How can Big Data Analytics help fintech companies in cybersecurity and risk management?
Marketing Director at Spyrosoft Ltd.
The advent of fintech companies in capital and banking markets as well as insurance, wealth and asset management industries has had a significant impact. Considerable changes have also taken place with the emergence of online services providers facilitating peer to peer credits as well as lending and borrowing for businesses and individuals.
Financial services have always been responsible for protecting highly sensitive information about individuals and corporations.
With fintech companies coming into the picture, unprecedented volumes of information are available in digitised formats. The analysis of data and generation of valuable insights has become more convenient than ever before, but breaches of privacy and security have also become more likely. Hence, the significance of cyber security has also increased.
The current state of risk management and cyber security for fintech industry
Over the past few years we have witnessed a continuous rise in cases of fraud and security breaches placing the impetus on fintech companies to come up with more effective methods of cyber security. Risk management practices aren’t complete without considerable focus being placed on cyber security. In essence, risk management and cyber security have become entwined and interdependent.
In July 2018, Equifax- one of the foremost consumer credit reporting agencies, stated in a report that more than 143 million accounts fell prey to hackers who stole sensitive information such as social security numbers and phone numbers of account holders.
The infamous Zeus Trojan led to one of the most sophisticated and detrimental cyber attacks the banking industry has ever encountered.
Hackers were able to steal millions of dollars from banking customers all over the world as a direct result of Zeus’ ability to infect via web and email protocols, hack information provided in HTTP forms and steal account information provided in Windows Protected Packages. Zeus is still out there with sporadic instances.
The stark reality is that using advanced Machine Learning tools, Artificial Intelligence and Big Data analytics, for all around protection from cyber threats, is the only way forward.
It is now essential for fintech companies to encrypt their data to protect it from future threats. High-quality and effective tunnelling protocols employed by some VPN service providers with techniques such as PPTP, SSTP and Open VPN can prove valuable.
Challenges in improving cyber security For fintech companies
Fintech companies, banks and other financial institutions need to cope with the emerging cybersecurity challenges, which are threatening their ability to manage risk effectively. Some underlying challenges to this goal and factors that have left them reasonably vulnerable in the modern landscape include:
- Compliance with requirements of the regulatory framework – Complying with regulatory the framework has been difficult for fintech companies and other financial institutions. Opting for silo-based solutions to fulfill the minimum requirements has often been problematic.
It must also be noted that the security methods and practices of fintech companies may not be effective and optimally secure even when they adhere to all prescriptions of relevant national and international statutes, such as European Union GDPR. At times, efforts to comply with existing regulations can even be counterproductive because regulations haven’t been able to keep up with changes in the way fintech companies offer services.
- Protecting the privacy of customers and security of information – Many fintech service providers have failed to create integrated and comprehensive plans for data security for the entire organisation. Categorising data whilst retaining awareness of its sensitive nature, is another area where a lot of work is needed. At times, they have failed to understand which pieces of information matter more than others to enhance security frameworks for specific datasets.
- Handling risks arising out of third-part dealings – To reduce costs, partnering with other organisations or outsourcing services to them is a common practice adopted by many fintech companies. This leads to sharing of data in the cloud or over other platforms on the internet. These practices generate new challenges in optimising cyber security.
- Managing the rising expectations of customers – Modern financial services have become customer-centric and user-friendly. Obviously, this is essential, however, the requirements of seamless data sharing for managing customer demands also mandates consistent increase in the potency and capability of security measures. On many occasions, imperfect security protocols have led to fraud and the unethical hacking of sensitive information.
- Continuous advancement and adaptive nature of cyber threats – As evident from the examples of Zeus Trojan and other malware, future cyber threats are constantly evolving. Cyber criminals operate on a large scale; they have no shortage of funding, and they aim to cripple economies instead of targeting individual corporations. As a result, the threat looms large and is more powerful than ever.
How can Big Data Analytics, Artificial Intelligence and Machine Learning help?
Fintech companies need to be aware of the challenges. They need to build robust cyber security solutions powered by Deep Learning, Machine Learning, Artificial Intelligence and Big Data analytics. Getting ahead of the cyber criminals is essential to protect organisations and customers from the dangers posed by hackers.
Adopting machine learning in security frameworks can not only fight current threats but also evolve to provide security from emerging malware. Using Big Data analytics tools such as Predictive Analysis can help develop solutions using voluminous datasets leading to improved mitigation of threats.
Antivirus systems of fintech companies must be equipped with Machine Learning for the quick identification of different types of malware. Algorithms using Big Data analytics and AI can use pattern recognition for the detection of fraud along with helping in the creation of truly effective cyber security systems.
Fintech companies need to feed relevant and extensive datasets into their security algorithms to give them the power to detecting anomalies as soon as they arise. Deep learning, along with the isolation of sensitive data and applications, can ensure malware doesn’t move laterally within the system.
The entire cyber security framework used by fintech companies needs to be self-encrypting and self-healing if sensitive data and applications are to be protected from emerging threats. It is evident that opting for these technologies will ensure compliance with regulatory requirements while ensuring superior security for the data owned by fintech companies.
How we approach cyber security and risk management at Spyrosoft?
When you choose Spyrosoft as your service provider you will get access to state-of-the-art solutions for all aspects of cyber security.
Our solutions prevent existing malware from connecting with their command contacts operating from outside your system or network. As a result, they will not get activated, rendering them incapable of causing any harm. It will also lead to substantial cost savings because you have no need to deploy additional applications.
We seek to provide real-time monitoring with the help of AI, and Deep Learning enabled solutions for optimising cybersecurity. Along with this, we ensure automated encryption of datasets to guarantee sensitive information doesn’t move out of your systems without being encrypted.
Spyrosoft also focuses on optimal email security to protect intra-organisation communications. Our solutions are designed to remove downtime and email loss during any interruptions caused by external and unidentified factors.
Our solutions are aimed at creating extensive cybersecurity protocols and mechanisms for the entire organisation. Simultaneously, we will also help you in complying with all the regulatory requirements, depending on the laws governing cybersecurity issues for your organisation.