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

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: http://subscriptions.waterstechnology.com/subscribe

You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Waterstechnology? View our subscription options

Register for free

Access two articles, our IMD and Waters Wraps, plus a member newsletter. Find out more.

All fields are mandatory unless otherwise highlighted.

Most read articles loading...

You need to sign in to use this feature. If you don’t have a WatersTechnology account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here