Tailored policies, dynamic indices can help mitigate parametric basis risk: PwC

As per a new report from PwC, the inherent nature of parametric basis risk can be mitigated by improving the accuracy of models, refining index triggers, and ensuring high-quality data.

PwC’s report observed that despite its many merits, one of the significant challenges associated with parametric insurance products is basis risk.

“Basis risk occurs when there’s a mismatch between the coverage of the policy and the actual event that triggers payment, resulting in the policyholder receiving a lower payout than expected or no payout at all,” PwC explained.

This can reportedly be driven by several factors, including the limited availability of high-quality data that accurately predicts the occurrence of an insured event, the lack of an accurate and up-to-date index or trigger mechanism that accurately reflects the event, and/or the imposition of rigid terms within the policy.

“This is a key risk for both insurers and insured parties, as it can significantly impact the effectiveness and reliability of parametric insurance products.

“This risk is inherent in parametric insurance due to the nature of its design – the payout is triggered by specific, measurable events, rather than the actual damage or loss experienced,” PwC stated.

In light of this, the firm noted that basis risk can be mitigated by enhancing data quality, monitoring and evaluating the parameters of the policy, diversifying insurance parameters or complementing with traditional insurance covers.

“Reducing basis risk in parametric insurance typically involves improving the accuracy of models, refining index triggers, ensuring high-quality data, and designing policies that align as closely as possible with the insured’s true risk profile,” the firm added.

PwC concluded that while no solution can completely eliminate basis risk, a “multifaceted approach” can significantly reduce it.