comes from
Models the research names for this use case. Research, with sources on each model record.

Who Runs It

production, 5contract signed, 1pilot, 1planned, 1
Asuransi AstraAsuransi AstraCountry: IndonesiaOCR and AI for motor policy issuanceVendor: not statedproductionDate11 Sep 2026Policy issuance cut from 16 steps to 2; target 70 to 80% automatedEvidence: company statementConfidence: lowSource: investortrust.id
Prudential IndonesiaPrudential IndonesiaCountry: IndonesiaAI for customer profiling and claims analysis against policy termsVendor: not statedproductionDate6 Aug 2026Applied per Chief Digital and Technology OfficerEvidence: company statementConfidence: lowSource: keuangan.kontan.co.id
PT Zurich Asuransi Indonesia TbkCountry: IndonesiaAI motor claim survey: policyholders send their own photos and AI counts scratches and dents and checks coverage (product and vendor not named)Vendor: not statedproductionDate7 Mar 2024Faster process and better data accuracy (company statement, no figures)Evidence: company statementConfidence: lowSource: infobanknews.com
Tokio Marine IndonesiaCountry: IndonesiaAI fraud detection on motor and e-commerce shipment claims (model not stated)Vendor: not statedproductionDate13 Dec 2023No figures statedEvidence: company statementConfidence: lowSource: keuangan.kontan.co.id
Allianz IndonesiaCountry: IndonesiaAI for claims analysis, decisions and early fraud detection, developed from 2019 (vendor not named)Vendor: not statedproductionDate4 Dec 2020More than 7,500 claims a month analysed; fraud detection accuracy above 80 percent; twice the output of manual analysis (company claims)Evidence: company statementConfidence: lowSource: tirto.id
Oona Insurance IndonesiaCountry: IndonesiaCamCom image AI for car damage assessment in vehicle insurance inspection; severity and fraud features to be addedVendor: CamComcontract signedDate2 Feb 2024None statedEvidence: company statementConfidence: lowSource: investortrust.id
Asuransi AstraAsuransi AstraCountry: IndonesiaAI fraud detection for health claimsVendor: not statedpilotDate11 Sep 2026Described as developedEvidence: company statementConfidence: lowSource: investortrust.id
Asosiasi Asuransi Umum Indonesia (AAUI)Asosiasi Asuransi Umum Indonesia (AAUI) with PT PindaiCountry: IndonesiaAI for claim condition checks and fraud mitigation in motor and health insurance, developed with an unnamed Chinese partnerVendor: PT Pindai with an unnamed partner from ChinaplannedDate30 Jul 2026Trial with insurers hoped for Q3 2026; no resultsEvidence: company statementConfidence: lowSource: investortrust.id
Where this comes from
Documented uses by named organisations. The evidence column says who made the claim.

Candidate Models

TabArena: All Tasks, no imputation, snapshot 2026-05-06, 59 entries

A general benchmark for this model class, not a test on this use case. Elo across tabular tasks, anchored RandomForest default = 1000; TabPFN-lab researchers are involved. Higher is better. Elo has no zero, so the axis starts at 1,200. Showing 10 of 13.

AmazonAutoGluon 1.5Amazon maintainer-run1,700Prior LabsTabPFN-2.6Prior Labs maintainer-run1,626Prior LabsRealTabPFN-2.5Prior Labs maintainer-run1,604INRIATabICL v2INRIA maintainer-run1,598INRIARealMLPINRIA maintainer-run1,514Layer 6 AITabDPTLayer 6 AI maintainer-run1,460YandexTabMYandex maintainer-run1,448Microsoft AILightGBMMicrosoft AI maintainer-run1,435YandexCatBoostYandex maintainer-run1,418DMLC communityXGBoostDMLC community maintainer-run1,376
1,2001,5001,800
DMLC communityXGBoostDMLC community, tabularReleasedAug 2026open weightshas scoreslast 18 monthsMicrosoft AILightGBMMicrosoft AI, tabularReleasedJul 2026open weightshas scoreslast 18 monthsBaiduPaddleOCR-VL-1.6Baidu, OCR and documentReleasedJun 2026runs on edgehas scoreslast 18 monthsPrior LabsTabPFN-2.6Prior Labs, tabularReleasedMar 2026open weightshas scoreslast 18 monthsYandexCatBoostYandex, tabularReleasedFeb 2026open weightshas scoreslast 18 monthsZ.ai (Zhipu)GLM-OCRZ.ai (Zhipu), OCR and documentReleasedJan 2026open weightshas scoreslast 18 monthsDeepSeekDeepSeek-OCR 2DeepSeek, OCR and documentReleasedJan 2026open weightshas scoreslast 18 monthsAmazonAutoGluon 1.5Amazon, tabularReleased2026open weightshas scoreslast 18 monthsINRIATabICL v2INRIA, tabularReleased2026open weightshas scoreslast 18 monthsPrior LabsRealTabPFN-2.5Prior Labs, tabularReleasedNov 2025open weightshas scoreslast 18 months

Showing 10 of 107. All models of this class

Where this comes from
Derived, not researched: models in the directory whose class matches a class this use case uses, excluding family records and models shut down or deprecated. Ranked by how many fit facts they meet, then by release date. Each fit fact is read from the model record.

Sources

  1. 3 Ways Insurers In Asia Are Embracing Generative AI oliverwyman.com https://www.oliverwyman.com/southeast-asia/our-expertise/insights/2023/nov/generative-ai-transform-insurance-asia.html
  2. Asuransi Astra Targetkan 80% Proses Klaim Dilakukan Otomatis dengan AI investortrust.id https://www.investortrust.id/financial/115958/asuransi-astra-targetkan-80-proses-klaim-dilakukan-otomatis-dengan-ai
  3. Prudential Indonesia Terapkan AI Mulai Sisi Operasional hingga Pengelolaan Risiko keuangan.kontan.co.id https://keuangan.kontan.co.id/news/prudential-indonesia-terapkan-ai-mulai-sisi-operasional-hingga-pengelolaan-risiko

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Insurance Claims Automation", https://aurion.semai.id/usecases/fin-insurance-claims/, records of October 2026.