How Does Archera Underwrite?
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Archera uses its read-only access to cost- and usage-related data and metadata to build a comprehensive picture of your infrastructure usage and delineate between different use-cases being served.
The core engine is based on a mix of learned heuristics and rules — for example: workload region, instance/VM type, engine, the types of commitments available to cover these workloads and their accompanying discount rates — as well as machine learning models trained on historical service usage & longevity rates.
The way we calculate the "risk" of insuring a commitment is based on a few factors, one of which is the coverage ratio. The lower the historical coverage level a customer has before purchasing a commitment, the less risk posed to us when underwriting that risk. Conversely, the higher the historical coverage the more risky it is for Archera to underwrite.
Once we understand the "risk" of commitment relative to the customer, the insured coverage allowance is determined on a per resource basis. At the extreme, where a customer is covering something that we would classify as extremely risky (e.g. going above 100% coverage on low survival rate services or resources), the platform actually won't even offer insured commitments. The risk is too great to justify, both from our perspective and from a customer savings perspective. If the customer wishes to cover lower risk resources, larger allowances are generally given. At an intermediate level of risk, they will have an allowance which lets them take on some insured commitments.
Archera, similar to an insurer, is always open to creating custom "policies" and insured commitments based on requests — and the underlying risk — on an ad hoc basis via a conversation with our customer success and underwriting teams that you can request via the App or email.
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