Wall Street Journal:
AI platform identifies hidden patterns in data

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An excerpt from a recent Wall Street Journal article about SparkBeyond:

“SparkBeyond recently helped Swisscard AECS GmbH, a Switzerland-based credit-card issuer, identify the best way to prevent customer churn by detecting hidden patterns in online transactions and other customer data.

The analysis revealed individual customer preferences for being solicited by email, phone or regular mail, and when they were most likely to respond to upgrades and other deals, said Swisscard Chief Executive Florence Schnydrig Moser.

These patterns identified by the platform are “typically things you would not see as a human,” Ms. Moser said.

Or with traditional data analytics.

Where most AI-powered data-analytics programs are limited by the number of hypotheses fed into them manually by data scientists, SparkBeyond’s platform tests millions of algorithmic hypotheses pulled automatically from online libraries of open-source code like GitHub, the company said.

That enables the platform to break through a “cognitive bottleneck” and significantly expand the scope of analytics, said Sagie Davidovich, SparkBeyond’s co-founder and CEO.”

Read the full article here.

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