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How Smart Agents Are Changing Secure Banking

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Publication date: 10.04.2025

AI is no longer just hype in fintech. It’s here – and it’s changing how banks build software, fight fraud, and serve people. The new heroes? Smart agents. They don’t just answer questions – they act. They detect fraud, test software, and move fast.

Let’s dive into how AI-powered fintech makes banking safer and smarter.

Smart Agents: The Next Step in Fintech

Smart agents don’t wait for instructions. They work on their own.
Unlike chatbots with canned replies, these agents handle tough jobs:

  • Process payments
  • Spot risks
  • Test updates

Banks work with oceans of data – customer records, payments, rules. Old tools can’t keep up. Smart agents sort through the noise and act fast.

This is not a tech demo. It’s real value.
In 2024, 60% of financial firms used AI. By 2027, that number will jump to 85%. Why? Because AI cuts time, reduces costs, and improves trust.

Examples:

  • Software testing in hours, not days
  • Pattern spotting in seconds
  • Real-time insights for better decisions

According to KPMG, fintech investments hit $95.6 billion in 2024. AI is leading that wave. Smart agents help teams work faster – catching bugs, predicting cash flow, and streamlining systems.

Few successful projects of WislaCode
Explore AI testing
Exploring the State and Future of AI Testing
Defining the Core System Architecture
Mobile banking app with an innovative user experience

Smarter Security with AI

In banking, security is everything. Customers expect it. Regulators demand it.

Smart agents don’t just respond to threats – they find them before they spread.

Imagine this:
You open a banking app. It checks your face, your phone, your location. In seconds, it knows it’s really you.

This layered approach stops fraud without slowing you down.

How Smart Agents Boost Security:

  • Spot risks fast: Detect strange behaviour (like sudden transfers)
  • Layered checks: Combine biometrics, GPS, and device ID
  • Auto-encryption: Secure data flows in real time

Old systems can’t match that. Manual checks are too slow.
Phishing, ransomware, deepfakes – all growing threats. In 2023, the average banking breach cost £4.5M (IBM). Smart agents lower that risk – fast.

“Fraud dropped by 40% after we added smart agents to payments.” – Fintech Developer

Practical AI That Solves Real Problems

Forget AI buzzwords. What matters is impact.

Smart agents help banks solve real problems:

  • Automate compliance reports
  • Speed up loan approvals
  • Personalise customer advice

What Can Smart Agents Do?

TaskJobResult
ID VerificationMatch faces to IDsFast signup, less fraud
Risk MonitoringFlag strange behaviourLess loss, more trust
Loan ApprovalsAnalyse spending, decide fastLower cost, happy clients

A McKinsey study showed that AI tools cut banking costs by 20% and boosted customer satisfaction by 15%. That’s not just nice – that’s a win.

But AI still needs clean data. Messy input means messy results. The right setup is key.

Fit for Any Bank – Big or Small

Small fintech? Use smart agents to check IDs.
Big bank? Use them for real-time market analysis.

The tech scales. It adapts to your goals – speed, security, or savings.

Quick wins with smart agents:

  • Faster launches (bug-free apps)
  • Fraud prevention (live monitoring)
  • Better support (personal tips)
WislaCode develops modern banking solutions

Effective use of artificial intelligence requires a deep understanding of the entire ecosystem, including trust, security and flexibility.

How We Help: Real Results at WislaCode

At WislaCode, we’ve seen it first-hand.

We’ve built systems that:

  • Cut fraud using face ID
  • Tested full apps in half the time
  • Improved onboarding with smart checks

With 24+ years in fintech, we go beyond building – we align tech with your strategy. Whether you’re a lean startup or a global bank, we tailor the solution to your challenge.

Special thanks to our partners at Productera.io for their insights in this podcast.

Let’s Talk About Your Next Banking Move

Facing a tough problem in fintech software?
We’re here to help.

At WislaCode, we build secure banking tools powered by AI. Smart agents are changing the game – and we’ll make them work for you.

Get in touch. Let’s turn your idea into something real.

FAQ: How Smart Agents Are Changing Secure Banking
Autonomous AI agents in banking are advanced software entities capable of making independent decisions and taking actions without constant human oversight. Unlike traditional rule-based systems or basic chatbots, these agents can process vast amounts of data, learn from patterns, and adapt to new threats or opportunities in real time. This autonomy allows banks to respond to risks and customer needs much faster, improving both security and service quality.
AI-driven financial security tools use machine learning and data analytics to monitor transactions, detect anomalies, and flag suspicious activities instantly. These tools can identify complex fraud schemes that might go unnoticed by manual checks, providing a proactive layer of defence. For customers, this means their accounts are continuously monitored, reducing the risk of unauthorised access or financial loss.
Intelligent fintech automation refers to the use of AI to streamline and optimise banking operations, from customer onboarding to loan approvals and compliance reporting. By automating repetitive and time-consuming tasks, banks can reduce operational costs, minimise human error, and deliver faster, more reliable services. This efficiency is crucial for staying competitive in the rapidly evolving financial sector.
Real-time fraud detection leverages AI algorithms to analyse transaction data as it happens, instantly identifying unusual patterns or behaviours that may indicate fraud. For example, if a customer’s account is accessed from an unfamiliar location or a large transfer is attempted, the system can flag or block the transaction immediately. This rapid response helps prevent losses and builds trust with customers.
AI-powered compliance monitoring automates the process of ensuring that banks adhere to regulatory requirements. These systems can scan transactions, customer data, and internal processes for compliance issues, generate reports, and alert staff to potential breaches. This not only reduces the risk of regulatory fines but also frees up human resources for more strategic tasks.
Biometric identity verification uses unique physical characteristics – such as fingerprints, facial recognition, or voice patterns to confirm a user’s identity. Smart agents can integrate these checks seamlessly into banking apps, making it much harder for fraudsters to gain access. This approach enhances security while keeping the user experience smooth and convenient.
Predictive risk analytics involve using AI to forecast potential risks by analysing historical and real-time data. Smart agents can identify trends that may signal emerging threats, such as increased fraud attempts or market volatility, allowing banks to take preventive action. This forward-looking capability helps institutions manage risk more effectively and maintain financial stability.
Personalised banking recommendations use AI to analyse individual customer behaviour, preferences, and financial goals. Smart agents can suggest tailored products, savings plans, or investment opportunities, making banking more relevant and engaging for each user. This level of personalisation not only increases customer satisfaction but also helps banks build stronger, long-term relationships.
About the Author

Viacheslav Kostin is the CEO of WislaCode. Former C-level banker with 20+ years in fintech, digital strategy and IT. He led transformation at major banks across Europe and Asia, building super apps, launching online lending, and scaling mobile platforms to millions of users.
Executive MBA from IMD Business School (Switzerland). Now helps banks and lenders go fully digital - faster, safer, smarter.

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