Independent Validation Confirms Scientific Rigor of Greater Than's AI Model for Crash Risk Prediction

• Greater Than has validated its AI to strengthen trust and transparency in predictive risk intelligence for safe, sustainable mobility           
• Independent review by AI expert Anders Arpteg confirms scientific rigor of model           
• The AI uses real-world driving and crash data to predict crash outcomes regardless of geographies and vehicle types 

STOCKHOLM, April 8, 2026 /PRNewswire/ -- Greater Than, a global provider of risk intelligence into road safety and climate impact, has completed an independent third-party validation of its artificial intelligence (AI) technology by AI expert, Anders Arpteg. The validation reinforces Greater Than's commitment to transparency while confirming the scientific methodology behind its unique pattern-based model. 

"Following an independent technical validation, I confirm the scientific rigor of Greater Than's Crash Probability Score," said Independent Validator Anders Arpteg, Ph.D., Artificial Intelligence. "A defining characteristic of this model is its foundation on actual real-world crash outcomes, rather than the proxy indicators, such as harsh braking, commonly used in the industry."

Greater Than's AI technology has been trained on over 20 years of driving data and verified crash outcomes, using anonymized data from 106 countries to reflect diverse driving conditions and behaviors. It analyzes GPS data to identify patterns in driving behavior and predict crash probability. 

"Because crash events are statistically rare, effectively training an AI to predict them requires a massive volume of historical and global data," added Anders Arpteg. "Given the model performance, it is clear that sufficient data from many years and countries has been used."

For the validation, the company's Crash Probability Score was used as a representation of the AI model. The review confirmed that drivers with higher Scores were consistently associated with a disproportionate share of claims – regardless of geography, vehicle type or driver category. Both at-fault and not-fault claims were included, reflecting the probabilistic nature of crash risk and avoiding bias related to fault determination. 

"Trust and transparency are critical in the world of AI," said Anders Lindelöf, Co-founder & Chief Technology Officer at Greater Than. "Given Anders Arpteg's extensive background in AI, we greatly value his thorough evaluation of our model so organizations can rely on our technology with confidence."

At a time when the use of AI is growing rapidly within the mobility landscape, Greater Than believes transparency is essential to building trust. By completing this validation, the company aims to strengthen confidence in using AI to improve safety and sustainability outcomes within mobility – today and in the future.

CONTACT:

Press contact Greater Than
PR@greaterthan.eu
+46 855 593 200
www.greaterthan.eu

This information was brought to you by Cision http://news.cision.com

https://news.cision.com/greater-than/r/independent-validation-confirms-scientific-rigor-of-greater-than-s-ai-model-for-crash-risk-predictio,c4331554

The following files are available for download: