TECHNOLOGY the process . Likewise , one day soon it will seem nonsensical to speak of software without understanding that security is part of every phase of development , deployment , operation , and maintenance .”
MACHINE LEARNING , BIG DATA , AND ANALYTICS
Zero-trust networks , blockchain and biometrics Regardless of the technologies in use , the current fintech sector requires a redefining of user privacy . Many technologies are effective here , but zero-trust networks , blockchain-based systems , and biometricsbased authentication are the future solutions of choice . In the light of recent ransomware and other malware attacks , Zero Network Access ( ZNA ) ensures that a user does not receive access to a network without properly confirming their identity .
“ For too long cybersecurity solutions have focused on protecting the machines in an organisation , and not the people running the machines and handling huge amounts of data ”
TIM SADLER TESSIAN
“ Advanced machine learning that can automatically detect threats - like phishing or insider threats - by understanding the behaviours of employees in an organisation . This type of technology not only automatically
Every day , financial service providers receive an abundance of data . Although many institutions lack the expertise to create a protective layer against cyber threats , the data they have gathered for many years can be applied to the security of their systems . With the help of Machine Learning and standard data analytics practices , companies are capable of leveraging big data to find irregular patterns from these data streams to continuously redesign risk management systems , allowing them to detect problematic behaviour in seconds and protect customers from potential data loss / exposure without considerable investment .
Embedded authentication interventions Embedded systems have been on their edge for some time , but the fintech sector has only recently discovered the real potential of these systems . Instead of relying on hardware or software alone , an embedded system can combine both to confirm a customer ' s identity . For instance , a hardware identifier on users ’ endpoint systems can be used along with a traditional PIN / passcode to verify access to finserve platforms .
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