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With the improvement in technology, more and more players are joining the bandwagon to leverage it.

One of the late entrants is the finance sector also referred to as fintech companies who use technology to offer their services.

Off late, fintech is catering to a wide array of customers by rolling out solutions that impact nearly everyone. With the right technology in place, they broadened their reach while significantly increasing the flexibility and innovation level of financial services.

While there is technology in the finance industry, on one hand, there’s Artificial intelligence too introduced as a way to simplify human lives by integrating in a day to day life. And in the same manner, AI is integrated with the fintech to offer exceptional services in the simplest possible manner. But, with the increase in digital services and transactions, the vulnerabilities to have increased significantly. Not to mention, the cyber threat remains an all-time high for the online financial transaction and this why Fintech companies are aware of it too. Here’s where AI app development comes to play to by introducing smart applications and programs making it difficult or rather treacherous to access for the cybercriminals to hack systems.

Like any other technology, AI to carries a certain amount of threats and this is why utmost care must be taken while implementing the same for Fintech. Conditioning AI for future vulnerabilities is one way to get things started.

Enabling AI to distinguish between the access

Since AI is a system that is designed in a way to remain value-agnostic, feeding the understanding of Good and Wrongful access is a must as a safety measure against cyber threats. Being a value-agnostic concept, AI is not naturally capable to differentiate between the ethical transactions versus the wrongly intended ones. This is because the login condition tends to remain the same for each transaction/attempt.

For example, imagine a user moving his/her funds digitally from New York to London and then to Paris, and back again. You can expect a sizeable dip along the way due to different taxation policies and rate. Usually, a transaction of such nature will go down in the books of accounts as “usual business” under the AI engine scanner. Such transactions in the FinTech world will involve plenty of intricate calculations that refer to jurisdictions and statutes. Here’s when human intervention is required and that’s when the vulnerability is exposed. The AI will not be able to make any discretionary judgment and ethics and hence security becomes the primary concern.

Regulating the Access Control

One of the major cybersecurity vulnerabilities involves access control to a certain set of data in the fintech industry. For AI to control the access to data for security purpose, it gets difficult to manage the data security. The biggest vulnerability is that of the ability of cybercriminals and hackers to bypass the access controls with an aim to steal information or even pose as another legitimate individual.

They try to leverage identity theft for engaging in the phishing schemes. For fintech companies, the first line of defense to negate the power of unauthorized access is that of introducing e-signatures as a mandatory protocol for authorizing the business transaction. One can also involve other complex access control for advance security that involves bio-signatures or even biometric authorization that involves retina or irises scan, fingerprint login, etc.

Making the best use of AI and RPA for a Dynamic Security

AI has limited power to control security because of its scope. Perhaps, this is the reason why there is a difference between Robotic Process Intelligence (RPA) and AI. For any security engineer responsible for the fintech company’s security, the line between RPA and AI shouldn’t be blurred at any cost.

One has to move beyond the conventional idea of a security level when it comes to fighting vulnerabilities faced by fintech corporations. You can use RPA for a set of iterative tasks that involves protocol verification, ownership verification, and even monitoring and ensuring the right balance mechanisms.

And when it comes to security for banks, merely employing an intelligent system acting as a cybersecurity gatekeeper is not enough. This is because a banking transaction has far more depth than any other online transactions as it involves routing digital currency thru multiple devices and storage spaces.

This is where the breaching opportunities are opened up and vulnerabilities are exposed at each point. Engineering a static AI solution cannot cater to such all-pervasive threats, especially when fintech industry is experiencing a higher frequency of ‘zero-day’ attacks. The 76% of zero-day cybersecurity attacks took place in 2018 that stemmed from sources that were entirely unaccustomed for.

Doing away with the defensive, negative attitude

Challenges are everywhere, and most often when businesses face challenges on the technology front, the mindset differs. Much key business personnel are left feeling that it’s only a matter of time before their systems are hacked. The question boils down to ‘when will it get hacked’ rather than ‘will it ever’ or even better, ‘if it can get hacked’?

Here’s where the half battle is lost. One has to understand that AI is nothing sort of a magic bullet aiding the modern cybersecurity complexities. Fintech sites and transactions will inevitably need AI integrations to ensure safety. The benefits of bringing inefficiencies will evolve in the coming times as AI too wears off the age and presents a wider scope with deeper securities in terms of reducing manual efforts, and bringing down the salary costs while ensuring timeliness.

The best way to tackle threats is not to surrender to the idea of ‘one-stop-solution’ when it comes to securing transactions thru AI. The key is to look at the incremental transformation by taking an example from the likes of PayPal who are immune to large scale as they have adopted a continuous testing approach that keeps vulnerabilities at check.

Conclusion

The blend of Artificial intelligence in the fintech has become integral to both the industry wherein a dedicated mobile app development company plays a major role in bridging the gap.

This is because banking and investment have moved beyond the traditional brick and mortar way where even institutions are encouraging people to move their finances digital.

And this is why we see many traditional banks pair up with fintech firms to blend in the best of both worlds. And hence, ensuring the safety of all such transactions that take place on their portal becomes the liability for the banking and financial institutes.

Any failure in that regard will have customers losing faith in them and even risking the future prospects of investors as they fear to operate online.

Customers too have evolved when it comes to picking the fintech companies as they tend to go for the one that follows regulations and best practices.

They also consider whether or not such firms had any cyberattacks history and checks how well the company utilize precautions for cybersecurity.