Quants turn to machine learning to unlock private data
Replication could allow financial firms to use—and monetize—data that was previously off-limits
When an investment firm wanted to find out how a new breakfast menu at Wendy’s might affect the fast-food chain’s bottom line, it looked for the answer in time-stamped credit card transaction data.
The data was anonymized, of course. Credit card companies remove sensitive information and add statistical ‘noise’ to this type of data before selling it to investors or even sharing it internally. But these anonymization techniques are not foolproof, and nervousness about privacy breaches has held
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