A guide to managing data privacy risks for BigTechs

The ethics of Big Tech data collection

Amanda Khatri

Editorial Manager

A guide to managing data privacy risks for BigTechs


Whenever a technological advance promises to change the financial services landscape, data privacy concerns are never far behind. It is hard to overstate the importance of data to Big Tech companies with data being a critical resource for both commercial purposes and regulatory compliance. Organisations must invest in understanding how to manage and use data to stay competitive and avoid regulatory penalties. 

To help manage the challenges associated with data collection, let us explore how data privacy impacts Big Tech businesses, and examine some of the key pain points associated with compliance processes. 

The ethics of Big Tech data collection

The regulatory constraints associated with Big Tech data usage are in place to protect personal information and minimise ethical concerns around data collection. High-profile global data leaks have increased public awareness of how Big Tech companies use their private data — and prompted the introduction of regulations in jurisdictions worldwide. 

There is no shortage of recent scandals highlighting personal data collection’s privacy risks. In May 2023, there was a data breach within the US Government, which exposed the personal information of 237,000 US Government employees. There was also a ChatGPT data leak on 24 March 2023, which exposed customer data such as credit card information.

Big Tech data problems do not just relate to malicious hacking and security issues, but also to internal compliance failures. In November 2022, Google paid a $391.5 million settlement following allegations by 40 US states that it had been tracking user data illegally. More recently, in June 2023, the US Federal Trade Commission ordered Amazon to pay a fine of $30.8 million for failing to delete the personal data of children who had used its Alexa voice assistant. 

Data regulation

Governments around the world have picked up on public concerns about Big Tech data collection and have introduced regulations to manage the problem. 

The EU’s landmark General Data Protection Regulation (GDPR), introduced in 2018, had a significant impact, setting out strict rules for how companies could store and use company data, and introducing rights for customers to demand their data be removed from databases. Following the GDPR regulation, many US states introduced their own data privacy regulations, with similar data control rules for private sector organisations  — these included:

In late 2022, President Biden signed an executive order that would address some of the data privacy regulation gaps between the US and Europe, with the EU approving the deal in July 2023. The EU-US Data Privacy Framework will impose new compliance obligations on US firms that share data with partners across the Atlantic, and align data management practices with rules set out in the EU’s GDPR. 

The US-EU framework, US state data laws, and data laws around the world carry strict non-compliance penalties — but breaches can also inflict reputational damage if they are picked up by the media. In a competitive commercial landscape, data privacy has become a controversial and highly visible topic of public debate, which means that organisations must take their regulatory responsibilities seriously and develop effective data privacy compliance solutions. 

5 ways to manage data privacy pain points

As firms continue to develop and implement data privacy solutions, it helps to understand the common compliance challenges. With that in mind, key data privacy pain points include:

1. Data security

Personal data breaches, both accidental and malicious, are the most visible of these since leaked private information quickly creates public anger and media attention. Big tech firms deal with vast amounts of personal data daily and must be able to keep that data safe without degrading its utility. Data security solutions must be comprehensive and involve protection against cyberattacks (including viruses and malware), account for human error such as lost or forgotten passwords and be updated regularly to account for emerging threats. 

Addressing data security friction requires proactivity. Firms should map the risks associated with their existing IT infrastructure, introduce suitable security measures such as dual-factor authentication, update training schedules, and consider ways to add efficiencies to account for potential procedural slow-down.

2. Scalability 

New privacy regulations combined with commercial growth can mean that the demands of big data collection and analysis quickly snowball. An increasing data burden may negatively affect the delivery of products and services, especially if firms are unable to update their IT infrastructure to match the pace of expanding compliance requirements. 

Migrating data infrastructure to the cloud may help firms deal with their data burden. Cloud data solutions can help resolve scaling problems since they allow for virtual data storage and processing. When provided as a service, cloud solutions also allow firms to lock in costs for periods of time, add flexibility as data needs change, and increase storage capacity exponentially.  

3. Customer needs

Recent data privacy regulations, such as the CCPA, emphasise customer data rights. Under such regulations, firms must typically allow customers to access their personal data upon request, disclose information about how data is being used, stored, or sold, and delete it upon request. 

Firms must fulfil customer rights or risk severe compliance penalties. In practice, this means implementing a system to inform customers and communicate with them about how their data is being used, and to ensure that employees understand how to handle customer data legally. Automation offers an advantage in protecting customer data rights: in addition to delivering terms and conditions of data use to customers, software solutions can facilitate customer disclosure requests quickly and efficiently and build security measures into the process. 

4. New regulations

The data landscape is constantly evolving, with emerging risks prompting governments to develop and implement new data privacy regulations. In this environment, firms may struggle to keep up with regulatory changes or integrate new compliance processes into existing infrastructure without negatively affecting the delivery of services. 

Given the volatility of the data privacy landscape, firms should consider compliance horizon scanning an important priority. Effective horizon scanning allows firms to keep an eye not only on incoming regulatory changes but on how modern technologies and new criminal methodologies might affect the way they do business. 

CUBE’s AI-driven regulatory change management solution uses horizon scanning to alert firms to new requirements or of any forthcoming changes to current regulations. This provides businesses with enough time to implement obligations to current policies and procedures to ensure compliance and avoid penalties.

5. New technologies

Big Tech data management is inextricably linked to the capabilities of technology. As tech innovations, such as AI and machine learning, affect the industrial landscape, firms must make decisions about when and how to integrate a new solution. While it is important to retain a competitive edge, it is also critical that modern technologies do not compromise data privacy obligations — which means that firms must assess innovations with existing infrastructure, a process that can take time and money.  

While firms may have the budget and resources for testing, it is often simpler and safer to engage third-party service providers to integrate modern technology. Service providers may not only shoulder some of the compliance burden, but can ensure that modern technology is integrated correctly, meets the relevant security standards, and remains up to date as the regulatory and risk landscape changes. 

Managing data privacy with RegTech 

CUBE’s data privacy compliance solution offers a way for firms to stay ahead of their compliance obligations in a challenging data privacy landscape. Built with powerful artificial intelligence, we tailor our data privacy solutions to the needs of businesses, delivering automated speed, accuracy, efficiency, horizon scanning, and day-to-day regulatory assurance. 

Our solutions take the heavy lifting out of data compliance by focusing on capturing incoming risks and regulatory changes, and on technical accuracy, with maps of the specific policies and controls that firms will need to implement to achieve compliance. Firms also benefit from detailed, defensible audit trails, with customer data routed to the right handlers automatically, and protected by cutting-edge cyber-security. 

To learn more about CUBE’s data privacy solution and regulatory technology platform, get in touch today

To ensure your firm complies with cyber, data and privacy regulations, speak to CUBE.



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