Re/insurance broker WTW has announced the launch of the newest version of its leading-edge Radar pricing software, Radar 4.15.
The latest version overcomes a major barrier to wider adoption of machine learning by introducing a market-first capability, making it significantly easier for insurers to benefit from the full predictive power of machine learning, without losing the ability to interpret accurately the outcomes of increasingly complex models.
WTW says that by introducing a proprietary algorithm that resolves the previous inherent trade-off between accuracy and interpretability of models, the radar upgrade delivers an exceptional level of “predictiveness and transparency.”
The upgrade will also transform insurers’ ability to unlock the full potential of machine learning in order to optimise both their underwriting and claims processing, whilst adapting to a regulatory environment increasingly focused on fairness.
Serhat Guven, Managing Director at WTW, said: “The innovation underpinning Radar 4.15 is ground-breaking, for the first time giving insurers access to state-of-the-art, speed-to accuracy performance that goes hand-in-hand with unrivalled levels of transparency. Technological advances will inevitably continue to reshape the insurance landscape, yet it will only be possible to harness the full potential of these technologies if customers and regulators trust they are being used by insurers responsibly.”
Furthermore, WTW noted that while both AI-based and machine learning tools offer high predictive performance and accelerate speed to market, by their nature however, they are more complex and less transparent, which prevents users from being able to fully understand the model they are creating.
WTW said: “Their ‘black-box’ nature poses significant risks if deployed without due care, including amplifying bias risks that lead to discriminatory decisions, and regulatory tolerance is running out for pricing perceived to be unfair.”
Serhat added: “Radar 4.15’s powerful new algorithm addresses the black-box limitations of machine learning by offering insurers a ‘best-of-both-worlds’ solution that combines the pure predictive power of the machine learning approach of Gradient Boosting with the exceptional intepretability and transparency of Generalised Linear Models.”
