Posted By Jessica Weisman-Pitts
Posted on November 10, 2021
By Michael Queenan, CEO and co-founder of Nephos Technologies
In the modern and increasingly digitised world that we live in, data is being produced at unprecedented rates. During 2021, the amount of data generated by the financial industry each second is expected to grow by 700%, compared to 2020.
The financial sector holds some of the most valuable and sensitive data – and this must be protected. However, it’s more than simply storing the data. Financial firms want to use it to help grow their businesses whether that’s through delivering a better customer experience, innovating products and services or predicting future trends to improve risk management.
A strong data governance model is crucial as it helps to understand what data is being held, where it is stored, how to use it, and who can access it. Key to achieving a modern governance model is to understand the difference between its three core parts: data governance, data privacy and data security. Only when all three solutions are deployed will an organisation’s data be compliant and secure.
The foundation – data governance
Data governance is a blanket term for everything that goes on to make sure an organisation or business looks after its data properly. This includes the strategic and tactical overview and operational roles, responsibilities and processes. Data governance ensures the quality and security of the data you use. It’s the who, what and how; it defines who can do what, based on what data, under what situations and using what methods.
Most companies have already evolved some form of governance for individual applications, units, or functions but it’s often on an informal basis. Establishing formal processes and responsibilities is the key to managing data flow, ensuring compliance and scaling up.
The benefits of a well-crafted data governance strategy include minimised risks, coherent policies, metrics and processes, and better implementation of compliance and enhanced data value.
Next is data privacy
In our digital age, data privacy generally applies to the handling of critical personal information, also known as personally identifiable information (PII) and personal health information (PHI). If data is king then data privacy is the principal gatekeeper.
In today’s ‘data economy’, collecting, sharing and using data about customers or users has huge value both now and potentially in the future. And since consumers expect their private information to remain private, there is an increasing focus on the importance of transparency. To build trust with customers, businesses must follow their privacy policies and request consent to keep and manage personal data. Better transparency around data privacy builds customer trust.
At the same time, every business has to meet the challenge of regulatory compliance, and failure to do so can lead to devastating fines under regulations such as GDPR or CCPA. The regulations exist for a reason; if a business is victim to a hack or ransomware, the consequences in terms of lost revenue and lost customer trust could be far worse.
The icing on the cake – data security
Data privacy and data security are often confused. Whilst data privacy refers to the collection and usage of data, security involves protecting data from theft, corruption or unauthorised access that could occur from possible ransomware attacks or data breaches. Data security keeps all data secure, from physical hardware to virtual access controls and cloud data storage.
The US Commerce Department’s National Institute of Standards and Technology (NIST) released an internationally recognised framework of cybersecurity standards which outlines the following five areas:
- Identify your weak points – know all of your systems and services so you can identify any potential points for unauthorised access.
- Protect your systems – put the right security measures in place to protect your services and know which systems need the most protection.
- Detect any hacks – a monitoring system should be in place so any authorised access can be detected and stopped as quickly as possible.
- Respond quickly to a breach – a crisis response plan should be worked out beforehand so as soon as an attack is detected, everyone knows what to do.
- Recover – if a breach or attack does occur, systems and services must be able to be revived as quickly as possible to limit downtime.
Reap the benefits
Data is an increasingly valuable asset in the financial sector and can provide significant competitive advantages. With a strong data governance model, financial institutions can monitor risk and gain market insights which can be used to predict future trends and provide unique customer experiences. This is only achievable when the time is taken to implement data governance and achieve high quality data. To be most effective, data governance, privacy and security must all work seamlessly together. Whilst keeping data secure with cybersecurity solutions, financial institutions should implement effective data governance and data privacy measures to reap the benefits of a strong data governance model.
By Michael Queenan, CEO and co-founder of Nephos Technologies
In the modern and increasingly digitised world that we live in, data is being produced at unprecedented rates. During 2021, the amount of data generated by the financial industry each second is expected to grow by 700%, compared to 2020.
The financial sector holds some of the most valuable and sensitive data – and this must be protected. However, it’s more than simply storing the data. Financial firms want to use it to help grow their businesses whether that’s through delivering a better customer experience, innovating products and services or predicting future trends to improve risk management.
A strong data governance model is crucial as it helps to understand what data is being held, where it is stored, how to use it, and who can access it. Key to achieving a modern governance model is to understand the difference between its three core parts: data governance, data privacy and data security. Only when all three solutions are deployed will an organisation’s data be compliant and secure.
The foundation – data governance
Data governance is a blanket term for everything that goes on to make sure an organisation or business looks after its data properly. This includes the strategic and tactical overview and operational roles, responsibilities and processes. Data governance ensures the quality and security of the data you use. It’s the who, what and how; it defines who can do what, based on what data, under what situations and using what methods.
Most companies have already evolved some form of governance for individual applications, units, or functions but it’s often on an informal basis. Establishing formal processes and responsibilities is the key to managing data flow, ensuring compliance and scaling up.
The benefits of a well-crafted data governance strategy include minimised risks, coherent policies, metrics and processes, and better implementation of compliance and enhanced data value.
Next is data privacy
In our digital age, data privacy generally applies to the handling of critical personal information, also known as personally identifiable information (PII) and personal health information (PHI). If data is king then data privacy is the principal gatekeeper.
In today’s ‘data economy’, collecting, sharing and using data about customers or users has huge value both now and potentially in the future. And since consumers expect their private information to remain private, there is an increasing focus on the importance of transparency. To build trust with customers, businesses must follow their privacy policies and request consent to keep and manage personal data. Better transparency around data privacy builds customer trust.
At the same time, every business has to meet the challenge of regulatory compliance, and failure to do so can lead to devastating fines under regulations such as GDPR or CCPA. The regulations exist for a reason; if a business is victim to a hack or ransomware, the consequences in terms of lost revenue and lost customer trust could be far worse.
The icing on the cake – data security
Data privacy and data security are often confused. Whilst data privacy refers to the collection and usage of data, security involves protecting data from theft, corruption or unauthorised access that could occur from possible ransomware attacks or data breaches. Data security keeps all data secure, from physical hardware to virtual access controls and cloud data storage.
The US Commerce Department’s National Institute of Standards and Technology (NIST) released an internationally recognised framework of cybersecurity standards which outlines the following five areas:
- Identify your weak points – know all of your systems and services so you can identify any potential points for unauthorised access.
- Protect your systems – put the right security measures in place to protect your services and know which systems need the most protection.
- Detect any hacks – a monitoring system should be in place so any authorised access can be detected and stopped as quickly as possible.
- Respond quickly to a breach – a crisis response plan should be worked out beforehand so as soon as an attack is detected, everyone knows what to do.
- Recover – if a breach or attack does occur, systems and services must be able to be revived as quickly as possible to limit downtime.
Reap the benefits
Data is an increasingly valuable asset in the financial sector and can provide significant competitive advantages. With a strong data governance model, financial institutions can monitor risk and gain market insights which can be used to predict future trends and provide unique customer experiences. This is only achievable when the time is taken to implement data governance and achieve high quality data. To be most effective, data governance, privacy and security must all work seamlessly together. Whilst keeping data secure with cybersecurity solutions, financial institutions should implement effective data governance and data privacy measures to reap the benefits of a strong data governance model.