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Can Data Analytics Improve the Security of Customer Data?

Data breaches are all over the news lately, but data analytics may be the key to tighter security — and better customer service.

A growing number of high-profile organizations have been in the news recently for data breaches that put customers at risk, and the trend shows no signs of stopping. Collecting data about customers allows organizations the advantage of personalizing their services, but safeguarding that data comes with major security concerns.

Data analytics, or the way organizations process the information they collect to learn about their customers, is becoming increasingly effective at de-anonymizing large amounts of data and tying it back to specific individuals. While personalized data is a goldmine in terms of marketing and services, it’s also exactly what cyber-criminals target.

But information expert Sam Ransbotham, in the MIT Sloan Management Review, says that de-anonymizing people through data analytics coud be a powerful security tool itself, and can even improve customer service along with way.

How data analytics plays into security

Ransbotham points out that authenticating identity is one of the most important parts of keeping data secure. Whether online or over the telephone, authenticating your identity usually means answering a string of questions first to identify your account and then to affirm that you are who you say you are.

Data analytics, however, offer a better way of authenticating identity. A number of companies in the banking sector have already begun to use speech processing to identify a caller’s voice based on recordings of previous telephone calls. These “voiceprints” can confirm identity almost instantly and reduce the chance of someone stealing a personal identification number (PIN).

Using an automated system of voice-data analysis gives banks the added benefit of being able to adjust their security protocols for all customer service interactions at once. This allows for faster responses to updated assessments of security threats, rather than having to re-train customer service representatives.

Customer service advantages

Instead of making callers identify themselves by answering “security challenge questions,” data analytics allows the security process to take place behind the scenes. Customers experience a more streamlined calling experience that immediately addresses their needs. They save time and are spared the hassle of answering questions to identify themselves.

Security challenge questions are, Ransbotham says, “adversarial by design. … This authentication process must begin with the assumption that the caller is a malefactor impersonating the real customer.” By performing the authentication process behind the scenes, voiceprints help re-define the customer service experience as helpful instead of combative.

Organizations, in turn, can save time on employee training. They can focus on training employees for service rather than security.

Data analytics does not have to involve a trade-off between security and service. Techniques like collecting and analyzing voice data can actually start providing solutions to some of the security concerns that data collection raised in the first place.

As Ransbotham suggests, data analytics has the potential for further applications. Voice analysis can detect speech patterns that indicate if someone is being coerced or suffering from impairment, which could be adapted for security and service purposes, too.

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Published by
Elizabeth Hines

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