AI on the Frontline: 5 Strategies to Boost Banking Security

With rapid digitization, the finance and banking industry has witnessed remarkable transformations, bringing both convenience and new challenges. Regulatory compliance, data security, and risk management are key concerns for financial institutions looking to stay secure and competitive.

By leveraging the power of AI, banks are now better equipped to tackle these challenges head-on. From advanced fraud detection systems to personalized financial insights, AI-driven solutions are revolutionizing how financial institutions protect their data, assets, and reputations.

Let’s explore five AI-driven approaches to fortifying banking security.

The Problem: Missteps in risk management can lead to financial losses, damaged reputations, and even industry-wide crises. The trickiness of risk management lies in the complexity and uncertainty of the financial landscape; market volatility, regulatory changes, cybersecurity threats, and economic fluctuations cause new risks to emerge. And the interconnectedness of global financial systems amplifies the issue, making it harder for banks to monitor and mitigate risks effectively.

The AI Solution: Financial risk management relies on gathering and analyzing huge swaths of data—something AI happens to be great at. By analyzing vast amounts of financial data, market trends, and customer behavior, machine learning algorithms can help review loan applications and highlight potential risks. You can easily assess creditworthiness, evaluate investment opportunities, and analyze market conditions to make more informed decisions.

The Problem: Banks face stringent regulations, such as anti-money laundering (AML) and know-your-customer (KYC) guidelines, designed to prevent financial crimes and protect customers' interests. The constant introduction and revision of regulations require monitoring, interpretation, and implementation to ensure compliance. These shifting responsibilities can burden institutions as they strive to maintain compliance while also focusing on core operations.

The AI Solution: AI-powered RegTech can streamline the compliance process by automating how big data is monitored and analyzed. These systems can flag suspicious transactions, identify potential money laundering, and conduct due diligence on customers more efficiently than manual processes. Plus, AI algorithms can adapt and learn from new regulations and evolving crime patterns, ensuring that banks stay up to date with compliance requirements.

The Problem: The sensitive nature of financial data makes it an attractive target for cybercriminals. According to a 2022 report from IBM, the average data breach costs $4.35 million. The complexity of financial institutions' digital infrastructure and the evolving threat landscape make data security a challenge—but it’s a challenge that’s essential to solve.

The AI Solution: AI algorithms can monitor network traffic, user behaviors, and system activities, so you can detect anomalies and security breaches early. By leveraging machine learning techniques, AI systems can learn from historical data to identify patterns indicative of cyber threats and proactively alert security teams, thereby reducing response time and minimizing the impact of attacks.

According to IBM, organizations with “fully deployed security AI and automation” save $3.05 million on data breaches, compared to orgs with zero AI or automation in security. AI-savvy companies also “experienced on average a 74-day shorter time to identify and contain” data breaches, compared to organizations lacking security AI.

The Problem: When fraud goes undetected, it can lead to damaged customer trust, regulatory penalties, legal consequences, and financial losses—about $48 billion annually. Fraudsters’ constantly evolving tactics make detecting their activities especially challenging, and the increasing volume and complexity of financial transactions make it difficult to differentiate legitimate activities from fraudulent ones.

The AI Solution: Chase Bank uses AI to flag consumer fraud. How? By analyzing large volumes of data, including transaction history, customer behavior patterns, and real-time information, AI algorithms can flag suspicious activities, protecting both the bank and its customers. It’s no wonder publications like Insider Intelligence have awarded Chase for its superior Security and Reliability.

The Problem: The stakes are high when it comes to securing user access. Financial institutions hold vast amounts of personal data, making them attractive targets for cyber crimes like identity theft and fraudulent transactions. While attackers employ phishing, social engineering, or malware to bypass security measures, customers themselves can be a weak link. Poor password strategies, falling for scams, or disclosing confidential information are all possible vulnerabilities.

The AI Solution: AI technology enables the use of biometric authentication methods, like facial recognition, voice recognition, and fingerprint scanning, for secure and convenient access to banking services. It’s an extra layer of security that eliminates the need for passwords or PINs, which can be compromised or forgotten. AI algorithms can compare biometric data to authenticate users accurately, reducing the risk of unauthorized access.

AI has the potential to revolutionize banking in many ways, but we need the right staff to build these tools. FinTech companies like Intuit, Splash Financial, and FreshBooks have partnered with Jobsity staff to develop cutting edge projects, and you can too.

Partnering with Jobsity allows you to innovate with new solutions while staying within budget and on schedule. Your FinTech team doesn’t have to be held back by hiring bottlenecks or restrictive budgets.

Ready to revolutionize finance? Connect with Jobsity to get the staff you need in 2 business days or less.