AI in FinTech: Benefits and Obstacles You Should Know About in 2025

AI and FinTech have become increasingly inseparable, and such a connection will be stronger and stronger with each passing year, thanks to the benefits that AI brings to this industry. It makes FinTech services more secure and generally transforms how companies deliver them, focusing on customer satisfaction and business performance.

As an IT company with 13+ years of experience in FinTech software development and a solid expertise in AI solutions creation, we are here to tell you what AI in FinTech industry is, its major benefits, challenges, and the end-to-end AI automation roadmap.

AI in FinTech refers to the use of artificial intelligence technologies to improve, automate, and personalize financial services. It involves utilizing smart systems that learn from data to make your financial processes smarter, faster, safer, more efficient, data-driven, user-friendly, and less prone to human error. Such AI tools can analyze vast amounts of financial data, detect patterns, predict outcomes, and make decisions without human intervention.

AI in FinTech industry is growing fast and demonstrates incredible performance and revenue indicators, proving its great potential. We’ve collected the most telling statistics that show the AI and FinTech market perspectives:

• Future Market Insights reported that the global AI in FinTech market was $13,515.7 million in 2024
• According to the same Future Market Insights, overall AI in FinTech market is expected to be $58,701.4 million by 2034, reflecting a robust CAGR of 15.9%
• CoinLaw revealed that approximately 40% of loan approvals now incorporate AI analysis, reducing processing times by up to 30%
• According to Reuters, the bank's AI tools contributed to a 20% increase in asset and wealth management sales between 2023 and 2024, with expectations to expand client portfolios by 50% over five years

AI in FinTech gives financial institutions a lot of advantages over competitors, starting with lower operating costs and ending with enhanced fraud detection. Also, it brings gains for clients such as faster service, better personalization, and more. Now, let’s take a look at the benefits for both your FinTech businesses and your clients.

Here are the main benefits FinTech companies get when they implement AI tools:

Your clients also receive many advantages when you use AI when delivering financial services, since artificial intelligence greatly improves service speed and quality. There are the main:

FinTech AI tools mainly help in three aspects of your business: customer experience, employee productivity, and process optimization. Let’s look at the top 3 AI use cases in the FinTech industry according to these aspects.

AI reshapes how FinTech companies interact with users. It delivers faster answers and adapts responses in real time. By removing friction and personalizing interactions, firms increase engagement and build trust between them and their clients.

AI applications in FinTech include intelligent advisory tools like chatbots and virtual assistants. These tools interpret both customer and internal team questions, analyze the context, and generate accurate, conversational replies. In addition, AI-managed portfolios enable platforms to create personalized investment strategies tailored to specific financial goals.

Let’s look at companies that have implemented AI in their financial services and have already enhanced their customer experience:

• NatWest Group. They are a UK-focused bank serving over 19 million customers, with businesses across retail, commercial, and private banking markets. NatWest Group has implemented the models that analyze customer behavior and provide business insights based on it. These AI models help the bank deliver personalised support that customers want and need, and detect if customers might be in the process of being scammed.
• Thomson Reuters. Thomson Reuters is a technology company that has been providing its clients with trusted content and workflow automation for decades. They integrated an internal sandbox for secure and scalable testing and utilization of large language models with support for fine-tuning. As a result, they empower teams to quickly develop AI solutions to accelerate the creation of personalized and efficient services for customers.

AI helps teams extract value from data that would otherwise go unused. Many financial firms store years of documents, filings, and emails, yet struggle to turn them into actionable insight. Moreover, Fintech and AI solutions automate the discovery process, freeing up analysts and compliance teams to focus on decision-making.

Teams now use FinTech AI tools to build structured data on demand, competitor landscapes, product catalogs, and relationship maps from unstructured sources. Such an approach helps organizations stay ahead of the market and respond quickly to changing dynamics. Let’s look at companies that boosted financial team productivity by implementing AI in their financial services:

• BBVA. BBVA is a customer-centric global financial services group that has a strong leadership position in the Spanish market. They have implemented the AI analytics tools that collect and structure data. It gives efficiency in managing large amounts of data for more than 2,800 data engineers and architects.
• Deriv. They are one of the world’s largest online brokers. Deriv implemented a generative AI solution to integrate and search information from multiple internal sources, including Slack, Google Docs, and others, without the need for machine learning expertise. Thanks to it, the company reduced new hire onboarding time by 45% and accelerated recruiting tasks by 50%.

Workflow automation is one of the most valuable AI applications in FinTech. It streamlines complex documentation tasks and supports product development. Fintech entities use AI to handle routine but essential work that once slowed down growth.

Firms use FinTech with AI to automatically draft research reports, loan documents, insurance policies, and regulatory communication. AI also powers new product features like natural language stock screening for wealth advisors and clients. These innovations reduce time-to-market, support compliance, and drive competitive advantage.

Here are organizations that integrated AI in their services and optimized financial workflows:

• Crypto.com. They are a cryptocurrency company with approximately 100 million users across 90 countries that offers a trading platform, derivative exchanges, and more. Crypto.com has implemented generative AI to perform high-speed and multilingual sentiment analysis of the crypto market. As a result, the company is able to provide accurate and localized real-time market insights to its users, thanks to streamlining financial workflows and improving the user experience.
• Zurich Insurance. Zurich is a leading multi-line insurer serving people and businesses in more than 200 countries and territories, and has more than 63,000 employees and over 75 million customers. They integrated an AI-CRM system that recommends insurance products based on customer needs. Thanks to this, Zurich Insurance reduced customer service time by more than 70% and improved the quality of interactions.

The process of integrating AI in FinTech is complex and involves many aspects, starting with choosing a reliable vendor and aligning on an AI strategy and ending with solution development, testing, and deployment. To simplify it for you, we have prepared a step-by-step guide on how to integrate AI in your financial company.

Choose a technology partner with experience in providing FinTech development services, who understands financial regulations, can build secure banking, investment, and payment systems, and knows how to work within strict compliance requirements. This expertise ensures smoother development, fewer risks, and faster approvals. On top of that, look for proven AI capabilities, including machine learning, automation, and data analytics.

The right IT services provider supports you at every phase of the development cycle, from early decision-making and risk assessment through proof of concept (PoC), full-scale development, and long-term support. Don’t forget to look at the partner’s portfolio and check client reviews on trusted platforms like Clutch because it clearly shows the quality of services they provide.

Work together with your partner and figure out where AI can really add value in your financial business. Evaluate which of the outcomes you are prioritizing: better customer engagement, simplifying employees' workflows, or streamlining processes. Your vendor checks the data you have to consider the ability to train an effective model on it. After this stage, your IT services provider will start to create an implementation roadmap. This way, your IT partner helps to kick-start your AI in Fintech implementation journey that begins with a business goal to grow it into tangible business results.

Work with your FinTech software development partner to create a PoC and test your idea. At the PoC stage, your vendor introduces a limited piece of functionality to understand if the idea makes sense in practice and delivers real business impact. Also, they should collect feedback from employees to help clarify whether the solution improves workflows or addresses key pain points. Based on these insights, you can decide whether to scale the solution further.

Based on validated use cases and available data, the team refines the model, ensures stable performance, and integrates the solution into your business infrastructure. The goal is a seamless transition from PoC to a production-ready system that delivers measurable results. Once deployed, your AI solution will deliver real-time value, ready to support business growth from day one. A structured launch plan and ongoing performance monitoring ensure your model remains reliable, secure, and aligned with shifting business demands.

Despite the benefits of AI in Fintech, there are also obstacles that you need to solve. We’ve outlined the main obstacles to integrating AI in your financial services and ways to cope with them.

Challenge: AI applications in FinTech must comply with a complex mix of global and regional regulations (Source: Research by Wiley). Any lapse could lead to legal exposure or data breaches. Entrepreneurs often struggle to align AI tools with evolving standards like PSD2, GDPR, AMLD, or MiFID II. This challenge intensifies as businesses scale across markets with different legal frameworks.

Cleveroad’s solution: We design AI with compliance in mind from day one. Our team has deep experience building FinTech AI tools that meet global and regional standards, including GDPR, PCI DSS, PSD2, AMLD, MiFID II, ePrivacy, and eIDAS (QES, SES, AES). Whether your product involves digital signatures, KYC, or CLOB-based trading, we ensure your AI integrates securely and lawfully across all your operational regions.

Challenge: Using AI with FinTech means handling sensitive financial and personal data. A single weak point in data security can damage user trust and trigger regulatory fines. As more AI use cases in FinTech emerge, risks grow.

Cleveroad’s solution: As a company upholding ISO/IEC 27001:2013 certificate for security management standards, we apply clear and documented processes to manage risks, control access to sensitive data, and prevent breaches. For every FinTech project, we implement such security measures:

• Security testing
• Malware & fraud protection
• Vulnerability assessment
• RegTech

With our assistance, you can safely leverage artificial intelligence for FinTech while meeting security requirements and customer expectations.

Challenge: AI projects demand serious investment, especially in FinTech, where companies must strengthen infrastructure and secure sensitive data. Moreover, companies often face overinvestment by implementing complex solutions without proven value, forced to incur extra costs again and again until they find the perfect AI solution.

Cleveroad’s solution: We reduce the risk of ineffective investments starting at the POC. Such an approach allows you to test the value of AI for your FinTech business by implementing only a partially functional product and significantly reducing the initial investment to identify the right AI solution and assess its business impact.

Moreover, we also provide flexible cooperation models for AI development and deployment in FinTech, giving you the choice between custom development, a dedicated team that fully manages all processes, or IT staff augmentation to extend your AI dev capabilities with several specialists working under your management.

Recently, we’ve delivered IT staff augmentation services for our client in the FinTech industry from Denmark, named Penneo. They have about 3000 clients within various industries, including Audit and Accounting, Finance and Banking, and Real Estate. They also cooperated with well-known companies such as Deloitte, KPMG, Jyske, and others.

Penneo partnered with Cleveroad to quickly augment their internal platform team with two senior DevOps engineers. Throughout the collaboration, onboarded Cleveroad DevOps engineers handled diverse tasks to support cloud infrastructure according to our client’s practices, using the Infrastructure-as-Code approach and Terraform as an IaC tool.

See what Hans Jørgen Skovgaard, CTO at Penneo, says about cooperation with Cleveroad.

Challenge: Building and deploying AI in FinTech isn’t simple. From data processing to training custom models, the technical depth required often overwhelms internal teams. Even firms familiar with the benefits of AI in FinTech may hesitate due to the complexity of implementation.

Cleveroad’s solution: We bring high-skilled AI engineering to your FinTech projects. Our team creates custom AI solutions that automate workflows, predict user behavior, and enhance decision-making. Clveroad specialists specialize in NLP, smart chatbots, predictive analytics, and generative AI models tailored to FinTech.

Integrating AI with FinTech offers transformative value, but only when challenges like regulation, security, cost, and complexity are addressed. At Cleveroad, we deliver fintech artificial intelligence solutions that are compliant, secure, and scalable. Let us tell you more about how we can help you.

Cleveroad is a FinTech software development company with 13+ years of domain experience. We also have deep expertise in AI development, helping our clients implement advanced AI-driven solutions tailored to their unique needs. Our team develops various AI solutions for FinTech, including AI-based fraud detection and risk management, automated trading software, personalized finance assistants, NLP-powered chatbots for customer support, and much more.

Choosing Cleveroad to implement artificial intelligence in your FinTech business, you’ll get:

• Flexible cooperation models to match your resource needs: Dedicated Development Team, IT Staff Augmentation, and Project-Based Cooperation
• Free Solution Workshop stage to align your FinTech AI needs with the technical realization within a comprehensive AI implementation roadmap
• AI POC services to validate and refine the compatibility and performance of a new technology solution with your FinTech business IT ecosystem
• Partnership with an ISO-certified company that strictly adheres to ISO 27001 security standards and implements ISO 9001 quality management systems
• All guarantees for your business information security and signing an NDA per your request

We have hands-on experience smoothly implementing AI in the FinTech industry, and to prove our skills, we would like to present one of our recent case studies.

Cleveroad developed an investment management system for our client from the UK, who is a conglomerate with 22 years of experience in property investment. Their goal was to create a scalable ecosystem that would serve individual and institutional investors, advisors, and property developers, all within a single platform.

To address our client’s business needs, we designed and developed a comprehensive system that included mobile apps for investors and advisors, a web portal, and an admin dashboard. The Cleveroad team built the platform with security and compliance at its core, including a robust KYC module with multiple verification options. The platform also features investment flow management, user role-based access, electronic contract signing, support request handling, and banking system integration for transactions and tax processing.

Also, as part of the investment platform, we introduced an AI-based Investment Advisor — a smart feature designed to support investors in making informed decisions. Leveraging user profile data, investment history, risk appetite, and current market trends, the AI module suggests optimal investment opportunities within the platform.

As a result, our client received an investment management system on time and within budget. Over the first operational year, investors contributed £164.4M through the platform, and revenue reached £7.6M and grew to £9.3M the following year. The platform not only simplified the investment process but also significantly boosted user engagement and investor trust.