Next-Gen Tech: What Drives Financial Sector Performance

The financial world moves faster than most bankers can keep up with. AI, quantum computers, blockchain – these aren’t buzzwords anymore. The world’s largest banks are dumping billions into these technologies because whoever figures them out first gets to set the rules for the next decade.

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Why Banks Can’t Stay on Old Systems Anymore

Most financial institutions still run on systems built 20-30 years ago. Legacy platforms prevent modern AI implementation, slow down new product development, and limit personalization capabilities. Meanwhile, regulators keep tightening requirements, cybercriminals refine their methods, and fintech startups poach customers.

That is why banks are actively working on modernization to:

• Upgrade infrastructure while keeping everything running
• Get AI working across their operations
• Build better defenses against cyber attacks
• Cut costs wherever possible
• Actually give customers what they want

Investors know the score. A bank’s tech stack matters just as much as its quarterly earnings now. Maybe more.

AI in Banking: Real Numbers, Real Impact

What JPMorgan Chase Does With $17 Billion

In 2024, JPMorgan Chase allocated $17 billion to technology — the largest figure among all financial institutions worldwide, more than Bank of America ($12 billion) and Wells Fargo ($4 billion) combined.
Half of the budget goes toward maintaining existing infrastructure. The other half is invested in developing new solutions, with AI at the core.

Tangible results of AI adoption at JPMorgan:

• KYC processes: In 2022, the bank processed 155,000 files with 3,000 employees. By 2025, they plan to process 230,000 files (50% more) while using 20% fewer staff.
• Cash Flow Intelligence AI: reduces manual work by 90%.
• IndexGPT: delivers personalized investment advice to clients in real time.
• LLM Suite: a platform based on models from OpenAI and Anthropic that provides employees with instant answers and decision support.

Goldman Sachs is also heavily investing in AI. The bank acquired venture firm Industry Ventures for $665 million, with an additional $300 million committed through 2030. The funding targets startups developing solutions for trading, risk management, and back-office automation.

Where AI is most beneficial

Area	What It Does	What Changes
Credit scoring	Analyzes massive borrower datasets	Better lending decisions, fewer defaults
Fraud detection	Watches transactions as they happen	Blocks suspicious activity in seconds
Customer service	Chatbots and virtual assistants	Handles 80% of requests without human help
Risk management	Predicts market movements	Faster reactions when things go sideways

IT Ukraine Association reports that 90% of fintech companies worldwide use AI and machine learning now. 

Cloud Migration at Scale

JPMorgan’s Infrastructure Overhaul

JPMorgan plans to cut data centers from 32 to 20 while moving more into public and private clouds. Right now, 50% of applications and 70% of data sit in the cloud. By year-end, they want 70% and 75% respectively.

The bank has over 30,000 employees with cloud certifications. That’s not dabbling — that’s institutional commitment.

How Major IT Companies Enable This

Banks don’t replace core systems in one move. Old platforms usually stay in place while new ones are added around them, often for years. Because of that, banks work with several technology vendors, each covering a specific part of the stack.

Some companies focus on infrastructure, others on integration or automation. IBM, Accenture, and Capgemini are often involved in modernization projects. Providers like TCS, Infosys, and Cognizant help extend existing core systems without disrupting daily operations.

DXC Technology provides IT solutions for financial services that actually work at scale. Their Hogan platform handles six of the ten largest US banks, supports 300 million deposit accounts, and processes two-thirds of all card transactions in America.

Why Hybrid Clouds Win

Most banks split their infrastructure:

• Private clouds hold the most sensitive data where they control everything
• Public clouds (AWS, Azure, GCP) run less critical workloads and test environments
• On-premise systems stay for legacy applications too risky or expensive to move

This balances security, cost, and the ability to actually ship new features.

Quantum Computing Gets Real

Why Quantum Changes Everything

Regular computers use bits — either 0 or 1. Quantum computers use qubits that can be both at the same time through superposition. This lets them crunch numbers that would take normal computers centuries.

McKinsey thinks quantum computing could be worth $400-600 billion to finance by 2035.

Banks Testing Quantum Right Now

1. Yapı Kredi Bank (Turkey): Used quantum technology from D-Wave to analyze financial risks. What would have required years of classical computing was completed in just 7 seconds.
2. Intesa Sanpaolo (Italy): Together with IBM, the bank is testing quantum machine learning for fraud detection. The quantum model showed higher accuracy while requiring less data.
3. HSBC: Are experimenting with quantum key distribution (QKD) — a form of encryption that is theoretically impossible to crack.
4. Danske Bank: Danske Bank ran Scandinavia’s first quantum-protected data exchange outside a lab. They’re preparing for when regular encryption becomes useless against quantum attacks.

Logical (stable) qubits required for industrial-scale use are still under development. However, banks already understand that those who start adopting quantum solutions early will gain a major advantage in analytics, risk management, and security.

Blockchain Beyond Crypto

Market Growth That’s Hard to Ignore

The blockchain market grew from $3.67 billion in 2020 to $31.28 billion in 2024. Forecasts put it at $1.4 trillion by 2030. That’s roughly 90% annual growth.

What Banks Actually Do With It

Grupo Santander in Spain built One Pay FX on blockchain to move money between Europe and South America. Transactions go faster and cost less. Goldman Sachs invests heavily in Circle and other crypto projects while building blockchain settlement systems for institutional clients. Deutsche Bank tests blockchain for regulatory reporting because immutable transaction records make compliance easier.

The technology has problems. Proof-of-Work burns massive amounts of energy. Scaling remains difficult. No global standards exist yet. Different jurisdictions can’t agree on regulations. But costs keep dropping and banks keep experimenting.

Cybersecurity Gets Worse Before It Gets Better

Hackers stole $2.3 billion globally in 2024 — 40% more than 2023. UK banks lost $1.6 billion to fraud. The British government allocated $162 million in April 2025 for quantum technology research specifically to fight financial crime.

The US National Institute of Standards and Technology (NIST) released a set of post-quantum encryption standards in August 2024. The problem: when quantum computers become powerful enough, they’ll crack modern encryption in hours. Banks therefore need to start migrating to quantum-resistant algorithms now. Some are already preparing:

• Banque de France tests post-quantum encryption on critical channels with full migration targeted for 2027.
• Bank of England develops quantum-safe protocols for interbank settlements and runs simulations of quantum attacks to find vulnerabilities before real attackers do.

Automation That Actually Matters

RPA has been around about ten years now. It automates repetitive tasks by following strict rules but can’t make decisions. Intelligent automation combines RPA with machine learning so systems can handle complex work, adapt to new situations, and make data-driven decisions.

Real Deployments at Major Banks

JPMorgan’s Cash Flow Intelligence AI slashes manual work by 90%. IndexGPT personalizes investment recommendations for thousands of clients at once. The bank processes over $6 trillion in consumer payments annually, and automation touches all of it.

Citigroup implemented RPA for securities transactions. Processing time dropped from hours to minutes. Operational costs fell 30% in those divisions. BNP Paribas uses AI to review credit applications automatically. Decisions that took days now take hours, and approval rates went up because the risk analysis got better.

Why Investors Care About Tech Spending

Banks with serious IT budgets show they’re ready for long-term competition. Investors watch this closely now. Strong tech investments correlate with better stock performance. Fintech companies with proven AI get higher valuations. Banks that fall behind lose market share to faster competitors.

JPMorgan gets called “the NVIDIA of banking” because of how much they spend on technology. CEO Jamie Dimon says AI will touch every single process in the bank. Not as marketing talk — as operational reality that already shows up in productivity numbers.

Where Money Goes in Fintech

Global fintech funding dropped to $95.6 billion in 2024 as investors got more careful. But payments still pulled $31 billion compared to $17.2 billion in 2023. Money follows results, not promises.

Top investment areas for 2024-2025:

1. AI and machine learning for financial services
2. Payment infrastructure
3. Blockchain and Web3 tech
4. RegTech for compliance automation
5. Cybersecurity and fraud prevention

The Legacy System Problem and Human Factor

Many banks run on platforms built in the 1980s and 90s. These systems use COBOL and Fortran — languages hardly anyone codes in anymore. The architecture is complex and poorly documented. They’re too critical to shut down but cost millions yearly to maintain.

What goes wrong during modernization

Problem	Impact	How to Fix It
Missing documentation	Nobody knows how it actually works	Migrate gradually through APIs
Downtime risk	Every minute offline costs money	Run old and new systems in parallel
No qualified staff	Few programmers know COBOL	Hire specialized firms like DXC or IBM
Integration issues	Legacy doesn’t speak to modern systems	Build middleware layers

The Human Factor

Technology isn’t just code and hardware. It’s also people who must learn to work differently.

Main challenges:

• Employees fear AI will replace them
• Lack of skills for new tools
• Resistance to change from old-school management
• Difficulty coordinating between IT and business units

Successful banks invest not only in technology but also in staff training. JPMorgan spends $1 billion annually on employee development programs.

The future of banking technology: predictions for 2025-2030

Quantum Goes Commercial

By 2030, reliable logical qubits should be available commercially. Banks will predict market movements with accuracy that seems impossible now, optimize portfolios in real time, and model complex scenarios in seconds. The institutions building quantum expertise today will dominate.

Blockchain Becomes Infrastructure

Central banks test digital currencies worldwide. The ECB works on digital euro with pilots through 2026. Bank of England researches Britcoin. The Fed studies digital dollars. Blockchain stops being future tech and becomes part of everyday banking.

Cybersecurity Gets More Expensive

As quantum computers get stronger, so do threats. Banks need post-quantum encryption, zero-trust architecture, AI-powered threat detection, and staff training for new attack types. Cybersecurity spending jumps from $200 billion in 2024 to over $500 billion by 2030.

Conclusion: Technology is shaping the future of finance

Fintech startups, unburdened by legacy systems, can roll out innovation in months. Large banks, by contrast, benefit from scale, capital, and customer trust, but tend to move more cautiously due to their conservative nature.

That said, even the biggest institutions have become far more open to change in recent years. JPMorgan, Goldman Sachs, BNP Paribas, and Deutsche Bank are all investing billions in AI, quantum computing, blockchain, and cybersecurity — not because it’s trendy or meant to appeal to Gen Z, but because it’s essential for survival in a world where customers expect more personalization, better services, and faster experiences.

The next few years will show which banks can successfully navigate this AI-driven wave of digital transformation. Traditional banking as we once knew it is clearly changing for good. Some institutions will disappear, while new ones will take their place. And cryptocurrency payments may well become as commonplace as PayPal.

But for now, we’ll wait and see — these are still assumptions and forecasts.

Common Questions About Banking Technology

• Will AI replace bank employees?

  AI handles routine tasks but doesn’t eliminate jobs wholesale. People shift to work that needs creativity, judgment, and human interaction. JPMorgan expects role changes, not mass layoffs.

• Are quantum computers safe for financial data?

  Quantum creates threats and solutions simultaneously. Current encryption becomes vulnerable, but quantum-safe encryption exists. NIST published standards, and banks are implementing them now.

• Why can’t banks just upgrade everything quickly?

  Legacy systems keep the bank running. You can’t risk downtime. Regulations require extensive testing. Modernization has to happen in phases while maintaining operations.

• What’s a hybrid cloud and why use it?

  Hybrid combines private clouds for sensitive data with public clouds for everything else. You get security where you need it and cost efficiency where you can have it.

• How do you know if a bank takes tech seriously?

  Read annual reports. Look for IT investment numbers, tech partnerships, AI implementation details. Banks with real strategies explain their projects instead of just mentioning “digital transformation.”