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How to Manage Data in Highly Regulated Industries

Managing data safely is important for all industries, especially after the enforcement of the General Data Protection Regulation by the EU in 2018.

The GDPR aims to protect citizen’s data by making data breaches punishable with a fine. But if your industry is highly regulated the stakes are even higher.

If you work in healthcare or financial services, managing the public’s sensitive data can be legally problematic for IT support teams.

Managing Health Data

There is no data more personal than medical records. People don’t want anybody other than their medical professionals to have access to them – but they also want quality care.

Great medical care cannot be provided if the right people cannot access the right data. So what happens if your patient needs to consult another specialist or need medical treatment when they’re out of town?

A key part of health industry data management is about firmly connecting individuals to their medical information. Doing so ensures that medical professionals always have access to the information that they need.

In Great Britain, the NHS has a system called the NHS Spine. Spine allows people’s medical data to be seamlessly accessed by their GP, prescription services, and any doctors they are referred to.

Large data organisation systems like NHS Spine certainly improve care, but they also put people’s data at risk. Systems like the Spine are large and a single breach affects a huge number of patients.

In 2018, an NHS system faced a data breach that impacted 150,000 patients. Healthcare providers must go further than mere compliance when protecting their customers from cybercriminals.

Managing Financial Services Data

Financial services are one of the most volatile industries in the world. Decisions are made every day that decides the fate of everybody’s money.

Like the health industry, financial service firms need to wrestle with vast quantities of data. The data held and used by financial services is a risk. An attack on the firm Equifax in 2017 exposed the personal details of 143 million people in the USA. Much more worrying was the theft of 209,000 customers’ credit card details.

Risks are there, but opportunity arises from risks. Managing data effectively presents an untapped resource for financial services firms. The main way that financial services can be propelled into the next generation is by using machine learning and AI technology.

Machine learning is all about improving efficiency by simplifying data. If computer systems can make their own decisions about removing useless data, employees will be able to spend more time making the decisions that matter the most.

Machine learning algorithms can also be used to predict customer behaviours and characteristics. Knowing how financial service customers might behave in advance could help you maximise your services or responses.

For example, if a customer is likely to fall behind on loan payments, the firm needs to respond to it quickly. Is there a way that you can help your customers?

By using customer data to make such predictions, machine learning can reduce the risks associated with lending and prevent people from falling into debt.

Improving Your Data Management

The modern age of data has made conducting business harder. Your responsibilities to protect your customers are only increasing, particularly if you are in a highly regulated industry.

Managing data properly can offer plenty of opportunities but also pose a threat to highly regulated businesses that could be financially crippling. At the very least, your IT support team needs to be aware of policies and regulations around GDPR compliance.

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