Stay Ahead of Cyber Attacks: AI-Driven Security for Fintech
OCT 18, 2024
Imagine your customer walks into a bank and there’s a robot to assist with deposit and withdrawal of cash. Sounds futuristic, doesn’t it? Most fintech firms are putting efforts into modernizing their infrastructure with AI. With a growth rate of approximately 2.91%, artificial intelligence in fintech is predicted to increase from 44.08 billion USD in 2024 to 50 billion USD in 2029. Innovations in the fintech industry have made financial services more convenient and accessible to all. But the element that puts life into fintech is data. It is the elixir that financial technology companies use to understand what consumers prefer and how they can personalize customer service. Due to advancements in financial technology, the volume of data available for analysis has vastly increased.
With so much data comes the responsibility to take care of its security and make sure it doesn’t fall into the wrong hands. As mobile transactions and electronic payments become more prevalent, the risk of maintaining data integrity also arises. To understand the seriousness of cyberattacks across several industries, you’ve got to look at this chart below. Fintech seems to be one of the biggest victims of cyber threats. To protect data assets, fintech companies must implement effective security protocols backed by artificial intelligence and provide reliable services to customers.
Source: Statista
How will AI boost the security of your infrastructure?
1) Fraud detection
In the previous 5 years, fraudulent activities in the fintech sector have increased by more than 30%. To counter these tactics of cybercriminals, you need effective fraud detection measures. AI models, built with the help of machine learning, deep learning, and NLP, can monitor large datasets and spot suspicious patterns. These anomalies in data can be easily missed by any human or a traditional tool with less accuracy and speed.
2) Predictive analytics
No matter how much data you collect, it's of no use if you can’t refine it properly and gain insights. It's not practically possible to get accurate results when the data is transmitted from different channels, like satellite images, web apps, videos, sensors, etc. By contextualizing the data with the help of AI, you can anticipate threats that may cause trouble to your organization in the future and take preemptive actions to resolve those threats.
3) Automated interactions
At the end of that day, the key element that justifies your efforts is customer satisfaction. AI can help you pick those services that match the tastes of your consumers. You can offer better financial recommendation plans and proactive consumer support with AI adaptation in devices like chatbots and virtual assistants. Chatbots can quickly address and resolve their issues on time. With this level of comfort, there is no way consumers won’t come back to you.
4) Behavioral biometrics
Your consumers no longer have to memorize their difficult PINs and credentials. They just have to show up and get scanned for biometrics! Many big financial technology companies, like Mastercard and Paypal, are using behavioral biometrics to assess consumer behavior, voice, heartbeats, and expressions. By 2027, the global value of biometrically authenticated remote mobile payments will rise to $1.2 trillion, and it is expected to become more prevalent in the fintech sector.
5) Security orchestration
Both orchestration and AI need to be in perfect sync to create an effective payment strategy. If it is directed properly, you can deliver better accuracy and automate threat response. As Yash Prajapati, our penetration tester at Webelight Solutions Pvt. Ltd., rightly said, “Security orchestration, powered by AI, allows us to streamline and automate responses to emerging cyber threats. This approach ensures that fintechs' digital infrastructures remain resilient, adaptive, and secure against the constant wave of evolving threat.” By doing this, we can derive insights from a large volume of data and oppose any cyber threat.
6) Risk assessment
As you already know, fintech solutions have been using manual processes and statistical models for managing cyber security risks. However, these methods fail when you are dealing with a vast amount of data. To analyze historical data and identify fraudulent patterns, NLP technology, and machine learning algorithms are used by financial technology firms in their AI models. ML algorithms keep on learning from new data and refine their accuracy over time.
Obstacles in Fintech that can be mitigated with AI
1) Data breach
As quoted by Sun Tzu, a Chinese military general and strategist, “All warfare is based on deception.” The same logic applies to data breaches in financial transactions. Hackers can easily break into your database with deception and steal all your data. These breaches can only be resisted with AI-powered cybersecurity solutions. It is about time you stop relying on traditional intrusion detection systems and firewalls to save vulnerable consumer data.
2) Bias and fairness
Surprisingly, AI algorithms have proven to be biased. They can’t exactly assess the creditworthiness or the fairness of information unless they are properly programmed to do so. Any form of data that is fed into AI and ML algorithms needs to be properly investigated to eliminate bias. In the quest for quick and relevant information, you shouldn’t forget to check for its fairness and correctness.
3) Third-party risks
The complexity of depending upon third-party vendors has evolved exponentially in the AI area. While collaborating with them, you are also giving them access to vulnerable consumer data. It can increase the likelihood of unauthorized access to your financial systems. Any disruptions experienced by the third-party vendor can cause an impact on your operations as well. To avoid this, you must conduct rigorous due diligence and frame penalties for data manipulation.
4) Regulatory compliance
For consumer safety, regulatory bodies across the globe have set their guidelines and rules for fintech. Not complying with these regulations can land your organization in trouble in the form of penalties and credibility. With AI, you can analyze millions of transactions in a matter of seconds and detect risks. AI integration can drastically reduce the chances of cyberattacks and make sure that your organization lives up to the compliance standards. Have a look at these prominent regulatory bodies and policies that always keep an eye on you.
Imagine complying with these Regulations without expert AI help
1) Consumer Financial Protection Bureau (CFPB)
CFPB is a U.S. government agency that has control over lenders, banks, and even non-bank entities. It is a department that keeps an eye on the financial services provided to your consumers. More than 4 million consumer complaints have been received by CFPB, and it is resolving them promptly.
2) Securities and Exchange Commission (SEC)
SEC is a federal government regulatory body launched after the notorious stock market crash in 1929 that defends shareholders from financial fraud and maintains the fairness and integrity of financial transactions. Its job is to also validate that financial technology firms give a transparent disclosure of their business, like the securities they are trying to sell and the risks associated with that.
3) Office of the Comptroller of the Currency (OCC)
The OCC, too, is a federal agency appointed by the President that supervises the laws relevant to national banks. It regulates several aspects like asset quality, liquidity, capital, sensitivity to market risk, and compliance. It has the authority to take action against national banks and reject applications for new bank branches.
4) Anti-Money Laundering (AML) Regulations
As per the United Nations Panel, it's projected that around $1.6 trillion worth of money is laundered every year. To deal with manipulated financial records and inflated asset valuations, many countries have implemented robust AML regulations to locate and intercept money laundering businesses.
5) General Data Protection Regulations (GDPR)
Known as one of the toughest nuts to crack, GDPR is a framework that defines guidelines for the collection and processing of financial records. Consumers have the right to know what the financial technology companies are doing with their sensitive data. Violation of its policies, privacy, and security standards can result in heavy fines and penalties.
6) Revised Payment Services Directive (PSD2)
The revised PDS2 improves upon the original European Union rules created by PSD. PSD2 aims to make payments more secure and provide a platform for payment service providers. PSD2 is further amplified by regulations set on cybersecurity in fintech for operational issues and managing cyber security risks.
7) Electronic Identification and Trust Services (eIDAS)
The eIDAS regulation ensures a safe and fast electronic transaction between users and organizations. eIDAS monitors the audit processes and security protocols of companies that provide electronic trust services. It has created a framework for electronic seals, signatures, time stamps, and documents.
8) Payment Card Industry Data Security Standard (PCI DSS)
PCI DSS is a council formed by major payment brands, and it is governed by the PCI SSC. It makes sure that all financial technology companies conduct transactions through a secure channel. A PCI certification helps build consumer trust in a company as they get the assurance of the safety of their sensitive information.
9) ISO/IEC 27001
ISO/IEC is an internationally recognized organization established to protect intellectual property and information assets. It is an organization that helps in managing data and safeguarding information. Having this certification gives a boost to the company’s reputation and customer acquisition rate.
Future of fintech cybersecurity with AI
With the establishment of robust regulatory standards, your fintech solutions must prioritize the safety and privacy of data and comply with these regulations. This is not going to be easy, since cybercriminals are evolving their tactics with AI and making it harder for you to maintain impenetrable security standards.
One key focus area would be the encryption of sensitive data, where you should definitely invest your money to integrate advanced AI encryption technologies into your infrastructure. For robust security, devSecOps integration is also necessary to make sure that security protocols become an internal part of the fintech software development cycle. Last but not least, you need to follow a zero-trust approach for your fintech, where every user and device will be thoroughly authenticated before granting access.
Fortify financial data with our AI-driven cybersecurity solutions
We recognize that robust security should be an integral component right from the beginning of the Software development cycle. As data threats evolve, so does our organization’s approach to dealing with them. We always maintain intelligent cybersecurity standards from the initial stages till production to safeguard your final product and make sure it can’t be hampered by cyber criminals. No matter how hard cybercriminals try, our penetration testers and cybersecurity experts at Webelight Solutions Pvt. Ltd. are always going to be one step ahead of their tactics. They are up-to-date with modern penetration testing and ethical hacking practices.
As far as the integration of artificial intelligence and machine learning is concerned, our team is proficient in smoothly incorporating AI and ML into your security architecture. We have been working with the latest and most advanced cybersecurity technologies to improve the growing problem of data privacy and cybersecurity in fintech.
When there are so many government regulations your organization needs to comply with, it's natural for you to hesitate before choosing any firm for AI-backed cybersecurity solutions. But we assure you that our team will strike the perfect balance between innovation and compliance and create something magical for your fintech.
