Is the concept of data privacy flawed?
SINCE the enforcement of the EU’s General Data Protection Regulation in May this year, customers have raised concerns about the use (and misuse) of data.
However, the fact is that most of today’s businesses run on data — information is the oil of modern commerce, they say. Whether a bank wants to train an artificial intelligence (AI) model to estimate the credit risk associated with a loan application (in minutes) or a retailer needs to personalize the experience for customers, data is needed.
The truth is, customers — to quite an extent — want a certain degree of personalization and product intelligence that is only possible if they make their data available to organizations. Unfortunately, if surveyed, these very customers will say that they’re not comfortable with businesses gaining access to their data.
What data do businesses need?
To be fair, businesses need access to most of the data they have. Take the bank who is training an AI model to estimate credit risk for customers who send in an application for a loan.
If the model does well, it can be deployed online, allowing the bank to process loan applications in minutes — transforming personal finance, wealth management, and customer experience — all at once.
However, it is true that any AI model is only as good as the data it is trained on.
In this instance, except for the names of (past) applicants, the bank’s model needs access to all sorts of data about the applicant and the loan application — the credit score, the loan amount, salary and tax details, and repayment details for loans approved, among other things.
For retailers looking to create personalized experiences, being able to identify customers along with the ability to track their movements, preferences, and choices is critical to the task itself.
Is this the end of data privacy?
There’s no definite answer to this, but the concept of data privacy in the information age seems quite flawed to begin with.
It’s impossible for customers to interact or transact with businesses without leaving behind their data. It’s also impossible to make progress in the field of AI without the use of customer data. Finally, in order to personalize experiences, businesses need data.
In essence, today’s world revolves around data — and hence, data privacy is a difficult concept to achieve. It’s almost like going to the same store every day after work to buy groceries — and expecting the staff to forget your face and what you bought as soon as you walked out the door (at the end of the session).
What’s the alternative to data privacy?
Data privacy is difficult, but the harmful effects of the lack of it are quite easy to remediate.
For starters, businesses should be more vigilant about identity theft.
Banks, for instance, should make sure that customers have a good experience on mobile and internet banking applications but are asked for additional authentication when they’re making unusual transactions.
Fingerprint sensors are common handsets today — banks should be among the first to use them as an additional factor of authentication. Voice and facial recognition should also be explored. In effect, banks should try their best to make it impossible for the wrong person to break into an account.
Imagine, if identity theft becomes impossible, most customers wouldn’t be half as worried about data privacy.
There’s also a role that government organizations play when it comes to data privacy. They need to make it difficult for businesses to monetize the data to the detriment of customers, without making it impossible for them to use it to benefit their existing business and enrich the customer experience.
Here’s an example: Retailers, for example, who are able to use data to personalize the experience for customers, should neither be able to commoditize their technology and lease it out to competitors, or create products using the customer’s personal data to give allied businesses a competitive advantage.
When businesses and governments are able to provide the right protections, data privacy will not be as big of an issue — and the focus will shift to using data for good of many rather than exploiting data for the benefit of a few.