AI's Impact on Financial Services: Smarter, Safer, Personalized

In this exclusive interview, Amit Taneja, a seasoned financial technology expert based at Mitchell Martin, USA, explores how Artificial Intelligence is revolutionizing the finance industry. With a focus on risk management, personalization, and operational efficiency, his recent research dives deep into AI's real-world impact.

Q: Amit, let's begin with the big picture. Why is AI such a game-changer for financial services?

Amit Taneja: Great question. Financial services have always been data-rich. But historically, we've lacked the tools to make full sense of all that data in real-time. AI changes that. It enhances decision-making, automates routine tasks, and drastically improves risk management. By using machine learning, natural language processing (NLP), and predictive analytics, institutions can now detect fraud quicker, execute trades faster, and personalize services for millions of customers at once.

Q: Speaking of fraud, how does AI revolutionize fraud detection compared to traditional methods?

Amit Taneja: Traditional systems are rule-based and operate in batches, so they often lag behind real-time threats. They also generate many false positives. In contrast, AI-powered systems use machine learning to analyze structured and unstructured data simultaneously—like transaction histories, device fingerprints, and even behavioral biometrics. This allows for real-time detection with higher accuracy. For instance, Mastercard's Decision Intelligence reduced false declines by 50% while improving fraud detection. That's transformative.

Q: Let's talk trading. How does AI influence algorithmic trading?

Amit Taneja: AI pushes algorithmic trading to a new frontier. Traditional trading relies on predefined rules, but AI-based models, especially deep learning and reinforcement learning systems, can learn from market behavior and adapt dynamically. They analyze massive datasets, including news sentiment from NLP tools, and execute trades in milliseconds.

For example, a study from JPMorgan found AI strategies delivering a 10.3% average annual return versus 5.9% from traditional methods. And they also help reduce transaction costs and boost market liquidity.

Q: AI is also making waves in personalized banking. What does that look like in practice?

Amit Taneja: Personalized banking is no longer a luxury; it's an expectation. AI enables banks to understand customer behavior at a granular level. It uses past transactions, demographics, and online interactions to build rich customer profiles. Then, through machine learning and NLP, banks can recommend personalized products like the right loan or investment strategy just when the customer needs them.

Studies show banks using personalization see up to 33% increases in customer satisfaction and 20% improvements in retention. It's about making customers feel seen and valued.

Q: AI isn't without its challenges. What are the major hurdles in the financial sector?

Amit Taneja: Absolutely. The three main challenges are:

1. Regulation and Ethics: AI must be fair, explainable, and accountable. Financial decisions can't be a "black box," so there's growing pressure from regulators to ensure AI is auditable and unbiased.
2. Data Privacy and Security: With increasing cyber threats, protecting sensitive financial data is a top priority. Compliance with GDPR, CCPA, and other regulations is essential.
3. Integration with Legacy Systems: Many financial institutions still use outdated infrastructure. Integrating modern AI systems requires major upgrades and change management, including employee training.

Q: What does the future of AI in finance look like?

Amit Taneja: The future is both exciting and complex. I see three key directions:

• Explainable AI (XAI) will help build trust by making AI decisions transparent.
• Privacy-preserving AI, like federated learning, will enable secure model training without data exposure.
• Convergence with emerging tech, especially blockchain and IoT, will create smarter, more decentralized financial ecosystems.

Ultimately, collaboration between banks, tech providers, regulators, and researchers is essential to ensure innovation is both responsible and sustainable.

Q: Any final thoughts you'd like to leave us with?

Amit Taneja: AI is not just a technological upgrade; it's a paradigm shift. Its power lies in combining human intuition with machine intelligence. But to truly unlock its potential, we need to focus as much on trust and transparency as we do on performance. The future of finance will be built on this convergence.