Deep Learning, Cyber Security and Finance

The financial spectrum is widely complex with a plethora of factors influencing each other. More data scientists are entering the banking field developing sophisticated models. Today, deep learning has come to play an integral role in many phases of the financial ecosystem from portfolio construction to cyber security. 

The financial system is vital to any country as it directly focuses on the efficient functioning of the economy. The finance industry also provides a significant amount of employment to people across the globe. Apart from employing the masses, the finance industry also focuses on other parts of the human life such as loan provision for businesses to invest in ambitious ventures. Apart from providing enterprises with funding solutions, the finance industry also focuses on risk management services that arrive with pooling of funds. The deep learning technology focuses on capturing abstract concepts to assist machines in concluding better decisions. According to Dr. Yoshua Bengio in an interview to the Tech Emergence, deep learning is a technology that can contribute to help people directly not just by building improved gadgets, but by directly influencing the human situation. Deep learning is an application that the pioneers in the finance industry are vying for to solve the current complex problems faced by them.

The Threat of Cyber Attacks in the Finance Industry 

Despite transforming lives and corporations, the challenges faced by the financial institutions are still numerous. One of the multiple challenges faced by the finance industry is the ability to keep up with the consumer laws. Keeping up with such laws and maintaining efficient functioning is always a challenge for financial companies across the world.

Another challenge commonly faced by financial organizations is the threat of a cyber-attack. Financial institutions are a prime target for attackers having the potential to make more money for the hackers. Apart from making monetary benefits, attackers are also focusing on targeting the information held by such organizations. When an attacker gets access to a financial organization’s information, the threat of data theft always exist. One of the reasons CTOs and CIOs of financial organizations are on their toes to counter such attacks is because of the increase in the frequency of cyber-attacks on financial institutions in the last few years.

Countering Cyber Attacks with Deep learning 

Deep learning is a technology that learns from algorithms and focuses on making decisions based on an intensive investigation of data. As of today, the amount of information available to businesses and people is in abundance. With so much data being available, deep learning that uses neural networks can assist financial organizations in countering the challenges faced by them in numerous ways.

With deep learning algorithms, organizations can feed the machines with patterns that are similar to cyber-attacks that are common. By learning from algorithms and having the availability of tremendous amounts of training data, deep learning can assist machines in determining a scenario of a cyber-attack in its initial phase itself.

Apart from merely using deep learning for countering cyber-attacks, the finance industry can leverage such technology even when they want to review commercial loans and form contracts accordingly. JPMorgan Chase is leveraging deep learning for the same purpose.

Deep learning has numerous applications across several industries. CTOs and CIOs of financial organizations should now find better ways of hiring deep learning experts to work on pre-existing data to achieve accurate information. Apart from hiring deep learning experts, businesses can also try to educate their employees on how to work with such a dynamic technology. Organizations could also focus on how they can revamp their infrastructure to welcome the wave of deep learning in their industry.