Robust data privacy strategy for healthcare, banks in AI, ML era

In the age of AI and machine learning, personal data has become the most valuable resource, driving advances in technology and automation. As digital transformation accelerates, healthcare providers and banks are at the forefront of this new era, harnessing the power of data to improve services and better serve their clients.

However, the immense potential of AI and machine learning cannot be fully realised without robust data privacy and security strategies. In this article, I outline how healthcare providers and banks can create a comprehensive data privacy strategy for the next 5-7 years, ensuring their clients’ personal information is protected. First and foremost, healthcare providers and banks must prioritise a culture of privacy, fostering an environment where data protection is valued and integrated into every aspect of the organisation. This requires continuous training and education for all employees, from frontline staff to C-suite executives. An excellent example of a company successfully promoting a privacy-centric culture is Apple, which has consistently emphasised user privacy as a core value, even going as far as to refuse government requests for backdoors into their devices.

In tandem with this cultural shift, organisations must adopt a privacy-by-design approach, embedding privacy into the development and implementation of new technologies and processes from the outset. This ensures that data protection is not an afterthought but rather a fundamental aspect of every project.

The European Union’s General Data Protection Regulation (GDPR) provides a comprehensive framework for implementing privacy by design, which can serve as a model for healthcare providers and banks worldwide. Risk assessment and mitigation must also be at the core of any data privacy strategy. This involves regularly identifying and assessing potential risks associated with data processing and implementing measures to minimise these risks. For instance, the National Institute of Standards and Technology (NIST) provides a Cybersecurity Framework that organisations can use to evaluate and improve their cybersecurity posture. By following these guidelines, healthcare providers and banks can identify vulnerabilities and take steps to address them before they lead to breaches or data leaks.

Moreover, healthcare providers and banks should invest in advanced AI and machine learning technologies to detect and prevent potential threats. Anomaly detection, for example, can be used to identify unusual patterns in large datasets, flagging potential breaches or unauthorised access. In the banking sector, JPMorgan Chase has successfully deployed AI-based systems to detect potential fraud, saving the company an estimated $150 million annually.Collaboration between organisations is also crucial for a strong data privacy strategy. By joining forces and sharing best practices, healthcare providers and banks can enhance their data protection capabilities and stay ahead of emerging threats. A shining example of this collaborative approach is the Financial Services Information Sharing and Analysis Center (FS-ISAC), which facilitates the exchange of cybersecurity information among financial institutions, enabling them to quickly respond to new threats.

Additionally, healthcare providers and banks should actively engage with regulators and policymakers to help shape the future of data privacy legislation. As AI and machine learning continue to evolve, it is essential that industry leaders work closely with government agencies to develop regulations that strike the right balance between innovation and data protection.

This collaborative approach ensures that new policies are informed by the expertise of those on the front lines of technological change. Transparency is another critical element of a successful data privacy strategy. Healthcare providers and banks must be open and honest about their data collection and processing practices, giving customers the information they need to make informed decisions about their privacy. This includes providing clear, accessible privacy policies and giving users control over their data. A notable example of transparency in action is the “Right to be Forgotten,” a provision in the GDPR that empowers individuals to request the deletion of their personal data.

Healthcare providers and banks must prepare for the possibility of a data breach by developing a comprehensive incident response team that is prepared to trigger effective mitigation controls when breaches do happen. The world is entering into a new era led by the neck breaking speed of AI and ML, and it behoves banks and healthcare providers who will benefit from this positively to also play the defensive part.