Fintech: The democratising effect of digital money

Financial Services Trends Report: A snapshot of fintech-led innovation, connectivity and transformation in financial services, with expert insights on talent and leadership.

Fintech market outlook

Through tech innovators, disrupters, and organisations in transformation, fintech has radically changed the financial landscape, reshaping markets and the broader economy. Initially tied to gold, banknotes, coins and cheques, money now flows through a mobile, digital-first ecosystem.
In the process, money has been democratised, enabling remote, commercially unviable, or underserved communities to engage in economic activity, and enhancing financial literacy worldwide. In driving efficiency, financial inclusion and investment in financial services, the fintech industry achieved a value of $320 billion in 2024, and is projected to reach $1.5 trillion by 2030¹
A broad consensus identifies growth coming from:
- (i) tech advancements
- (ii) regulatory dynamics, and
- (iii) shifting consumer preferences.
Advanced technologies combined with billions of unbanked or underbanked individuals-turned-consumers creates a glittering horizon. In addition, GenAI is set to turbo-charge the evolving financial landscape, alongside other game-changing technologies such as application programming interface (API), blockchain, regulatory technology (RegTech), robotic process automation (RPA) and data analytics.
In such a data-driven industry, GenAI is valuable for creating synthetic datasets for risk assessment, enhancing customer service through advanced chatbots and providing financial market forecasts. Analysis of real-time transaction data enables immediate detection of anomalies in customer behaviour, significantly enhancing cybersecurity.
Customer experiences leveraging GenAI are slower to gain traction, primarily due to the potential for mistakes and errors with real-world consequences, as reported in Deloitte’s State of Generative AI in the Enterprise. In creating new content using public, unstructured and multimodal data, GenAI creates more opportunities for misuse and error. However, adoption of non-customer facing traditional AI systems and GenAI continues at pace:
- Morgan Stanley uses OpenAI-powered tool Debrief to support client meetings in wealth management;
- Citi and JPMorgan Chase have a Gen AI tool for employees;
- BNY Mellon signed a multi-year deal with OpenAI to supercharge the bank’s internal AI platform; and,
- Lloyds Bank in the UK uses AI to focus on personalised services, streamlining processes and improving security.
These initial investments indicate ‘a long-term shift in how financial institutions operate,’ comments data transfer fintech Plaid. However, financial institutions will need to update AI governance frameworks to address legal and reputation risk, as well as cyberattacks and fraud. McKinsey cautions that traditional AI-risk-governance systems are not designed to oversee GenAI using public, unstructured and multimodal data. They advise incorporating model risk management (MRM) and new technology, data and legal risks into the enterprise risk model.
API integration is enabling businesses to provide Banking-as-a-Service (BaaS), with banking capabilities embedded directly onto their platforms, covering payments (e.g. Stripe), data aggregation & verification (e.g. Plaid), and trading & portfolio management (e.g. Robinhood). As regulatory frameworks evolve, BaaS platforms are bridging the gap between traditional banking and emerging digital ecosystems. According to Fintech Magazine, the top five BaaS providers globally are: Engine by Starling Bank, Marqueta, Mambu, Green Dot, Solaris and ClearBank.
Regulatory frameworks won’t take too long to evolve, with RegTech revolutionising financial compliance, transforming regulatory processes. AI, ML and data analytics are helping institutions with a complex regulatory environment, reducing costs and mitigating risks through fraud detection, ID verification and real-time transaction monitoring. Leading providers include Ascent and Chainanalysis (USA), Alyne (Germany), Blinking (Serbia), Cleversoft (Benelux & Germany) and ComplyAdvantage (UK).
Blockchain is enabling the creation of cryptocurrencies, prompting new compliance and regulatory processes. The Trump Administration’s more favourable outlook on digital assets, evidenced by the President’s own cryptocurrency ventures, is encouraging an assertive bid by fintech firms and crypto companies to be licensed as state or national banks. Bank status can reduce the cost of capital and doing business, while providing legitimacy to attract customers and pursue market opportunities.
Stablecoins are a dominant force in the cryptocurrency ecosystem in terms of transaction volume and facilitation of financial activity. They take the form of US-dollar-pegged cryptocurrency tokens (usually 1:1) designed to maintain a constant value, used by crypto traders to move funds between tokens, and customers to make cheaper, instant payments via apps such as ApplePay, Paypal and Revolut.
In June 2025, the US Senate passed the stablecoin bill, known as the GENIUS Act (short for Guiding and Establishing National Innovation for US Stablecoins), to create a regulatory framework for the $250 billion market for stablecoins². The Republican-controlled House of Representatives will decide whether to adopt the Senate’s version, or push its own stablecoin bill, before final sign off by President Trump. The White House wants a stablecoin bill passed before August 2025.
This strategy supports the growth of digital assets, enshrined in the executive order on ‘Strengthening American Leadership in Digital Financial Technology’. In parallel, President Trump has prohibited the creation of central bank digital currencies, notably a ‘digital dollar’. This would, in his own words, “threaten the stability of the financial system, individual privacy, and the sovereignty of the United States,” reported by Pinsent Masons, who point to such a ban freeing the way for private cryptoassets.
Contrast this with Europe, where the European Central Bank (ECB) has created an innovation platform to explore the creation of a digital euro, signing up merchants, fintech companies, start-ups, banks and other payment service providers to explore payment functionalities and use cases. Findings are due to be published in late 2025. The ECB explains, “A digital euro would be a digital form of cash, issued by the central bank and available to everyone in the euro area”.
In the credit card market, Visa has extended its investment in blockchain technology by making a direct investment in BVNK, a stablecoin payments infrastructure player, the latest of its stablecoin partnerships. Visa is aiming to connect approximately 4.8 billion cards, 150 million accepting merchants and 14,500 financial institutions with the crypto ecosystem. Chris Harmse, Co-Founder and Chief Business Officer, BVNK commented, “This is really powerful validation from the world's largest payment network that stablecoins are the next chapter of global payments”.
Robotic process automation (RPA) is delivered in attended, unattended and hybrid formats to perform repetitive office tasks using software robots, or ‘bots’ such as ‘chat bots’. RPA combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. RPA is process-driven while AI is data-driven. For RPA to keep up with the market, tools will need to include intelligent automation (IA), incorporating sub-disciplines of AI such as machine learning, natural language processing and computer vision. Benefits include less coding, cost savings, higher worker satisfaction and better accuracy and compliance.
Over a third, 36% of all use cases of RPA, were in the finance and accounting sector identified by Forrester in 2023, with more than 1 in 3 bots currently in the financial industry. A number of banks use RPA solutions to automate customer research, account opening, inquiry processing and anti-money laundering, relieving humans of tedious, rule-based tasks.
With vast amounts of data in today’s digital-first, financial ecosystem, fintech data analytics are shifting decision making from reactive to proactive, redefining workflows, risk models and customer experiences. Realtime data streams and intelligent analytics enable financial institutions to anticipate market movements, detect fraud and understand customer behaviour in a dynamic approach enabling faster, more accurate decisions in a market demanding agility.
With a more personalised, predictive model of engagement, service providers can use data analytics to provide customised product recommendations, credit offers or budgeting tools at the moment of greatest impact, enhancing the customer experience, retention and lifetime value. Data analytics is therefore promoting a faster, smarter and more resilient financial ecosystem.
The rapid growth and success of the fintech industry is based on alignment with consumer preferences, notably digital and mobile services, personalised experiences, affordability and convenience. Fintech is used daily by 48% of Americans and 84% of UK respondents, according to Forbes, with almost equal take up by men (82%) and women (78%).
From a consumer perspective, fintech has ushered in an era of equality, empowerment, cost savings, financial management and personalised services. With so much power literally in an individual’s hands, traditional financial services organisations are upping their game in the more dynamic and customer-centric financial services ecosystem.