How AI Helps SMEs Compete in the Global Fintech Landscape
FEB 03, 2025
Imagine a young fintech business owner like you running a small but ambitious fintech SME. You have a great product, a motivated team, and the desire to make waves in a sea of industry giants. Yet, the market feels overwhelming, resources are limited, and the challenges never seem to slow down. How can you serve your customers better and more efficiently?
As discussed in our latest ebook, “AI Automation: The Future of Fintech”, the answer lies in AI and machine learning development for fintech, where we talk about how our AI/ML services for fintech can help you reach unprecedented heights. Once viewed as a distant innovation, AI has become the driving force behind significant advancements in financial services, like streamlining payment processes and enhancing customer service.
With the evolution of generative AI and large language models, AI's market value is expected to soar to $49 billion by 2028. This shift towards digitalization is key for improving critical areas such as credit risk management and personalized banking for SMEs. AI is helping small players to level the playing field with larger competitors.
Digitization: A Key Driver of SME
You're likely familiar with the challenges of securing financing. Traditional financial systems often fail to meet the unique needs of SMEs, from high costs and slow processes to the lack of access for businesses without credit histories or collateral. Through digital financial services (DFS) powered by cutting-edge technologies like AI, your business can access faster, cheaper, and more accessible financial products.
Role of Technology in Digitization
Mobile devices, big data analytics, artificial intelligence (AI), and machine learning (ML) enable a wave of change in SME finance. For example, mobile-based services allow SMEs, even those with limited financial literacy, to access essential financial products. Big data and AI are also being leveraged to assess credit risk using alternative data sources, which businesses without established credit histories need. This opens up financing opportunities for SMEs that traditionally wouldn’t have been able to get a loan from a bank.
Watch this insightful video where Armin Moradi (CEO & Co-founder, Qashio) and Parthi Duraisamy (CEO, Alaan) discuss how innovative tech and AI-powered fintech solutions can boost financial inclusion and help your fintech SME grow in the competitive market.
How can AI be advantageous to fintech startups and SMEs?
Many fintech startups and SMEs are competing to keep up with the demands of digital-savvy customers and regulatory challenges. From safeguarding against sophisticated cyber threats to providing hyper-personalized customer experiences, AI can help you stay ahead of others.
1) Advanced Fraud Prevention
Cybercriminals have honed their tactics, making traditional fraud detection software systems feel like relics of the past. AI-driven fraud detection software system works with both "good" (legitimate transactions) and "bad" (fraudulent ones)—to teach itself the patterns of financial fraud. As new transactions occur, the system learns, adapts, and evolves to stay ahead of fraudsters.
AI recognizes unusual behaviours, such as sudden password resets or contact detail changes. AI-driven fraud detection software analyzes subject lines, content, and email patterns to flag fraudulent ones and classify them as spam. AI and machine learning algorithms can accurately compare original and fake documents, authenticate signatures, and ensure your customer verification (KYC) process remains airtight.
2) AI-Driven Personal Finance Solutions
Traditional banking bombards customers with generic offers, but AI tools and strategies for FinTech SMEs can recommend tailored solutions—whether a credit card with travel rewards for someone planning a vacation or a remortgage option for a customer with fluctuating income. AI tools can also effortlessly categorize transactions using natural language processing (NLP). For example, the AI detects "Shell $44" as a fuel purchase and categorizes it under "transport."
AI-powered APIs streamline operations by automating data entry and access. For example, loan applicants can securely share their tax and financial details through APIs. AI’s ability to detect suspicious activity is a massive advantage. They use machine learning to spot anomalies, such as unauthorized changes in vendor payment details. You can avoid payment failure by blocking suspicious transactions before they occur with the help of AI tools and strategies for FinTech SMEs.
3) Streamlined Credit Evaluation
If you're still relying on manual processes to evaluate your borrowers’ creditworthiness, you’re slowing things down and exposing yourself to data entry errors, time constraints, and limited scalability. Traditional methods often miss key factors when analyzing a borrower’s creditworthiness, but AI doesn’t make that mistake.
With the capability of financial fraud detection in real-time with AI, this technology reduces fraud risks by detecting anomalies and red flags. It is also great at minimizing biases that may creep into manual assessments, ensuring fair and credible decision-making. Incorporating an AI-driven solution for credit risk assessment creates a smoother, faster, and more transparent experience for your borrowers.
4) Smarter Trading and Portfolio Management
AI algorithms level the playing field by scanning thousands of price charts across geographies and exchanges in minutes for an SME where resources can be limited compared to larger competitors. You don’t have to restrict your trading opportunities to a few markets, as AI identifies the best trading conditions globally with smart AI-powered financial advisors.
AI-powered trading bots detect favourable market conditions and execute trades with unbelievable speed. With the facility to place and execute large orders within seconds, AI ensures that your business capitalizes on fleeting opportunities before they vanish. AI helps optimize portfolio allocation by suggesting adjustments dynamically, ensuring that your portfolio aligns with evolving market conditions and risk tolerances.
5) AI-powered Virtual assistants
Your customers expect instant responses and round-the-clock service, and AI-powered virtual assistants for fintech SMEs can do what is needed. Earlier, customers had to endure endless phone queues or long waits to resolve fundamental issues. However, AI-powered virtual assistants for fintech SMEs can handle routine queries like password resets or interest rate checks 24/7.
AI agents for fintech SMEs offer personalized experiences by tailoring interactions based on customer preferences and past behaviours. For instance, they can recommend financial products aligning with customers' needs. AI chatbots and voice assistants can handle up to 80% of financial queries and respond to inquiries 10 times faster than human agents in the banking industry. These bots can manage thousands of interactions simultaneously without breaking a sweat.
6) Data-driven decision making
Millions of transactions, user interactions, and market signals come at you daily. With this data, you can extract actionable insights in real-time with AI. Unlike us, AI depends on empirical evidence and statistical analysis, ensuring accurate and error-free decisions. You can understand customer behaviours, preferences, and demographics with rich insights.
The evolution of explainable AI ensures you’ll get clear, understandable explanations for every recommendation. Moreover, with the combo of edge computing and AI, you can process data locally, reduce latency and get real-time insights. This is invaluable in areas like financial fraud detection in real-time with AI and instant loan approvals. With technology becoming more affordable and accessible, fintech SMEs are set to join the party.
If you're keen on understanding how smart automation for fintech can drastically reduce costs and increase efficiency for fintech SMEs, our ebook, “AI Automation: The Future of Fintech”, is your guide.
Case Studies of Successful AI Implementation in Fintech SMEs
By adopting AI, these fintech businesses are automating routine tasks and creating new opportunities to enhance decision-making, improve customer engagement, and minimize operational risks. Explore real-world case studies of successful AI Implementation in Fintech SMEs that showcase how Fintech SMEs have successfully integrated AI technologies.
1) QuickLoan Financial
Challenge: As QuickLoan Financial grew, the company faced the challenge of managing an increasing volume of loan applications. The manual process delayed loan approvals and frustrated their customers. The inefficiencies strained QuickLoan’s resources, limiting its ability to scale. The company needed to find a way to process loans faster and more accurately.
Solution: QuickLoan Financial decided to implement an advanced AI-driven model designed to automate the entire loan approval process. The AI system assessed applications based on various criteria, including credit scores, employment history, and overall financial behaviour. AI processed the application forms and financial statements and analyzed unstructured data, such as bank statements and transaction histories. The system could extract valuable insights from these sources and give QuickLoan a much clearer picture of each applicant’s financial situation.
Result: The company saw a remarkable 40% reduction in loan processing time, meaning customers got their approvals faster than ever before. The AI-driven system helped the company reject high-risk applications with 25% greater accuracy. This improved the quality of loan approvals, reduced defaults, and boosted customer satisfaction.
2) SwiftCredit Lending
Challenge: SwiftCredit Lending was facing some major hurdles when it came to assessing creditworthiness. Their traditional methods relied on credit histories, which many potential borrowers—especially in underbanked regions—didn't have. Many applications were getting rejected, limiting their customer base and growth potential.
Solution: SwiftCredit decided to take a bold step and overhaul its entire credit scoring process by embracing an AI-driven solution for credit risk assessment. The system integrated traditional and alternative data sources, like mobile phone usage, bill payments, and even social media activity. They leveraged natural language processing (NLP) to analyze text data from social media and bill payment histories, while predictive analytics helped forecast future credit behaviour. SwiftCredit was able to speed up loan approvals and make them more efficient.
Result: With the AI-based credit scoring system, SwiftCredit Lending saw a 40% increase in approved loans within just six months. But that’s not all—there was a 25% reduction in default rates, proving the system was more accurate and reliable. They could now serve customers without traditional credit histories, which allowed them to expand into new markets.
3) MetroBank Group
Challenge: MetroBank Group found itself drowning in an ocean of customer data but couldn’t make the most of it. With a diverse customer base, they had a hard time offering personalized services. Instead of being able to predict what customers wanted, they were stuck with generic marketing that failed to hit the mark.
Solution: The turning point came when MetroBank decided to implement an AI-powered analytics platform. It was a smart, AI-driven system that utilized machine learning algorithms to dig into customer behaviour patterns, transaction histories, and interactions across various channels. Whether it was online banking, ATM usage, or even social media feedback, the AI combined all this data to create a comprehensive 360-degree view of each customer. Real-time data processing allowed the bank to make personalized recommendations and offer timely financial advice.
Result: Customer satisfaction skyrocketed by 30%, and engagement rates jumped by 20%. With more targeted, personalized marketing campaigns, MetroBank saw a 35% increase in the uptake of recommended products. Their retention improved, new customer acquisition soared, and solidified MetroBank’s reputation as a customer-first bank.
Listen closely to the video below to understand how Artificial Intelligence will impact the financial industry in the coming years. Here, the representatives from Wex, Home Trust and Wells Fargo are talking about the opportunities for sustainable growth, the effect of AI on finance and banking, and the common challenges surrounding its implementation.
If you want to dive even deeper into such great examples and learn specific strategies for using AI in your own fintech business, we highly recommend going through our e-book.
Implementation Challenges and considerations for fintech SMEs
Surprisingly, only a handful of fintech firms have experienced major financial gains from artificial intelligence despite the enormous promise of AI. The issue is that many businesses cannot handle typical fintech AI deployment difficulties. These are the most typical obstacles to financial AI implementation.
1) Regulatory Compliance Risks
With AI taking over many financial processes, keeping up with compliance standards has become increasingly challenging. Falling short of these requirements can lead to hefty penalties and harm your company’s reputation. Your financial firm must stay proactive and adjust AI systems to align with changing regulations. Read our ebook for a comprehensive overview of regulatory challenges.
2) Issues in Integration
Bringing AI into existing financial setups isn’t always seamless. Older systems may not easily align with new AI technologies, leading to possible disruptions. Careful planning is needed from the beginning to ensure the integration process runs smoothly and avoids interruptions to day-to-day operations.
3) Protecting Customer Privacy
AI depends on customer data to offer tailored services, which raises significant concerns about data privacy. Striking the right balance between leveraging AI's capabilities and safeguarding personal information is difficult. You must prioritize customer trust by adhering to strict privacy laws and handling data responsibly.
4) Algorithmic Bias
AI solutions for fintech SMEs can unintentionally carry over biases from the data they’re trained on, resulting in outcomes that may be unfair or discriminatory. This can affect decisions like loan approvals, credit scoring, or customer interactions. To prevent this, financial institutions need to ensure their datasets are inclusive and accurately represent diverse groups.
5) Cybersecurity Concerns
As AI systems manage sensitive financial information, they’re prime targets for cyberattacks. Establishing strong security measures to shield these systems from potential threats is a must. Your financial organization should routinely update its cybersecurity strategies to stay ahead of malicious actors.
Best AI fintech startups in 2025
The fintech industry will continue to employ AI-powered fintech solutions in 2025 to solve specialized issues, making decentralized finance, investments, money management, and incentives simpler and safer.
1) ProRata.ai
ProRata.ai, one of 2025’s hottest fintech startups, has transformed how creators and publishers are credited and compensated in the domain of content creation. Launched in 2024 and headquartered in Pasadena, California, the company raised an impressive $25 million in Series A funding.
Many AI systems often reuse copyrighted material without properly crediting or compensating the original creators. ProRata.ai steps in as a secure fintech solution, ensuring fair attribution and revenue sharing for creators and publishers. ProRata.ai offers a 50/50 revenue split to publishers and creators who register their content. It is behind Gist.ai, an AI-powered search engine that prioritizes licensed, high-quality content to deliver concise and accurate answers. Big names like Universal Music Group, The Atlantic, and Financial Times have partnered with ProRata.ai.
2) Figure Markets
Figure Markets is a San Francisco-based company that has changed how investors trade in blockchain-native assets. Founded by Mike Cagney, who is also behind SoFi and Figure Technologies, Figure Markets focuses on creating a decentralized custody marketplace where users can trade a broad spectrum of assets, like cryptocurrencies, stocks, bonds, and even credit.
Centralized custody often comes with significant vulnerabilities—if a centralized institution is hacked or suffers a failure, all assets under its control are at risk. Figure Markets eliminates this problem by decentralizing custody. Instead of storing all assets in one place, they split the keys across a network, making it far more difficult for hackers to access the full range of holdings. Figure Markets also offers crypto-backed loans, by which you can borrow your crypto holdings and retain ownership instead of selling them.
3) Rewmo
The brainchild of Gary Reinhold (CEO) and Edward Ellis (CGO), Rewmo is headquartered in Fountain Hills, Arizona. Rewmo is doing something that’s never been done— turning everyday, unavoidable expenses like rent, loans, and utility payments into rewards. Since launching in 2024, Rewmo has secured an impressive $28 million in funding.
Instead of just watching your hard-earned money go toward bills and debts monthly, Rewmo allows you to earn points on these payments. Your rent or loan payment could help you score cash, travel perks, or even rewards for shopping and dining. It’s a simple, free-to-use platform with no hidden fees or transaction charges so anyone can hop on board. Rewmo’s current focus is rolling out services in five key states of the USA.
4) Loaded Luxury
Loaded Luxury, one of the best AI fintech startups in 2025, has introduced new ways for people to manage their assets. This Toronto-based platform was founded by Randy Frisch, a seasoned tech entrepreneur and author, to provide a secure fintech solution for tracking and managing high-value possessions, such as vintage watches and luxury vehicles.
With its AI-powered platform, Loaded Luxury offers a unified and digital approach to organizing, documenting, and securing valuable possessions. It also provides a "Digital Memorandum" to help users keep detailed records for insurance purposes and estate planning. Users can sort and store their assets in customizable categories and easily access their assets. By late 2025, the platform plans to roll out globally, targeting key European and Asian luxury markets.
5) Thane
With its headquarters in Northwest Singapore, Thane is making waves in the world of decentralized finance (DeFi) as one of the most promising AI-powered fintech startups in 2025. Founded by Lena Roesch and Alex Robinson, Thane innovated how users operate through the intimidating and complex world of DeFi.
Thane aims to simplify the DeFi experience and make it accessible to crypto enthusiasts. Its emphasis on community and education sets Thane apart from other DeFi platforms. The platform's roadmap includes exciting developments like a video-first mobile app and enhanced social features. Users can share and replicate strategies within the community. The platform allows users to conveniently discover, monitor, and execute DeFi strategies. A beta version of the platform, which includes a Telegram-based mini-app, is already live and receiving valuable user feedback for refinement.
Integrate AI/ML today to Compete with global fintech giants
AI opens up many growth opportunities for SMEs, especially in a competitive market. With smart automation for fintech in handling repetitive tasks, you can focus on innovative ideas for customer satisfaction. As the demand for AI solutions for fintech SMEs grows, so does the need for skilled developers. This is where companies like Webelight Solutions Pvt. Ltd. come in.
With deep expertise in AI and machine learning development for fintech, we help small fintech businesses like yours with AI-powered financial advisors and smooth AI integration in their infrastructure. Our team will help you implement the right AI tools and strategies to boost your ROI ultimately.
