Nace AI has launched Drex for Finance, a model designed for split-second financial tasks, like determining whether a card payment looks fraudulent.
It can use a document or a transaction log along with a fixed set of possible answers, then deliver a probability score for each one.
In tests with 3,361 decisions from 48 finance benchmarks not included in training, it was right 85.7% of the time, compared to 70.9% for GPT-6 Luna.
Announcing Drex for Finance - the multimodal decision model, post-trained for sub-second financial decisions. Financial operations require precise, regulatory-grade decisions with zero hallucinations across filings, support, credit risk, live fraud prevention, quant signals, and compliance. Evaluated on 48 held-out finance benchmarks: - 85.7% accuracy across 3,361 decisions (+14.8% vs. GPT-6 Luna) - 77.3 Finance Index (+13.7 vs. Jev 1.14, +11.5 vs. Drex-Max v1.1) Trained for sub-second financial intelligence across the entire pipeline: - Financial Documents & Filings: Extraction decisions, classification, and clustering - Credit & Lending: Automated underwriting, PD modeling, and EWS - Fraud & AML: Sub-second transaction scoring, ATO defense, and SAR clustering - Markets & Trading: Regime detection, meta-labeling, and LOB execution signals - Insurtech & RegTech: Claims fraud detection, sanctions screening, and audit reconciliation Available exclusively on Nace Console: https://console.nace.ai
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Original title: Nace AI has launched Drex for Finance, a model designed for split-second financial tasks, like determining whether a card payment looks f...
