Drive
“critical to quality”
aspects of long-range financial forecasts.
Data & Segmentation
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Forward looking / lead indicators
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Campaign specific outlooks
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Macro-environment linkages
Unique ML methodology
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Ensemble of ML techniques and methods
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Standards for best Model selection
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Confidence intervals around the forecasts
Ether forecasting engine
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Full forecasting solution via Ether platform which integrates seamlessly with bank's data and batch processes
Is your approach accurately forecasting potential revenue and losses? Scienaptic brings together the key pillars of data, machine learning (ML) and proprietary forecasting engine to drive efficiency, sensitivity and robustness in the forecasting process.