Karsten Wenzlaff, Advisor
August 26th, 2025
Karsten Wenzlaff is a Crowdfunding and Fintech Expert from Germany. He is Secretary-General of Digit[...]
Synergy and disruption: Ten trends shaping fintech
McKinsey&Company | Dec 2018 | By Jeff Galvin, Feng Han, Sarah Hynes, John Qu, Kausik Rajgopal, and Arthur Shek
As the fintech landscape continues to evolve, a look at the newest developments from across the globe.
Fintech, the portmanteau of finance and technology, represents the collision of two worlds—and the evolution of the use of technology in financial services. Financial services and technology are locked in a firm embrace, and with this union comes both disruption and synergies.
Insight: What fintech can learn from Robinhood’s ‘epic fail’ of launching checking accounts
Financial institutions are engaging with fintech start-ups either as investors or through strategic partnerships. Almost 80 percent of financial institutions have entered into fintech partnerships, according to McKinsey Panorama. Meanwhile, global venture capital (VC) fintech investment in 2018 has already reached $30.8 billion, up from $1.8 billion in 2011 (Exhibit 1).
Average deal size is growing as well, particularly in Asia, where it is almost twice as large as the global average, due largely to a number of mega deals.1 The investing public is also enamored of fintechs: Zhong An made waves with its $11 billion IPO valuation last year, while Ant Financial is reported to be raising a pre-IPO round valuing the company at $150 billion.
However, the aggregate investment figures belie a more nuanced set of developments. “Fintech” covers a range of different models. We see four distinct variants, each operating in different niches, with different modus operandi (Exhibit 2):
- Fintechs as new entrants, start-ups, and attackers looking to enter financial services using new approaches and technologies. These firms seek to build economic models similar to those of banks, often targeting a niche or particular product. The primary challenge for fintechs in this group is the cost of customer acquisition.
- Fintechs as incumbent financial institutions that are investing significantly in technology to improve performance, respond to competitive threats, and capture investment and partnership opportunities.
- Fintechs as ecosystems orchestrated by large technology companies which offer financial services both to enhance existing platforms (e.g., AliPay supporting Alibaba’s e-commerce offering) and to monetize current user data or relationships. Because of the very high level of engagement these technology platforms have with their users, they often have a tremendous customer acquisition cost advantage relative to other firms.
- Fintechs as infrastructure providers selling services to financial institutions to help them digitize their technology stacks and improve risk management and customer experience.
See: What fintech can learn from Robinhood’s ‘epic fail’ of launching checking accounts
We believe the future will develop in different ways for these varying types of fintechs, and that they will face very different hurdles. For instance, while infrastructure providers will often succeed or fail based on product or technical capabilities, consumer-oriented start-ups most commonly grapple with customer acquisition costs.
For incumbent financial institutions, the biggest hurdles relate to organization and skills as much as investing in technology at scale. Shifting traditional mindsets and operating models to deliver digital journeys at a start-up pace is no easy feat for a financial behemoth.
For established technology players entering the fintech ecosystem, regulatory challenges may prove a hurdle. The “move fast and break things” approach that disrupted the advertising industry is unlikely to be tolerated in financial services. And concerns about monopolistic behavior could well prevent Western tech giants from developing the sort of integrated financial services offerings we see from Ant Financial or Tencent in China.
To cut through the headlines and buzzwords that saturate the discussion of fintechs, we now take a closer look at current trends, and the implications for both incumbents and attackers.
TEN GLOBAL FINTECH TRENDS
1. High level of regional variation in fintech disruption
Winners in fintech are primarily emerging at a regional rather than global level, similar to traditional retail banking. Regulatory complexity within countries and across regions is contributing to regional “winner take most” outcomes for disrupters. Firms need to invest more in regional compliance rather than launching a global effort on day one.
For example, in money transfer, regulatory approval in a single EU country can be passported across the other EU countries. This encouraged many cross-border payments start-ups, such as WorldRemit and TransferWise in the UK, to expand into neighboring European countries before moving across the Atlantic, which requires additional regulatory investment. Individual US states require licenses for money transfer, which makes US expansion more cumbersome for European operators. This also explains why money-transfer operators in the US, such as Xoom and Remitly, were slower to come to Europe and are not yet operating in Asia as sending markets.
In China, where regulation has been more accommodating, ecosystems were formed by technology giants such as Ant Financial, which have directly entered and are reshaping many financial sectors including digital payments, loans, and wealth and asset management. In the US and Europe, which have stringent regulatory requirements and well-established banking offerings, efforts have been more fragmented and large technology players have been limited to payments offerings and some small-scale lending offerings.
See: UK banks publish fintech collaboration toolkit
As fintech markets mature, attackers that have established a regional presence are now eyeing international expansion. To successfully enter new markets, they must adapt to new sets of market dynamics and government regulations and select new markets based on a clear understanding of regional variations.
2. AI is a meaningful evolution, not a great leap forward for fintechs
The buzz surrounding artificial intelligence (AI) applications in fintech is intense, but to date few standalone use cases have been scaled and monetized. Rather, we see more advanced modeling techniques, such as machine learning, supplementing traditional analytics in fintech. While AI shows great promise, it is likely to be more of an evolution than a great leap forward into new data sources and methods.
For example, many credit underwriting attackers claim to use AI to analyze vast alternative data sources—ranging from mobile phone numbers to social media activity—but they have not yet displaced traditional credit underwriting methods. In many cases, traditional markers such as repayment history, are still better predictors of creditworthiness than social media behavior, particularly in markets where credit histories (and dedicated agencies to monitor them) are well established. As a result, while consumer lending platforms are increasingly incorporating iterative machine-learning approaches to steadily improve existing performance, they do not need to take a quantum leap in AI to do so.
At least in the short term, winners may not be characterized by completely new modeling approaches or the most complex algorithms, but by the ability to combine advanced analytics and distinctive data sources with their existing business fundamentals.
3. Good execution and solid business models can trump exotic technology
The most successful fintechs have evolved into execution machines that rapidly deliver innovative products, with dynamic digital marketing campaigns to match. Notably, winning start-ups often succeed without using completely new technology. Data-driven iteration, coupled with early and continuous user testing, has led to robust product-to-market fit for these firms.
While cutting-edge technology is exciting, it can also be complex; demand is also untested, which can result in long lead times with little opportunity to validate the business model. As an example, consider cross-border money transfer, a market that has traditionally been dominated by large incumbents such as Western Union. Despite much hype about fintech—particularly blockchain-based solutions—entering the space, no start-up has gained anywhere near the scale of TransferWise, a digital business built on top of traditional payments rails, rather than a reinvention using the latest tech. TransferWise used great user experience and distinctive marketing campaigns to grow rapidly, enabling it to successfully disrupt the space, and to report £117 million in revenues in March 2018.
See: While Canada debates, others are commercializing our most valuable asset: data
4. Scrutiny of business fundamentals is increasing as funding grows more selective
Years into the fintech boom, after many highs and lows, investors are becoming more selective. While overall funding remains at historically high levels, technology investors globally are increasingly investing in proven, later-stage companies that have shown promise in attaining meaningful scale and profits. Data compiled by PitchBook show that despite a clear increase in total VC funding, investments in early-stage fintechs decreased by more than half from a peak of more than 13,000 deals in 2014, to around 6,000 in 2017. The bar for funding is quickly rising, and companies with no clear path to monetization are going to have a harder time meeting it.
Indeed, several well-known and well-capitalized fintechs have yet to develop a sustainable business model and may need to find a path to more meaningful revenues quickly to continue to attract capital. This is especially evident for challenger digital banks. Some have raised significant sums but still struggle to monetize their products effectively; others have not yet delivered a current account product due to complications around licenses and regulations.
Customer adoption of truly innovative business models takes time, and smaller-scale attackers may require heavy infrastructure investments over a long period before revenues start coming in. Blockchain start-ups, for example, are attracting a significant amount of venture capital with radically new infrastructures for payments and other sectors. However, incumbents remain cautious, with blockchain remaining in prototype mode—and the leap to revenue-generation has yet to take place.
5. Great user experience is no longer enough
Back when banks had cumbersome websites that didn’t render on mobile, it was easy for fintechs to win over customers by building a half-decent app with a great user experience (UX). Today, most financial institutions have transformed their retail user experience, offering full mobile functionality with best-in-class design principles. Great UX is now the norm. Customers, as a result, require more reasons to switch to new fintech offerings.
Robinhood, a US-based stock-trading fintech, simplified stock trading by offering zero commissions through its easy-to-use mobile app with solid UX. But first, it built its user base with free product offerings. It initially made money by investing users’ cash balances. In late 2016, the company launched a successful premium offering called “Robinhood Gold,” which added charges for margin and out-of-hours trading.
See: Blockchain’s potential will continue to spur public and private investment
Simple interfaces, ease of use, and free stuff no longer equate to a viable business model. Attackers now need to find more robust ways to differentiate themselves from incumbents.
Continue to the full article --> here
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November 10, 2026 | Market Activity | Artificial Intelligence And Data, Capital Markets Infrastructure And Funding A Toronto Fintech Riskfuel Analytics Brings AI Pricing Into BBVA’s Global Markets Workflow On November 10, 2026, BBVA deployed Riskfuel Analytics' neural pricing technology inside the pre-trade structuring workflow for autocallable products on its ePricer platform. Riskfuel is a Toronto fintech founded in 2019 that builds AI models for derivatives pricing. BBVA is a global bank with a large corporate and investment banking business. The deployment puts Canadian built AI directly into the calculations used to design complex structured products at a major global bank. Riskfuel's model is trained on BBVA's own pricing engine and uses more than 4,000 market and product inputs. The company says the surrogate was tested against more than 100,000 trades and can evaluate thousands of candidate structures in under a minute. BBVA had already added AI generated investment ideas to ePricer in September. Riskfuel goes further into the workflow by speeding up the numerical pricing work while BBVA's own model remains the reference. How Riskfuel Speeds Up BBVA's Autocallable Pricing Autocallables can depend on volatility, interest rates, dividends, maturity, coupon levels and several barrier conditions. Autocallables are structured investments ...
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