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Fintech: A Practical Guide to the Industry, Technologies, and Trends

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Technologies
4.06.2025
Fintech is one of the most popular IT industries: the number of applications and products increases every year. Who doesn't use a mobile banking app or pay bills online, for example?

Recognising the increasing interest in the fintech sector among IT professionals and non-IT individuals, and given our extensive expertise in hiring IT specialists for fintech companies worldwide, we decided to delve into the industry's prospects, current trends and sought-after specialists.
A practical perspective on the fintech market was shared with us by Kirill Gurbanov — founder of the consultancy Fintech Experts & Partners, Managing Partner and Board Member at Samolyot Group Bank, and Head of Digital Business at MTS Bank.
In this article:
1. What is Fintech
2. A Brief History of Fintech
3. Fintech’s Core Goals
4. What Makes Fintech Different
5. Risks in Fintech
6. Regulation in Fintech
7. Key Areas of Fintech
8. How a Fintech Service Works
9. Launching a Fintech Product
10. Technologies in Fintech
11. AI in Fintech
12. Fintech & Blockchain
13. Top 8 Fintech Roles
14. Global Fintech Market
15. Fintech Investment Trends
16. The Future of Fintech: Key Trends
17. Hiring in Fintech: What Makes It Different

What is Fintech

Fintech (short for financial technology) refers to an entire industry — and a broad range of tools, products, and business models — designed to deliver financial services through modern technologies. These solutions automate and streamline everything from payments and loans to accounting, investing, and insurance.

Not long ago, most financial transactions required a trip to the bank. Today, nearly everything can be handled from your phone.

At its core, fintech sits at the intersection of three domains:
  • Finance — where compliance, asset security, and precision matter.
  • Technology — from app development and data engineering to large-scale analytics.
  • User experience — because customers will always choose the fastest, simplest, and most convenient service.
But fintech isn’t just about sleek interfaces. Behind the scenes, it’s a complex infrastructure of scoring systems, anti-fraud tools, Open Banking protocols, and embedded finance solutions seamlessly integrated into e-commerce and SaaS ecosystems.

Digital financial technologies aren’t just changing how people interact with money — they’re reshaping the architecture of the financial system itself. Automating operations, reducing costs, enabling real-time access via APIs — fintech has become one of the key drivers of digital transformation in banking and beyond.

How Fintech Differs from Traditional Banks

Fintech companies and banks both operate in the financial services space — but their approaches differ significantly. Traditional banks rely on time-tested processes, heavy regulation, and stability. Fintechs compete on speed, agility, and a user-first mindset.

Here’s a breakdown of the key differences between fintechs and traditional banks:
In practice, the gap between banks and fintechs is narrowing. More and more traditional players are launching digital products, investing in R&D, building out tech teams — or outright acquiring fintech startups.

At the same time, fintech companies are entering regulatory sandboxes, acquiring banking licenses, and adapting to compliance-heavy environments. The result? They’re all playing on the same field — just with different levels of speed and flexibility.

A Brief History of Fintech

The term “fintech” only entered widespread use in the last 10–15 years, but the concept of using technology to improve financial services has been around for much longer.

Fintech’s evolution can be roughly divided into four key phases — each shaped by broader technological shifts:
  • Phase 1
    Banking Goes Digital (1950s–1980s). This era marked the beginning of large-scale computerization in banking. Early financial software was developed, electronic payment systems like SWIFT emerged, and ATMs started appearing. At this point, financial technology was fully internal — used by banks to optimize operations, with no direct interaction from customers.
  • Phase 2
    The Internet Revolution (1990s–2000s). With the rise of the internet, online banking became a reality. Electronic wallets, payment gateways, and trading platforms took shape. Services like PayPal and Neteller introduced users to the idea of handling money via browser instead of branch. This was the moment fintech began reaching the masses.
  • Phase 3
    Mobile First (2010s–2020s). The smartphone boom brought an explosion of financial apps: mobile banking, smart investing, expense trackers, crowdfunding, P2P transfers — and more. Promising fintech startups matured into full-service financial platforms, while traditional banks started feeling the heat. Fintech became an integral part of everyday digital life.
  • Phase 4
    APIs, Blockchain, and Embedded Finance (2020s–today). Modern fintech is modular, flexible, and deeply integrated into digital ecosystems. This phase is marked by open banking, challenger banks, DeFi, and tools for KYC/AML automation. Financial services are now seamlessly embedded into e-commerce, logistics, travel, and edtech platforms. Fintech is no longer just a “banking alternative” — it's a core layer of the digital economy.
fintech history
History of Fintech

Fintech’s Core Goals

Fintech didn’t emerge just because “digital is trendy.” It was born out of the limitations of traditional banking — from complex processes to limited accessibility. The core mission of the fintech industry is to make financial services faster, simpler, more transparent, and scalable — powered by modern technologies.

Here are the key goals most fintech products are built around:
  • Streamlining the user experience. Every interaction with money — payments, loans, investments — should take just a few taps. UX is a top priority, not only for finance professionals, but for everyday users.
  • Automating processes and cutting costs. From scoring to customer support, fintech automates what used to require manual work — using APIs, algorithms, and AI. This reduces operational costs and allows fintech companies to scale without inflating headcount.
  • Expanding access to financial services. Fintech isn’t bound by physical branches, big cities, or rigid eligibility criteria. Thanks to technology, anyone with a smartphone can open an account, get a loan, or start investing — often in minutes.
  • Flexibility and scalability. Modern fintech products are designed to integrate easily with other services, adapt to different regulatory environments, and handle growing user loads. This makes them especially valuable for fast-moving startups and dynamic businesses.
  • Driving digital transformation in finance. Fintech doesn’t evolve in a vacuum. It pushes the entire financial ecosystem forward. Banks, payment systems, insurance providers — they all have to adapt, modernize, and compete. As a result, financial services as a whole become more user-centric and efficient.

What Makes Fintech Different

Fintech products operate in a highly competitive space — where complex tech, strict regulations, and constant pressure to scale all come together. Breaking into the market is one thing. Surviving in it requires careful planning from day one: legal compliance, architectural resilience, and an understanding of deeply layered risks.

Here’s what sets fintech apart from most other IT verticals:
  • Handling sensitive data. In fintech, you don’t get to fix bugs “later.” Financial and personal data must be processed in real time, which means tighter requirements for data storage, encryption, access control, and audit logging.
  • Compliance as part of the architecture. KYC, AML, PSD2, PCI DSS, GDPR — these aren’t checkboxes at the end of the project. Fintech products must be designed around these rules from the start. That calls for tight collaboration between engineers, legal teams, and risk managers — across the entire stack.
  • Legacy system integration. Modern fintech still relies on old-school banking infrastructure. Outdated protocols, unreliable APIs, manual workflows — they’re all part of the ecosystem. Teams have to understand these constraints deeply and find creative workarounds without breaking compliance.
  • Regulatory complexity across markets. Each country means a different set of licenses, rules, and limitations. Scaling in fintech isn’t just a tech challenge — it’s an operational and legal one. Jurisdiction, local partners, payment gateways, and market entry strategies all shape the product roadmap.
  • Hiring isn’t easy. Fintech teams need more than just coders. They need people who understand the financial domain. Alongside engineers and data specialists, companies often look for antifraud analysts, RegTech experts, licensing consultants, and designers who speak “fintech.”
Fintech is inherently cross-disciplinary. That’s what makes it powerful — and what makes building in this space uniquely complex.

Risks in Fintech

Fintech is all about speed, flexibility, and cutting-edge tech. But where money and personal data intersect, the margin for error is razor-thin. Despite their clean, user-friendly interfaces, fintech services operate in high-stakes environments where even a minor failure can cost millions — in both financial and reputational terms. Security and reliability aren’t optional. They’re foundational.

Here are the key risk areas most fintech companies face:
  • Technical risks
    Fintech products often rely on complex architecture: real-time transaction processing, external APIs, scoring and antifraud systems. Any vulnerability — from a basic XSS to a subtle logic flaw — can lead to data breaches, transaction errors, or loss of funds. Add high demands for uptime, scalability, and rapid iteration, and the technical bar becomes even higher.
  • Financial risks
    Even with automated scoring and ML-based predictions, bad loans, fraud attempts, and abuse of system loopholes still happen. Fintechs are accountable for the quality of their risk models — and the data those models rely on.
  • Information security risks
    Fintech handles highly sensitive data: money, ID documents, contracts. A leaked wallet key, altered payment details, or breach of personal records isn’t just inconvenient — it can be existential for the business.
  • Legal and regulatory risks
    Fintech products must comply with a web of regulations — KYC, AML, GDPR, and local laws, which can shift without notice. A misread clause or a delayed policy update can result in fines, license suspensions, or blocked operations.
  • Reputational risks
    For users, it doesn’t matter whether a failure is due to bad code or a sudden legal change — they’ll lose trust and move on. In fintech, trust is currency: easy to lose, hard to win back. A single media incident or system outage can cause significant damage.
According to IBM (2024), the average cost of a data breach in the financial sector is $6.08 million — 22% higher than the global cross-industry average.
While fintech risks can’t be eliminated entirely, they can — and must — be actively managed. A company’s survival depends not just on product growth, but on how well it builds architecture, compliance, and operations around risk resilience.
Fintech risks
These three causes account for over 40% of all security incidents in fintech. Source: IBM

High-Risk Fintech

Some fintech projects fall into the high-risk category from the start — due to the nature of their product, target audience, or jurisdiction.

This segment typically includes:
  • DeFi and crypto-related platforms.
  • Online lending and microfinance services.
  • Fintechs operating in markets with unstable or unclear regulation.
  • Forex trading, betting, gambling, and adult-related financial services.

These companies face tougher compliance checks from banks and payment providers. They are more likely to encounter service refusals, frozen accounts, and frequent inquiries from regulators.

In the high-risk fintech space, it’s critical to maintain clear, well-documented processes, ensure full transparency of the business model, and involve legal experts with domain-specific experience — ideally from day one.

Regulation in Fintech

Fintech is tightly linked to regulatory frameworks — both national and international. In this space, compliance comes before monetization: even the most user-friendly and technically advanced product won’t make it to market unless it meets all the relevant requirements.

And even if a business doesn’t position itself as a bank, it still falls under the scope of key financial and data regulations:
  • KYC (Know Your Customer) — onboarding and identity verification.
  • AML (Anti-Money Laundering) — fraud and laundering prevention.
  • GDPR/DPA — or local data protection laws.
  • Payment standards like PCI DSS for handling card transactions securely.
  • Licensing requirements — from payment institutions to microfinance providers.
This creates legal complexity: regulations differ widely between countries, and fintech companies must be able to adapt quickly.

What affects the regulatory landscape:
  • Jurisdiction. Rules vary significantly between the US, EU, UK, Singapore, and the UAE. Whether a license is required — and what kind — depends entirely on the market. So does the expected level of transparency and control.
  • Product type. Embedded services, neobanks, crypto platforms, or SaaS with a financial module — each of these categories falls under different sets of regulations.
  • Audience size and type. The more users a fintech product serves, the more regulatory scrutiny it tends to attract — especially when it comes to reliability and risk mitigation.

RegTech

To keep up with evolving compliance requirements, many fintechs are turning to RegTech — automated systems for transaction monitoring, anomaly detection, log management, audits, and reporting.

In some regions (e.g. the UK, UAE, and Singapore), regulatory sandboxes allow startups to test their products under regulator supervision — without having to obtain a full license right away.

What happens when compliance is ignored:
  • frozen accounts or blocked operations;
  • hefty fines or revoked licenses;
  • banks and payment providers refusing to cooperate;
  • reputational damage and loss of customer trust.

Fintech is always a balancing act between innovation and compliance. Success belongs to the companies that treat regulation not as a constraint — but as a core part of product architecture.
fintech regulation
Core regulatory requirements fintech projects must address

Key Areas of Fintech

Over the past few years, fintech has expanded to cover nearly every segment of the financial sector — from insurance and investments to accounting and even gaming. Here’s a look at some of the main domains.

Payments

One of the most mature and fast-moving fintech segments. This includes everything from contactless payments and QR codes to in-app wallets and invisible checkouts.

Payments are mission-critical to nearly every business. Today, any company can accept transactions globally thanks to payment gateways, multi-currency processing, acquiring services, and automated invoicing.
Examples: Stripe, Adyen, Checkout.com, Rapyd, Square.

Neobanking

Digital-only banks offering full financial services without physical branches or paperwork. Intuitive mobile interfaces, instant account creation, card customization, expense analytics, and push notifications have all become standard thanks to neobanks.
Examples: Revolut, Monzo, N26, Chime, Nubank.

Investments & Wealth Management

Fintech has radically transformed the investment landscape, making it accessible to the general public — not just professional brokers. A few notable categories:
  • Smart investing / Robo-advisors
    Automated, algorithm-driven portfolios based on goals, timelines, and risk profiles.
    Examples: Betterment, Wealthfront
  • Stock & ETF trading apps
    Easy access to public markets, often commission-free, via mobile apps.
    Examples: Robinhood, Freetrade, Trade Republic.
  • Crowdinvesting platforms
    Allow users to invest small amounts into startups or small businesses. High risk, but potentially high reward.
    Examples: Seedrs, Crowdcube
  • Crypto investment services
    Platforms for buying, exchanging, staking, and holding crypto. Some offer automated portfolios, yield on stored assets, and diversification tools.
    Examples: Coinbase, Binance, Bitpanda
  • Micro-investing and “round-up” apps
    Automatically invest leftover change from purchases into selected portfolios.
    Examples: Acorns, Plum
  • Educational investing platforms
    Services with simulations, learning tools, and real-time guidance — popular with first-time investors.
    Examples: Public, Invstr

Accounting & Finance Management

More and more startups and small businesses are moving away from traditional accounting in favor of fintech-powered tools. These platforms make financial operations simple, accessible, and fully automated — no need for a dedicated accountant. Features typically include invoicing, bank integrations, tax calculations, and clear financial analytics.

Fintech here often works hand in hand with SaaS and automates what used to be repetitive manual work.
Examples: QuickBooks, Xero, Zoho Books, FreshBooks, Wave.

InsurTech

Fintech is also reshaping the insurance market — making it more flexible, transparent, and user-friendly. New models offer personalized pricing based on user behavior, real-time risk assessment, API integrations, and embedded insurance (like travel coverage offered automatically when booking a flight or car).

Benefits include instant coverage (often via a single checkbox), automated claims, and clear, no-fine-print terms.
Examples: Wefox, Lemonade, Oscar Health, Root Insurance, Next Insurance.

Lending & Credit

Fintech lending spans both consumer and SME segments — from buy-now-pay-later (BNPL) models to alternative business financing.

The key differentiator is instant credit scoring, often based on behavioral data, open banking, and big data sources. This allows access to credit for users who wouldn’t qualify under traditional bank models.
Examples: Klarna, Affirm, Upstart, SoFi, Zopa.

Embedded Finance

One of the fastest-growing areas in fintech is the seamless integration of financial services into non-financial products — often in marketplaces, but also across many B2C platforms.

Examples of embedded finance:
  • In-app subscriptions without redirecting to external payment pages (e.g. Netflix, Spotify).
  • On-platform salary and payout tools for freelancers and couriers.
  • Built-in wallets and peer-to-peer transfers (e.g. Uber Cash, Grab Wallet).

Fintech in e-commerce:
  • Instant credit or installment options directly in product cards.
  • Platform-branded payment cards (e.g. Amazon Store Card).
  • Cashback or reward points redeemable with partners.
  • Seller financing directly through the marketplace interface.

E-commerce is where embedded fintech shines — from one-tap payments to installment plans and integrated wallets.
Examples: Plaid, Railsr (Railsbank), Marqeta, Unit, FintechOS.

Financial Education & Planning

Fintech isn’t only about spending — it’s also helping users organize their money. From budgeting tools and savings planners to gamified apps that make financial literacy more engaging, this space is growing fast. Many platforms offer reports, insights, and recommendations.
Examples: YNAB (You Need A Budget), Cleo, Mint, Emma, Buxfer.

DeFi (Decentralized Finance)

Blockchain-based apps that work without banks or intermediaries. Lending, exchanges, derivatives — all managed through smart contracts. DeFi is an open-source, globally accessible alternative financial ecosystem.
Examples: Aave, Uniswap, Compound, MakerDAO.

ESG Fintech

The sustainability trend has reached fintech as well. ESG platforms help users invest with environmental, social, and governance factors in mind — through analytics tools and brokers offering “green” portfolios.
Examples: Ethic, OpenInvest, Impax, Trine.

Gaming & the Metaverse

Fintech is powering the future of digital economies: payment gateways, in-game currencies, NFT-based assets, and microtransactions for participation — all part of the next-gen financial layer.
Examples: Immutable X, The Sandbox, Enjin, Ramp.
Modern fintech is no longer a standalone sector — it’s a foundational technology layer that powers other industries and becomes embedded in the everyday digital experience.
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How a Fintech Service Works

Modern fintech products are far more complex than typical SaaS platforms. They come with stricter requirements for reliability, security, data consistency, and regulatory compliance. Even the simplest-looking interface hides a deeply layered system under the hood.

Here’s a breakdown of the core components behind most fintech applications.

Core System

At the heart of any fintech product is a set of microservices managing databases, business rules, and integrations. This is where key functions happen — account and balance management, fee and exchange rate calculations, enforcement of business logic (tariffs, limits, holds, etc.).

In traditional banking, this layer is handled by core banking systems like Flexcube or Temenos. In fintech, it’s usually a custom-built setup based on PostgreSQL, event sourcing, CQRS, and tools like Kafka, with REST or gRPC interfaces.

Identity & Access Management (IAM)

This component handles user verification and access control before any operation can occur. It typically includes:
  • KYC/KYB via external providers like Sumsub, Veriff, IDnow.
  • 2FA: SMS/email, TOTP, or push notifications.
  • Device binding and fingerprint tracking.
  • Session control, token issuance, and refresh logic.

Anti-Fraud & Risk Management

One of the most critical parts of any fintech stack. This block analyzes behavioral anomalies in real time and flags potential fraud based on a wide set of signals:
  • Rule engines for IP, geo, transaction velocity, and behavior patterns.
  • ML models for behavioral scoring and user profiling.
  • Blocking mechanisms, alerts, manual moderation.
  • Full fraud pipeline: from scoring to investigation and back-office case handling.

Integrations

This module connects the fintech platform with the outside world — and it’s what enables the product to function in a broader ecosystem:
  • Open banking APIs (PSD2, UK OBIE, Nordigen, etc.).
  • Payment gateways like Stripe, Rapyd, Checkout, SWIFT providers.
  • Crypto exchanges.
  • Other third-party APIs for partner services (BNPL, insurance, investments).

The integration layer is typically built using message queues, REST/gRPC, or pub/sub architectures.

Compliance & Reporting

This module ensures ongoing alignment with regulatory requirements — a must-have for any fintech product operating in a licensed or regulated environment. It typically includes:
  • Sanctions and PEP list screening (e.g. World-Check, ComplyAdvantage).
  • AML triggers and suspicious transaction reports (SARs, STRs).
  • Mandatory reporting — both internal and for regulators.
  • Operation logging — audit trails, GDPR logs, action histories.

In some cases, this block is implemented as a separate service or handed off to a specialized RegTech platform.

Back Office & Admin Panel

This is the operational interface used by internal teams to manage and support the system. Common capabilities include:
  • Manual review and verification.
  • Limit management, role configuration, exception handling.
  • Transaction inspection, moderator comments.
  • Event logs and manual status overrides.

A well-built back office is more than just a dashboard — it’s a fully functional internal tool with role-based access, meta-permissions, and full auditability.

As a fintech product scales — with more users, more jurisdictions, and more complex workflows — the architecture behind it must stay solid. The better it's designed from day one, the easier it is to evolve without losing control.
Example of how a fintech application works

Launching a Fintech Product

Starting a fintech company comes with a much higher barrier to entry than most digital ventures. It’s not enough to design a clean UX — you’ll need to build robust infrastructure, pass verification procedures, integrate with payment gateways, negotiate with regulators, and stay compliant from day one.

Let’s break down the key aspects of launching a fintech banking product — and what it takes to go live successfully.

Choosing the Right Niche

The fintech market is saturated, and launching “just another wallet” isn’t a great strategy. A better approach is to identify underserved niches with specific user pain points that existing products fail to address.

Examples of niche fintech products:
  • Micro-B2B tools for freelancers — invoicing, basic accounting, simple financial dashboards.
  • Fintech at the intersection of SaaS and e-commerce — payment rails, embedded finance modules, B2B payments from within CRM, API-first platforms for launching custom fintech flows inside third-party interfaces.
  • Automated personal finance tools — no-touch spending control, AI-based budgeting assistants, automated tax reporting.
  • Fintech for the creator economy — financial tools for streamers and content creators, instant payouts, income splitting for teams.
The idea: pick a focused use case, solve a clear problem. Your target users might be small business owners or solo entrepreneurs who don’t want complexity — they want a clean, usable interface that gets the job done.

Choosing a Launch Region

Launching a global fintech product out of the gate is close to impossible. Your starting jurisdiction will shape everything: licensing costs, launch timelines, compliance requirements, and how far you can scale before hitting regulatory walls.

Here’s a snapshot of jurisdictions that are either startup-friendly — or known for specific challenges.
Europe:
  • Lithuania
    One of the EU’s top fintech hubs post-Brexit. Quick licensing for EMI and PI entities. Timeline: 6–12 months. Regulator: Bank of Lithuania.
  • Estonia
    Simple business registration and crypto/payment licensing. Popular for e-Residency founders. Timeline: 6–9 months.Regulator: EFSA.
  • Poland
    Relatively fintech-friendly; offers a “small payment institution” registration path. Timeline: from 6 months.Regulator: KNF.
  • UK
    Independent post-Brexit. Regulatory process is stricter, but the FCA sandbox is one of the best globally. Timeline: 9–18 months. Regulator: FCA.
Asia:
  • Singapore
    Progressive fintech environment with clear licensing, consumer protection, and an excellent sandbox program. Timeline: 9–12 months. Regulator: MAS.
  • Hong Kong
    Strong in payment and investment fintech; good startup support via the HKMA Innovation Hub. Timeline: ~12 months. Regulator: HKMA.
North America:
  • USA
    Extremely complex: state-level MSB licenses + federal requirements. Many startups go through a partner bank.
  • Canada
    Softer than the US; national MSB registry and supportive fintech programs. Sandbox available.
If you want a faster, lower-cost launch — look at Lithuania or Estonia. For APAC scale, Singapore is your best bet.

What Is a Regulatory Sandbox?

A regulatory sandbox lets fintech startups test their product in a controlled environment — often without a full license, but under regulator supervision.

Top global sandboxes:
  • UK (FCA Sandbox) — One of the first and most influential.
  • Lithuania (Bank of Lithuania Sandbox) — Fast-track setup with advisory support.
  • Singapore (MAS Sandbox Express) — Focused on APAC fintech pilots.
  • Canada (Securities Sandbox) — Open to innovative finance projects.
  • Australia (ASIC Innovation Hub) — Tailored for early-stage startups.

How to get in:
  • Submit an application with your product description and business plan.
  • Show the innovation behind your solution and its benefit to the market.
  • Demonstrate your approach to risk and compliance.
  • Provide reports and operate your MVP within sandbox limits.

Application review typically takes 1–3 months. Participation doesn’t exempt you from baseline compliance — KYC/AML rules still apply.

Finding the Right Partners

A successful fintech launch often hinges on choosing the right partners — not just for functionality, but for compliance, reliability, and time-to-market.

Core partnerships to consider:
  • Payment gateways (e.g. Checkout, Stripe, Adyen) — payment processing, card issuing/acquiring.
  • BaaS platforms (e.g. Solarisbank, Mambu) — banking infrastructure delivered via API.
  • Custodian banks / sponsor banks — required for holding client funds (especially in the US and EU).
  • KYC/AML providers (e.g. Sumsub, Onfido, ComplyAdvantage) — fast user verification and risk checks.
When evaluating partners, factor in:
  • Licensing jurisdiction.
  • SLA for technical support.
  • Data transfer policies and compliance agreements.

Speed, Margins & Risk: The Startup Triangle

Launching a fintech product is always a trade-off between speed, profitability, and risk. Improving one dimension often increases pressure on the other two. That’s why your priorities must be clear from the start.

Most fintech products monetize through one or more of the following:
  • Transaction fees — a fixed amount or percentage per operation (common in wallets and payment apps).
  • Subscription or account fees — recurring payments for access, premium features, or B2B API usage.
  • Interest on client funds — via partner bank deposits or sweep models.
  • Interchange — revenue from acquiring commissions on card transactions (typical for card-focused products).
  • Partnered services — insurance, investments, BNPL, offered via API or embedded modules.
You’ll need to define your business model early — it impacts architecture, licensing, and even UX.

Fintech carries substantial technical, legal, and operational risk. Here are some of the most common pitfalls:
  • Frozen funds
    Client money can be blocked due to AML violations, sanction lists (e.g. OFAC), or partner bank concerns. Unblocking may take weeks — or be impossible.
  • Chargebacks and fraud
    High chargeback rates can lead to account suspension or punitive fees from your payment provider.
  • License violations
    Even minor non-compliance can result in license revocation or heavy fines.
  • Architectural bugs
    A single mistake in the core ledger can cause incorrect balance updates or failed settlements — critical in financial products.
Avoid rushing. Even with a strong team and reliable partners, launching a compliant, production-ready fintech product takes 6–12 months — minimum.
Want to Launch in 3 Months? It’s possible — but it comes at a cost:
  • You’ll likely need to go through a white-label partner.
  • You’ll carry high dependency risk if the partner fails.
  • Your transaction costs will be higher and margins lower.

If you’re building for scale, prepare for long integration cycles, careful regulator dialogue, and upfront licensing costs. Cutting corners early often leads to bigger problems later.
fintech projects

What an MVP Needs in Fintech

In a typical startup, an MVP is a quick way to test features. In fintech, it's something entirely different. An MVP here is a fully functional financial service, built to meet regulatory, technical, and operational standards from day one.

Here’s what a fintech MVP actually requires:
  • KYC and basic AML support
    You can’t move a cent without identity verification. KYC involves checking passports, personal data, and addresses — typically via an integrated provider like Onfido. Basic AML means screening against sanctions lists and monitoring for suspicious activity. At minimum, this includes automated onboarding checks and triggers for unusual behavior.
  • Real transaction handling (not just mocks)
    Your MVP should process actual operations — at least: create virtual accounts for users, emulate internal transfers, Integrate with at least one external gateway (a payment provider or bank). Even if your MVP runs on "virtual money," the system must enforce real validation logic — limits, fees, compliance checks, and data consistency.
  • Fault-tolerant architecture
    You can either build a lightweight core yourself (e.g. PostgreSQL + event sourcing) or use a BaaS platform that offers out-of-the-box infrastructure via API. Popular providers: Solarisbank (Germany), Mambu (EU/global), Modulr (UK). Using BaaS is faster and easier, but it comes with trade-offs: provider lock-in, limited flexibility, and higher per-transaction costs.
  • Basic reporting and logging
    Your MVP needs internal logs and reporting capabilities: Transaction and account activity, KYC history and verification changes, Manual audit exports (even if it's just CSVs for now).
Many successful fintech startups didn’t start with custom infrastructure. They built on top of a partner’s systems:
  • Wise used partner banks for cross-border payments early on
  • Revolut operated under a licensed partner in its first years
  • Many startups begin with BaaS for 12–24 months — then move to custom-built cores once they scale
In fintech, even your MVP is a financial institution — even if it runs through third-party platforms. “Fake” launches and nice-looking landing pages won’t cut it.

Case Studies

Let’s look at a few real-world fintech launches — both the ones that took off, and those that struggled.
Successful Launches:
  • Chime (USA)
    Launched as a mobile banking app without a banking license, using The Bancorp Bank as a partner. Focused on smooth UX, no-fee accounts, and early direct deposits. Growth was driven by Reddit, TikTok, and referral programs, not traditional advertising.
  • Wise (formerly TransferWise)
    Started without their own license, using banking partners in the UK and EU. Initially focused on a narrow use case — cheap cross-border transfers — before expanding into a broader financial ecosystem.
  • Brex (USA)
    Corporate cards for startups. Launched via Emigrant Bank and focused on fast onboarding and automated spend management. The product solved a very specific pain point for VC-backed companies.
  • Raisin (Germany)
    Built a platform for investing in deposit products across European banks. Operated under open banking and partner agreements before obtaining their own license.
Failures & Difficulties:
  • Simple (USA)
    One of the earliest US neobanks, built on The Bancorp Bank’s infrastructure. Despite a great-looking app, the team struggled with operational overhead and compliance processes. After being acquired by BBVA, the project failed to reach sustainable unit economics and was shut down in 2021.
  • Neat (Hong Kong)
    Focused on SMEs in Asia. Scaled quickly but failed to meet updated AML regulations in 2020. Eventually acquired and shut down as an independent brand.
  • Xinja (Australia)
    Received a full banking license in 2019 but burned through cash within a year without achieving a viable business model. Returned its license and shut down in 2020.
  • Wirecard (Germany)
    Once a fintech giant — collapsed after revelations of massive accounting fraud. While not an MVP-scale failure, it serves as a cautionary tale: even well-funded fintechs can collapse without strong internal controls and compliance.
Launching a fintech product takes more than great UI or rapid prototyping. It requires system-level thinking: architecture, partnerships, compliance, and risk management all need to be in sync. Success isn’t about launching fast — it’s about balancing tech, economics, and regulation from day one.
fintech startups
A few examples of successful fintech startups

Technologies in Fintech

Fintech isn’t just a new way to deliver financial services — it’s a fundamentally different operating model. The technologies behind fintech products determine not only how they function, but also what they enable: speed, scale, modularity, and innovation all start at the technical level.

Let’s break down the core technologies that power modern fintech systems.

API-First Approach

The API-first model means services are designed from the ground up to be accessible via APIs — not only for clients, but also for partners and internal teams.

Where it's used:
  • Payment processing and money transfers (e.g. Stripe, Adyen).
  • Identity verification integrations (e.g. Sumsub, Onfido).
  • Risk scoring, antifraud systems, and real-time decision engines.
  • Open Banking connectivity (access to bank data with user consent).

Key considerations when designing APIs in fintech:
  • Strong security protocols: OAuth 2.0, mTLS, encrypted payloads.
  • Strict versioning and backward compatibility.
  • Full request logging for audit trails and compliance.
API-first development accelerates product evolution and enables fintech platforms to scale and adapt quickly — without constant architectural overhauls.

Microservices Architecture

Microservices are one of the most foundational technologies in fintech. Instead of building a monolithic system, teams create independent service modules, each with a single responsibility — such as payments, KYC, or analytics.

Why it works so well for fintech:
  • Reliability
    If one service fails, the rest keep running. Crucial when downtime equals lost revenue.
  • Flexibility
    New features can be added or updated without refactoring the entire system.
  • Scalability
    Traffic spikes? Scale only the modules that need it — e.g. the transaction engine.
  • Security
    Access can be isolated at the service level, reducing attack surface and internal risks.
Typical implementation patterns:
  • Docker + Kubernetes for container orchestration.
  • Inter-service communication via gRPC, Apache Kafka, REST, or GraphQL, depending on latency and reliability needs.
  • Support systems: service discovery, circuit breakers, centralized logging and tracing (via tools like ELK, Prometheus, or Jaeger).
  • Tech stack per team or module may vary — as long as there’s consistency at the API and logging level.
The microservices approach is especially valuable in fintech, where products must remain secure and stable under heavy transaction loads, changing compliance rules, and fast-moving feature demands.

Cloud-Native Infrastructure

In fintech, cloud adoption isn’t just about “moving to the cloud” — it’s about designing systems natively for the cloud environment. A cloud-native approach enables scalability, resilience, faster deployment, and more agile feature delivery.

Why cloud-native matters in fintech:
  • Speed
    Products can be launched in days without heavy infrastructure investments.
  • Scalability
    Cloud services scale automatically with traffic and transaction load.
  • Reliability
    Top cloud providers offer SLAs up to 99.999%, which is critical for real-time systems.
  • Compliance
    Major providers are certified for standards like PCI DSS, SOC 2, ISO 27001 — simplifying audits.
Important caveats:
  • Public cloud isn’t always an option — some regulators require data residency.
  • Teams need cloud security expertise: IAM, VPC, Secrets Management, Zero Trust models.
  • Vendor lock-in is a risk — dependency on a single cloud provider can hinder flexibility and long-term scaling.
Where cloud-native is used in fintech:
  • MVP launches without upfront infrastructure costs
  • Auto-scaling during load spikes (e.g. Black Friday, crypto surges).
  • Secure storage and backups of sensitive data.
  • Real-time analytics, fraud detection, and transaction monitoring.

Key cloud-native technologies for fintech:
  • Providers: AWS, Google Cloud, Azure — with fintech-grade compliance support.
  • Architecture: serverless (AWS Lambda, Cloud Functions), managed Kubernetes, cloud-native DWH (Snowflake, BigQuery).
  • Security: private cloud setups, encrypted storage, geo-fencing for jurisdiction-specific data handling.
Cloud-native infrastructure allows fintech products to launch faster, cheaper, and more securely — as long as architecture accounts for fault tolerance, compliance, and regulatory constraints from the start.

Data Infrastructure

Data is one of the most valuable assets in fintech. From credit scoring and fraud detection to analytics and personalized UX — data powers every layer of the stack.

Core components of fintech data pipelines:
  • Data ingestion: Kafka, Apache Pulsar, AWS Kinesis — for real-time event collection.
  • ETL/ELT: Apache Airflow, dbt, Talend — for data transformation.
  • Warehousing: Snowflake, BigQuery, Redshift, ClickHouse — high-performance, scalable storage.
  • Stream processing: Apache Flink, Spark Streaming — for real-time analytics and fraud response.
  • BI & visualization: Metabase, Looker, Superset, Tableau — for reporting and dashboards.
Critical data requirements in fintech:
  • Real-time responsiveness
    Scoring, limits, and alerts must trigger with minimal delay.
  • Data quality
    Inaccurate or missing data can lead to financial errors, compliance violations, or system failures.
  • Flexible storage models
    Hybrid architectures with data lakes + warehouses enable both agility and structure.
  • Data lineage & audit
    Regulators require full traceability and proof of data integrity.
Additional focus areas:
  • Data governance — role-based access, metadata management, and cataloging.
  • Advanced logging — especially for financial transactions and user actions.
  • Retention policies — strict control over data location, deletion, and duration (GDPR, DPA, local FinReg rules).
In fintech, well-architected data infrastructure isn’t just about analytics — it’s about reliability, compliance, and financial risk control. A single failure in data can cost millions, which is why every pipeline, warehouse, and monitoring system must be built with resilience in mind.

Machine Learning

Machine learning in fintech isn’t about hype — it’s a production-grade tool used to automate high-stakes decisions. From credit scoring to fraud detection, ML drives core logic in modern financial platforms.

Where ML is used in fintech:
  • Credit scoring — loans, credit lines, and card limits.
  • Fraud detection — flagging suspicious activity, bots, and behavioral anomalies.
  • Predictive analytics — churn forecasting, default risk, CLTV.
  • Decision automation — chatbots, event-based triggers.
  • Personalization — tailored product recommendations, pricing, and segmentation.
What makes ML in fintech different:
  • Explainability matters — especially for compliance in scoring and forecasting (XAI is often required)
  • Clean data is a must — poor data = poor models, with financial consequences.
  • Models evolve — they must be retrained as user behavior, regulations, and risk profiles change.
  • Real-time inference — fraud checks and dynamic scoring require low-latency predictions.
Tech stack:
  • Models
    CatBoost, LightGBM, XGBoost for speed and accuracy; neural networks for complex patterns (e.g. voice/face ID).
  • Infra
    MLflow, SageMaker, Vertex AI, Kubeflow — for training, versioning, and deployment.
  • Integration
    Via APIs, stream pipelines (e.g. Kafka + Flink), or direct injection into scoring engines.
In fintech, ML isn’t a side project — it’s critical infrastructure. Precision, security, explainability, and auditability are just as important as accuracy.

Security & Encryption

In fintech, security isn’t just a module — it’s a cross-cutting architectural layer. Handling money and personal data leaves no room for error: a single vulnerability can mean financial losses or reputational damage.

Where security applies:
  • Data transmission and storage (documents, tokens, credentials).
  • Authentication and session control.
  • Transaction logging and event auditing.
  • API integrations with payment systems and partners.

Core technologies & best practices:
  • Encryption: TLS 1.3, AES-256, asymmetric crypto (RSA, ECC); mandatory encryption at rest and in transit.
  • Tokenization & HSMs — especially for card processing (PCI DSS compliance).
  • mTLS and OAuth 2.0 — for secure API integrations.
  • RBAC / ABAC — fine-grained access control, with least privilege by default.
  • Zero Trust — all access must be explicitly verified, no implicit trust between services.
Security-specific fintech requirements:
  • Strict logging, user action history, and authentication records — for audits.
  • Internal and external security reviews, including pen tests and bug bounty programs.
  • Built-in 2FA, biometric auth, SMS/push-based confirmation.
  • Real-time fraud detection and automated response systems.
In fintech, strong security is a prerequisite — not just for users, but also for partners, banks, and regulators.

Biometrics & Identity Verification

Accurate, fast, and secure identity verification is essential in fintech — not just for compliance, but for trust and user experience. That's why biometric and document-based systems are now standard in most fintech flows.

Common use cases:
  • User onboarding (KYC checks).
  • Account access and transaction approval.
  • Detecting multi-account abuse, bots, and fraud.
  • Remote account opening and business verification.

Tools and technologies:
  • Document verification: OCR + ML to process IDs, utility bills, bank statements.
  • Biometrics: facial, fingerprint, iris, and voice recognition — as primary or secondary factors.
  • Liveness detection: to prevent spoofing, deepfakes, and replay attacks.
  • Video verification: live or recorded calls with an agent — required in some jurisdictions.
  • Behavioral biometrics: keystroke dynamics, cursor movement, typing speed — adds passive antifraud layer.
Popular providers:
  • Sumsub, Onfido, Veriff, IDnow, iDenfy — full-stack KYC/AML platforms with biometric and video support.
Key challenges in fintech:
  • Accuracy and compliance (KYC/AML, GDPR, eIDAS, etc.).
  • Balancing security and UX — friction can hurt conversion, but weak flows increase risk.
  • Fallback mechanisms — there must be alternatives when biometrics fail.
Identity verification isn’t just a KYC checkbox — it’s the gateway to the product. Done right, it improves trust, security, and conversion. Done poorly, it blocks growth.
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AI in Fintech

AI in fintech isn’t about “smart chatbots” — it’s about automating decisions, scaling expertise, and increasing accuracy in areas that once relied on manual effort. Now artificial intelligence goes far beyond traditional ML models and becomes a core layer in both strategy and product development.

Where and how AI is used in fintech:
  • Credit scoring & underwriting — adaptive models using dozens of features, including non-traditional signals like in-app behavior.
  • Fraud detection — advanced AI systems can uncover complex and evolving fraud patterns that rule-based engines miss.
  • Personal financial assistants — voice/text interfaces powered by LLMs (e.g. ChatGPT, Claude) help users manage budgets, analyze spending, and choose financial products.
  • Automated document verification — OCR + computer vision + ML for faster, more accurate handling of IDs, bank statements, receipts.
  • Transaction analysis & categorization — identifying spending patterns, recurring subscriptions, and cost-saving suggestions.
  • Legal & compliance analysis — NLP-based tools extract risks and validate regulatory alignment in contracts and policy docs.
AI vs. ML in fintech:
  • ML is a subset — primarily used for predictions, scoring, and classification.
  • AI is broader — includes NLP, computer vision, generative models, and reasoning.
  • ML is often embedded in pipelines; AI powers more holistic systems — from LLM-based assistants to cognitive analytics engines.
What’s under the hood:
  • NLP: BERT, GPT, Claude — for text parsing, intent detection, category tagging, ticket routing.
  • CV: YOLO, Detectron, custom models — for document analysis, ID photos, and selfie validation.
  • Recommendation engines: ranking algorithms, reinforcement learning.
  • LLMs + retrieval: AI that can not only answer questions but search and interpret regulatory frameworks, contract clauses, or jurisdiction-specific policies.
Risks & limitations of AI in fintech:
  • Explainability
    Regulators require transparent reasoning, especially in lending decisions and rejections.
  • Bias & discrimination
    Flawed data = unfair outcomes = potential legal exposure.
  • Compliance & auditability
    AI use must include version control, logging, and reporting for regulatory review.
  • Ethics
    You can’t delegate sensitive decisions to a black box — especially in areas like lending, insurance, or fraud.
AI is a powerful enabler — but in fintech, it must be implemented with care. The winners aren’t just the ones who adopt LLMs or neural nets. The winners are those who turn them into auditable, explainable, and compliant business engines.

AI Use Cases in Fintech

AI in fintech isn’t a concept — it’s already in production across major platforms. Industry leaders are actively integrating artificial intelligence into both products and operations to improve speed, scale, and decision-making.

Here are a few real-world examples:
  • Revolut — AI-driven fraud detection & spending insights
    Uses ML and behavioral biometrics to detect subtle anomalies in user activity — catching fraud that simple rule engines miss. Also leverages AI to automatically categorize spending, predict financial behavior, and offer personalized suggestions.
  • Klarna — AI in customer service & debt management
    Handles over 2 million support requests via its in-house LLM-powered assistant — no human agent involved. AI also tailors debt collection strategies, adjusting tone and timing of reminders based on user behavior.
  • Brex — Automated finance workflows
    Applies NLP models to extract data from receipts, invoices, and contracts. AI helps flag risky transactions and screen business partners for compliance and corruption risks.
  • Upstart — AI-powered credit decisions
    Lending decisions are made using models that factor in non-traditional signals — like education, professional background, and onboarding behavior. Upstart claims improved loan approval rates without increasing default risk.
  • Cleo & Plum — LLM-based financial assistants
    These chatbots come with a distinct personality and help users plan budgets, track expenses, and identify suspicious subscriptions. Built on top of banking data, they improve over time by “learning” the user’s financial habits.
AI is no longer optional in fintech — it’s becoming the new standard for companies that want to scale fast and make smarter, more automated decisions.

Kirill Gurbanov, our expert, talks about the growing use of GenAI in fintech:
  • Kirill Gurbanov
    CEO, Founder, Seasoned Executive in FinTech & Banking, PropTech
    The key difference between GenAI and traditional AI/ML systems lies in their core function. Traditional AI is focused on analyzing existing data to classify, predict, or automate tasks based on patterns and predefined rules.

    GenAI, by contrast, specializes in generating new, original content — text, code, images, synthetic data, scenarios — by learning deep patterns from large and often unstructured datasets. This gives GenAI greater flexibility and adaptability, but also introduces issues with transparency (the ‘black box’ effect) and result consistency.
  • Kirill Gurbanov
    While chatbots are the most visible example, the potential of GenAI in fintech goes far beyond that. There are several promising application areas:

    1. Intelligent document processing and standardization.
    GenAI can automate extraction, interpretation, and normalization of data from a variety of financial documents — invoices, statements, ESG reports, regulatory texts. This significantly improves back-office efficiency, reduces errors, and ensures data consistency for analytics and compliance. One example is a major corporate bank in Asia that used GenAI to cut ESG reporting preparation time by 90%.

    2. Hyper-personalization at scale.
    By analyzing large volumes of customer and market data, GenAI can generate deeply personalized financial advice, product recommendations, investment strategies, and even marketing communications. Examples include AI assistants like Acorns, personalized investment tools like JPMorgan’s IndexGPT, and dynamic portfolio adjustment based on client goals and market signals.

    3. Synthetic data generation and risk modeling.
    GenAI can create realistic but artificial datasets that mimic financial behavior or transaction patterns. These synthetic sets are extremely valuable for training fraud detection and risk models — especially in cases of rare events or emerging threat types where real data is limited. Platforms like Feedzai are already using this approach to train systems on synthetic fraud scenarios. GenAI is also used for complex scenario modeling and stress testing.
  • Kirill Gurbanov
    It’s important to note that many of these use cases are designed to support human experts or enhance existing systems, rather than replace them entirely. GenAI acts as a productivity tool for analysts, a co-pilot for financial advisors, or a way to improve data quality for traditional ML models — reflecting a pragmatic approach to adopting this technology in the industry.

Fintech & Blockchain

Fintech and blockchain are deeply interconnected and continue to influence each other’s evolution. Blockchain is one of the foundational technologies that shaped fintech in the 2010s — and still plays a major role today. In the fintech context, blockchain goes far beyond cryptocurrencies: it enables transparency, verifiability, and the removal of intermediaries.

Where blockchain is used in fintech:
  • Payments — fast, low-cost domestic and cross-border transfers without banks or payment gateways.
  • Digital wallets and custody services — storing crypto assets, tokens, NFTs, and other digital holdings.
  • DeFi — decentralized lending, swaps, and yield generation without traditional financial intermediaries.
  • Stablecoins — crypto assets pegged to fiat currencies (usually USD), used for payments, hedging, and internal accounting.
  • Asset tokenization — converting ownership rights (e.g., for stocks, real estate, commodities) into blockchain tokens, enabling fractional ownership and automated transfers.
Benefits of blockchain in fintech:
  • Transparency — transactions are recorded in tamper-proof public ledgers.
  • 24/7 access — no banking hours or cut-off times.
  • Lower costs — fewer intermediaries such as acquirers or clearing houses.
  • Automation — smart contracts can execute business logic with no manual steps.
Technology stack:
  • Blockchains: Ethereum, Polygon, Solana, Avalanche — for DeFi and tokenized products.
  • Smart contracts: Solidity, Vyper — used to manage asset flows, KYC logic, and profit-sharing.
  • Layer 2 solutions: Arbitrum, Optimism — help scale transactions while reducing fees.
  • Private blockchains: Hyperledger, Quorum — typically used in enterprise-grade B2B solutions requiring permissioned access and compliance.
Key challenges:
  • Regulation
    Legal treatment of crypto assets remains ambiguous in many countries. Products can be blocked or restricted based on local law.
  • Scalability
    Public blockchains often struggle with speed and cost, especially during high-volume periods.
  • User experience
    Wallets, seed phrases, and network settings remain complex for non-technical users.
  • Fiat integration
    Bridging to traditional finance requires licenses, regulatory compliance, and banking partners.
Blockchain in fintech is not a direct replacement for traditional systems — it’s an entirely different architecture with unique strengths and constraints. When used appropriately, it opens new possibilities — but requires careful legal and technical planning.

Real-World Use Cases

Blockchain has moved far beyond crypto exchanges and is now embedded in real, production-grade fintech products — from remittances to loyalty programs. Here are a few examples:
  • Ripple — Cross-border payments without SWIFT
    RippleNet provides infrastructure for international transfers using distributed ledger tech. Partners include Santander, PNC, SBI Holdings, and Tranglo.
  • Circle — USDC for B2B and B2C payments
    The stablecoin USDC is used for fast payments, Web3 commerce, and internal settlements between counterparties. It's integrated with Stripe, Robinhood, Checkout.com, and others.
  • JP Morgan Onyx — Enterprise blockchain for interbank settlements
    The Onyx platform enables digital settlement between corporate clients using JPM Coin — a tokenized USD used inside JP Morgan’s internal infrastructure.
Today, blockchain is used where it makes technical and economic sense — and that’s exactly where it earns its place in fintech.

Top 8 Fintech Roles

Thanks to the development of new technologies, companies require various fintech specialists, from software developers to ML engineers. These professionals play a crucial role in creating new products and services, enhancing the efficiency of financial operations, and protecting clients from fraud.

A strong fintech team is always a mix of technical, product, and regulatory expertise. Below are the key roles that power every digital bank, payment platform, or embedded finance service — the people behind the code, compliance, and customer experience.
  • Backend Developer
    Responsible for the core logic of the fintech product — from transaction processing and API integrations to security and system scalability.

    Key responsibilities:
    • Building APIs and business logic (payments, scoring, KYC, reporting).
    • Integrating with third-party providers (banks, RegTech, payment gateways).
    • Ensuring secure storage, logging, and data protection.

    What they work with:
    • Languages: Go, Java, Kotlin, Python (sometimes Node.js).
    • Frameworks: Spring, Django, FastAPI, Fiber.
    • Databases: PostgreSQL, Redis, ClickHouse.
    • Messaging: Kafka, RabbitMQ, gRPC, REST.
    • Security & compliance: TLS, OAuth2, tokenization, PCI DSS, KYC.
Lucky Hunter Case

A major FinTech company approached us to find a blockchain developer willing to relocate to Abu Dhabi. The perfect candidate had to have experience in Ethereum and Solidity, web3.js, and truffle stack. Despite challenges such as a demanding test assignment and a slightly below-market salary, we successfully found a blockchain developer who accepted the offer and relocated to Abu Dhabi.

Read more in the case description
  • Data Engineer
    Builds and maintains data pipelines to collect, process, and store information.

    Key responsibilities:
    • Implementing ETL/ELT pipelines.
    • Supporting real-time processing (e.g., for antifraud or scoring).
    • Ensuring data quality and availability for analysts and ML.

    Tech stack:
    • Tools: Airflow, dbt, Spark, Flink.
    • Databases: BigQuery, Snowflake, ClickHouse, Postgres.
    • Messaging/storage: Kafka, S3, Parquet/Avro.
    • Advanced SQL and Python for pipeline development.
  • ML Engineer / Data Scientist
    Develops models that automate core processes — from risk scoring to fraud detection.

    Key responsibilities:
    • Building models for risk scoring, segmentation, and behavioral predictions.
    • Deploying models to production: inference, A/B testing, monitoring.
    • Ensuring model explainability (XAI) for regulatory compliance.

    Tech stack:
    • Python + scikit-learn, XGBoost, LightGBM, CatBoost.
    • ML tools: MLflow, Jupyter, Docker.
    • SQL, experience with DWH.
    • Strong understanding of fintech logic and explainability requirements.
  • DevOps / SRE
    Ensures system stability, scalability, and secure infrastructure.

    Key responsibilities:
    • CI/CD pipelines, monitoring, alerting.
    • Container orchestration and infrastructure-as-code.
    • Security controls and meeting SLAs.

    Tech stack:
    • Docker, Kubernetes, Terraform.
    • CI/CD: GitLab, Jenkins, ArgoCD.
    • Monitoring: Prometheus, Grafana, ELK.
    • Cloud: AWS, GCP, Azure.
    • Secrets management, network security, RBAC.
  • Compliance / RegTech Specialist
    Ensures the product meets all regulatory requirements (KYC/AML, licensing, data protection).

    Key responsibilities:
    • Managing customer verification and monitoring processes.
    • Integrating RegTech platforms (Sumsub, Onfido, ComplyAdvantage).
    • Supporting audits and maintaining compliance documentation.

    Skills required:
    • Knowledge of GDPR, AML, KYC, PCI DSS, local financial regulations.
    • Hands-on experience with RegTech tools.
    • Risk assessment, legal process documentation.
    • Collaboration with banks and auditors.
  • Product Analyst
    The most universal analytics role — essential for any fintech product, from neobanks to crypto exchanges.

    Key responsibilities:
    • Analyzing funnels, user behavior, unit economics.
    • Identifying growth points, A/B testing.
    • Preparing dashboards and reports for product teams and investors.

    Tech stack:
    • SQL, Python (pandas, matplotlib, seaborn).
    • BI tools: Tableau, Power BI, Metabase.
    • Product analytics: Amplitude, Mixpanel, GA.
    • Fintech metrics: CAC, LTV, ARPU, churn, risk-adjusted return.
  • Financial Analyst
    Essential for fintechs in B2B lending, investment, and payment verticals.

    Key responsibilities:
    • Financial modeling and performance analysis.
    • Revenue, cash flow, and risk tracking.
    • Supporting product and strategic decisions.

    Skills required:
    • Excel / Google Sheets (advanced modeling).
    • SQL, Power BI or Looker.
    • Strong grasp of finance: P&L, NPV, margin, default rate.
    • Understanding fintech specifics: MDR, cost of funds, fee structures.
  • Fraud Analyst
    Detects and prevents fraud across financial operations. Works at the intersection of data, security, and compliance.

    Key responsibilities:
    • Analyzing user behavior, transactions, system events.
    • Tuning fraud rules, identifying suspicious patterns.
    • Investigating incidents and collaborating with support and compliance.
    • Preparing reports for audits and regulators.

    Skills required:
    • SQL, often Python
    • Tools: Feedzai, Actimize, in-house rule engines, BI platforms.
    • Fraud knowledge: multi-accounting, card fraud, social engineering, abuse.
    • Metrics tuning: false positives, precision/recall.
    • Bonus: experience with real-time streaming and behavioral analysis.

Global Fintech Market

The fintech industry is one of the fastest-growing sectors worldwide. Products at the intersection of finance and technology are rapidly expanding into new verticals — from lending and payments to insurance, compliance, and investments. Thousands of startups are emerging, tech giants are entering the space, and traditional banks are redefining their roles.

Key figures:
  • According to Fortune Business Insights, the global fintech market is valued at $340.1 billion in 2024, with projections reaching $1.13 trillion by 2032 (CAGR of 16.2%).
  • North America remains the largest regional market, generating $112.91 billion in revenue.
  • It also leads in number of companies — over 12,000 fintech firms as of 2024.
Regional leaders in fintech adoption:
  • United States — the investment hub and home to major players like Stripe, Plaid, Robinhood, Chime, and SoFi.
  • Europe — strong in Open Banking, RegTech, and crypto infrastructure. Key hubs include London, Berlin, Amsterdam, and Vilnius.
  • India & Southeast Asia — rapid scale driven by mobile-first solutions, digital wallets, and P2P platforms.
  • Latin America — booming neobank and microfinance market, led by Nubank, Ualá, and Mercado Pago.
  • Middle East & North Africa (MENA) — growing interest in Islamic fintech, BNPL, and API-first platforms.
  • China — a powerful but closed ecosystem with domestic giants like Alipay, WeChat Pay, and Ant Group.
The global fintech landscape is moving beyond experimentation toward mature business models, with a stronger focus on regulation, interoperability, and real user value.
fintech market
Based on data from Fortune Business Insights

Fintech Investment Trends

Fintech remains one of the top sectors for venture and corporate funding. While the market cooled off in 2022–2023 after a pandemic-era surge, investor interest hasn’t disappeared — it has simply shifted. Today, the focus is on resilient B2B models, infrastructure, and compliance technologies.

Key trends:
  • Fewer deals overall, but growing interest in late-stage rounds (Series C and beyond): investors are betting on survival and scale.
  • Shift from B2C to B2B: fewer neobanks and consumer-facing apps, more payment infrastructure, RegTech, and embedded finance.
  • More strategic capital from banks, payment networks, and tech providers — Visa and Mastercard, for example, continue to acquire fintech stakes globally.
  • Geographic expansion: increased deal volume in Latin America, Southeast Asia, and MENA regions.
Key figures:
  • In 2021, global fintech investment hit a record $210 billion, according to KPMG.
  • In 2023, total investment nearly halved — but with higher allocation to infrastructure, security, compliance, and B2B fintech.
  • According to CB Insights, the top fundraising countries remain the US, UK, India, and Singapore.
What attracts investors:
  • Scalability and network effects, especially in payments and API infrastructure.
  • Embedded value — solutions tied to essential workflows like transactions, ID verification, and fund custody.
  • Cross-market potential — the ability to expand into e-commerce, HRTech, insurance, or B2B SaaS.
  • Regulatory maturity — licensed operations, clean ownership structure, and strong compliance practices.
Investor concerns:
  • Regulatory complexity and high compliance risk.
  • Tough integrations with banks and fiat infrastructure.
  • B2C churn and competition — user acquisition is expensive, loyalty is fragile.
  • Slower path to profitability, especially for consumer-oriented models.
Fintech is no longer seen as a hype-driven gold rush — it’s a mature, highly competitive industry. Successful companies combine technical strength with legal robustness, earning investor trust through both innovation and operational discipline.

The Future of Fintech: Key Trends

Fintech continues to evolve at the intersection of technology, regulation, and user expectations. Let’s look at the most important trends shaping the industry in the next 3–5 years.

Banking-as-a-Service (BaaS) on the rise

Fintech infrastructure is increasingly available “out of the box.” Instead of building core banking features from scratch, companies plug into BaaS platforms to launch financial products — no license or internal backend required.

Through API integrations, businesses can offer card issuing, account management, transactions, KYC/AML, tax calculations, and more.
Examples: Unit, Solaris, Marqeta, Synapse, Rapyd.
Fintech expert Kirill Gurbanov comments:
  • Kirill Gurbanov
    CEO, Founder, Seasoned Executive in FinTech & Banking, PropTech
    Just as AWS transformed software development by offering infrastructure as a service, a similar shift is happening in finance.

    With BaaS platforms and specialized APIs, companies across industries can embed payments, lending, and insurance directly into their user journeys. Finance becomes a function, not a destination — and trust shifts from banks to brands that already own the customer relationship.

Expansion of embedded finance

One of fintech’s defining trends, embedded finance brings financial services into non-financial platforms — marketplaces, SaaS, logistics, and retail.

Users can access credit, payments, or insurance directly within the interface they already trust — no redirects, no bank apps.
Examples: Shopify Capital, Uber Wallet, Stripe Treasury.
Our expert Kirill Gurbanov continues:
  • Kirill Gurbanov
    CEO, Founder, Seasoned Executive in FinTech & Banking, PropTech
    Forecasts for embedded finance vary in numbers but agree on the trajectory: fast growth with 20–30%+ CAGR.

    Main drivers include digital transformation, demand for frictionless UX, financial inclusion, and API/BaaS maturity. Payments dominate today, but embedded lending (especially BNPL) and insurance show the most growth potential.

    Shopify not only handles payments but also offers sellers banking products like Shopify Balance and working capital. Apple partnered with Goldman Sachs to launch Apple Card, deeply integrated into its ecosystem.

    Uber collaborates with banks like Barclays and Green Dot to provide drivers with instant payouts and credit tools.

Tightening regulation

As fintech matures, regulators are stepping in. KYC/AML requirements are evolving, decision-making algorithms face new scrutiny, and AI and crypto are moving into defined legal frameworks.
Examples: EU AI Act, PSD2/PSD3 updates, US BNPL oversight initiatives.

B2B fintech is gaining ground

The B2C space is crowded — but B2B fintech is full of untapped potential. Tools for SMBs, corporate payments, and automated financial ops are on the rise.
Examples: Ramp, Jeeves, Brex, Payhawk.

Localization and jurisdiction-first strategies

In 2025, global fintech means local-first. Licensing, data storage, language, and integration partners vary by market — and companies are designing products for multi-jurisdictional compliance from day one.

Scalability now depends on how well fintechs can adapt to multiple regulatory and operational environments.

Generative AI and Autonomous Financial Services

One of the most significant fintech trends in 2025 and beyond. LLMs and other generative models are no longer limited to support use cases — they’re starting to impact decision-making, document analysis, and product generation.
Examples: automatic credit profiling, AI-powered investment assistants, generation of offers and legal agreements.
Fintech expert Kirill Gurbanov, who contributed to this article, shares his perspective:
  • Kirill Gurbanov
    CEO, Founder, Seasoned Executive in FinTech & Banking, PropTech
    The adoption of generative AI in fintech is still in its early stages, but it’s developing rapidly. While many companies are actively exploring GenAI capabilities, large-scale deployment in core operational processes still lags behind traditional AI/ML systems.

    The potential is enormous — from boosting efficiency to enabling personalization and building entirely new products.

    However, there are also major challenges: training data quality, ethical concerns like bias and fairness, hallucination risks, lack of transparency and explainability, high computational costs, and strict compliance requirements.
  • Kirill Gurbanov
    Right now, GenAI acts more like a powerful augmentation layer built on top of traditional AI.
    A full disruption of mission-critical processes by GenAI alone is still a distant prospect. The key to success lies in solving the 'last mile' — safely integrating GenAI into tightly regulated systems, validating outputs, and ensuring compliance.

    The development of domain-specific financial LLMs and robust AI governance tools will be essential for wider adoption.

    It’s also important to emphasize that most of these scenarios are about augmenting human expertise — not replacing it. GenAI can enhance analysts’ productivity, assist financial advisors, and improve data quality for traditional ML models. That pragmatic approach reflects how the industry is embracing this emerging technology.

Sustainability and Ethics on the Rise

ESG and green finance are gaining traction, especially in Europe. Fintech companies are expected not only to check regulatory boxes, but to genuinely assess the impact of their products — on people and the environment.
Examples: carbon footprint trackers, anti-discrimination scoring models.
As fintech matures, the focus is shifting: away from flashy user experiences and toward robust infrastructure, regulatory alignment, and B2B product depth.

The industry is entering a new phase — one that demands a fundamentally different approach to building, scaling, and securing financial technology.
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Hiring in Fintech: What Makes It Different

Fintech teams operate under high stakes — with complex technology stacks, strict compliance standards, and serious responsibilities. Naturally, this impacts hiring: expectations, onboarding, and candidate profiles often differ significantly from other IT verticals.

What companies are looking for

Fintech companies are constantly hiring backend engineers, DevOps/SREs, data professionals, compliance and fraud specialists. But even for these familiar roles, the bar is higher — especially around mindset, accuracy, and stress tolerance.

Key soft skills:
  • Attention to detail, habit of double-checking and documenting logic.
  • Ability to explain decisions and follow established processes.
  • Emotional maturity and resilience — this isn’t a playground for chaos-driven teams.
Tech stack:
  • Common backend stack: Go, Java/Kotlin, Python, PostgreSQL, Kafka, Kubernetes.
  • Security-first mindset: TLS, OAuth2, encryption, audit logging, reportable data flows.
  • Fintech-specific experience: integrations with banking APIs, RegTech tools, commission engines, fiscalization, and more.
Nice to have:
  • Previous experience with sensitive data and awareness of its risk surface.
  • Understanding of KYC/AML, PCI DSS, GDPR, or other baseline regulatory frameworks.
  • Background in banking, payments, or fintech is a plus — not mandatory, but helpful.
This creates a narrow candidate pool — and means recruiters need more than just technical literacy. They also need to assess soft skills, composure, and a candidate’s ability to thrive under strict requirements.

What Affects the Hiring Process

Hiring in fintech isn’t just about a great tech interview and an offer. In mature, licensed companies, the process is often more layered — with additional steps around legal, compliance, and security:
  • Compliance and security checks
    In many fintech companies, candidates go through background checks and compliance procedures. This may include education verification, criminal background checks, or screening for sanctioned entities — especially for roles with production access. NDAs are standard; access rights are granted in stages.
  • Regulatory approval
    If a company is licensed in the EU, UK, UAE or similar jurisdictions, hiring for certain roles (e.g. CTO) might require regulatory sign-off. HR and legal teams are often involved as early as the first interview round — especially for C-suite roles.
  • Structured interview flow
    Interviews go beyond tech rounds — candidates may face situational or judgment-based case studies, particularly those simulating high-stakes environments. Compliance officers, internal risk managers or even the CEO may participate in final rounds, even for engineering hires.
  • Onboarding requirements
    Starting a fintech job often involves complex onboarding: security clearance, infrastructure access, logging protocols, data storage guidelines, and training for certified environments (e.g. PCI DSS). It's a structured, sometimes intense, process.
In short: fintech hiring is more than finding the right skillset — it’s about finding the right mindset, and navigating the layers of rules that govern the industry. Recruiters who understand both people and policy have the edge.

Hiring in B2B vs. B2C Fintech: What’s the Difference

At first glance, hiring for B2B and B2C fintech might seem similar — but in practice, the ideal candidate profiles can be very different.

In B2B fintech, the focus is on integrations, stability, and long-term architecture. Products are often API-first, with UX coming second. These teams typically look for engineers who can:
  • build scalable infrastructure;
  • navigate complex external systems and business logic;
  • adapt solutions to meet regulatory and partner requirements.

In B2C fintech, it’s all about real-time performance, user experience, and fast iterations. Teams prioritize candidates who can:
  • ship features quickly without breaking stability;
  • think from the user’s point of view;
  • work across engineering, support, and product marketing.

For recruiters, this means one thing: even roles with similar job titles may require completely different strengths and working styles.

Hiring Across Borders: Remote and Distributed Teams

Fintech has been remote-first long before it became a trend — largely driven by the need for local regulatory knowledge, global reach, and fierce competition for talent.

The typical team structure:
  • Core functions — product, architecture, security — are based in one region, usually tied to the company’s regulatory license.
  • Engineering, support, analytics, and data — are distributed across other countries.
  • Compliance, finance, and legal — must be aligned with local regulatory requirements.
Challenges of hiring for distributed fintech teams:
  • Data access: some jurisdictions restrict remote access to production or customer data.
  • Tax and employment regulations: in some countries, you can’t hire directly — companies rely on EORs or contractor models.
  • Time zones and availability: real-time products often require partial team presence during business-critical hours.
A growing trend is a hybrid setup: core functions stay in the license-holding country, while the rest of the team is remote — with strict access policies and clearly defined areas of responsibility.

Salaries and Market Competition

Fintech companies aren’t just competing with each other for talent — they’re also up against traditional banks and broader tech. This affects both salary ranges and candidate expectations.

Overheated roles:
  • Engineers with experience in highload systems, security, and failover architecture.
  • DevOps / SRE specialists with infrastructure certifications (e.g., PCI DSS).
  • ML and antifraud experts who can build explainable models and assess risk.
Where salaries are above market average:
  • Banking, crypto, and enterprise fintech — where sensitive data is the core of the business.
  • Infrastructure-heavy fintechs that rely on strict SLAs and system uptime.
  • Roles tied to licensing, compliance, or regulated processes.
Key factors to keep in mind:
  • The bar for entry is high: strict requirements, long approval chains, and complex onboarding.
  • But once onboarded, retention is strong: fintech tends to attract people who stick around.
  • The high barrier deters some, but those who make it in are often in it for the long run.
Hiring in fintech requires structure, precision, and long-term thinking. There are no universal playbooks — every process depends on jurisdiction, licensing, and internal architecture.

What matters is understanding the constraints from day one — and building a hiring strategy that supports not just growth, but resilience.

Final Thoughts

Fintech is a unique corner of the tech industry — where engineering meets strict regulation, security, and constant pressure to scale. The most successful products emerge at the intersection of solid architecture, risk awareness, and adaptability.

To build and grow in this space, you need more than just code. You need a deep understanding of market dynamics, compliance frameworks, technology stacks, and what makes fintech hiring fundamentally different.

For more than eight years, Lucky Hunter has been connecting the best IT specialists with FinTech companies worldwide. Fill out the form, and we will contact you soon.
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Olga Makhina
Content Manager in Lucky Hunter
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