SLVRCLD has a large structured household content item dataset, that was built-up by analysing millions of actual insurance quotes, and further enhanced so that we can accurately identify the item being claimed. This can be done automatically, if the item was specified before the claim, by the claims agent or by empowering your claimant through self-help portals.
Learn more about SLVRCLD | Capture
We use machine learning to determine the most suitable replacement items when an item has been discontinued, which experience has taught us is about 2 out of every 3 items.
Learn more about SLVRCLD | Replace
Replacement or current items are then quantified instantaneously from panel supplier quotes that were obtained previously. If instantaneous pricing is not available it breaks out into a quick and tender process, which all happens in the background.
Learn more about SLVRCLD | Quantification
Each and every claim is unique and needs to be settled using the most appropriate method. There are many virtualised instantaneous methods available depending on the supplier or country.
Learn more about SLVRCLD | Settle
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