FinTech adoption and AI maturity drive better corporate financial outcomes

FinTech and artificial intelligence (AI) are improving financial performance among publicly listed firms, but their full value depends on how well companies detect and interpret technological opportunities, claims a new study published in FinTech.

The study, titled “Examining the Impact of FinTech and Artificial Intelligence on Financial Performance: The Moderating Role of Dynamic Capabilities,” is based on data from 384 senior executives, chief financial officers, financial support managers and board members of firms listed on the Tehran Stock Exchange. The research finds that both FinTech and AI have positive and statistically significant effects on corporate financial performance, while dynamic capabilities mainly matter by strengthening the impact of FinTech rather than directly improving performance.

FinTech and AI emerge as direct drivers of financial performance

The study examines digital finance in an emerging-market setting where economic volatility, weak transparency, institutional uncertainty and uneven technology infrastructure can determine whether firms turn innovation into financial gains. The authors argue that while earlier research has often focused on developed economies, less is known about whether FinTech and AI generate similar financial gains in markets such as Iran.

The research focuses on companies listed on the Tehran Stock Exchange and uses a descriptive-correlational design. Data were collected through structured questionnaires and analyzed using partial least squares structural equation modeling. The sample included respondents from major sectors including petrochemicals, basic metals, pharmaceuticals, food, automotive, information technology and cement. The study examined the direct effects of FinTech and AI on financial performance and tested whether dynamic capabilities change the strength of the FinTech-performance relationship.

The findings show that AI has a strong positive effect on financial performance. The path from AI to financial performance was statistically significant, supporting the view that AI improves firm outcomes by raising decision quality, strengthening risk management, reducing uncertainty and improving operational efficiency. The authors frame AI as a technological capability that helps firms analyze data, automate processes, improve transparency and support more informed financial decisions.

FinTech also showed a positive and statistically significant effect on financial performance. The study defines FinTech as the use of digital technologies in financial services and financial processes, including tools that improve transaction management, financial data use, service delivery, risk handling and operational efficiency. The findings suggest that firms adopting FinTech are better positioned to reduce transaction costs, improve access to timely financial information, increase transparency and support long-term value creation.

The results support the broader argument that digital transformation is no longer optional for firms seeking competitive advantage. In financial systems, AI and FinTech can alter how firms manage data, allocate resources, evaluate risks, interact with capital markets and make strategic decisions. The study shows that these tools are not only technical upgrades but strategic resources that can influence profitability, return on investment, market share and competitive position.

However, the research also makes an important distinction between technology adoption and technology value. It shows that simply investing in FinTech or AI does not automatically guarantee stronger performance. The benefits depend on whether firms can identify useful opportunities, align digital tools with business needs and manage implementation under economic and regulatory uncertainty.

In Iran’s capital market, firms face exchange-rate volatility, inflation, regulatory frictions and structural uncertainty. In such conditions, the value of technology depends not just on adoption but on strategic timing and organizational readiness. A digital tool can improve performance when deployed with clear insight, but it can become costly or ineffective when used without a strong understanding of the surrounding environment.

Dynamic capabilities matter, but not all dimensions work the same way

The study examines dynamic capabilities - the higher-order organizational abilities that help firms identify changes, seize opportunities and reconfigure resources in response to shifting conditions. In digital transformation, these capabilities determine whether firms can convert technological resources into measurable financial gains.

The study divides dynamic capabilities into three dimensions: sensing, seizing and reconfiguring. Sensing refers to the ability to monitor technological trends, understand customer needs, interpret market shifts and detect regulatory or competitive changes. Seizing refers to the ability to allocate resources, make strategic investments and turn opportunities into new products, services or business models. Reconfiguring refers to the ability to redesign structures, processes and resources to adapt to changing environments.

Dynamic capabilities did not have a statistically significant direct effect on financial performance. This means that the mere presence of such capabilities does not automatically raise financial outcomes. Instead, their importance appears through interaction with FinTech. Dynamic capabilities significantly moderated the relationship between FinTech and financial performance, showing that they help firms turn FinTech adoption into financial value.

A more detailed analysis revealed that only sensing capability had a positive and statistically significant moderating effect on the FinTech-performance relationship. Firms that are better at identifying digital opportunities, tracking regulatory changes and interpreting market signals appear more capable of gaining financial benefits from FinTech. In other words, companies that see technological and market shifts earlier are better able to direct FinTech investment toward financially productive uses.

Seizing and reconfiguring did not show significant positive moderating effects. This finding is important because it challenges the assumption that all dynamic capabilities strengthen digital transformation in the same way. The study suggests that in Iran’s institutional and economic context, the ability to understand and anticipate change may matter more than rapid execution or organizational restructuring.

The results also show that seizing capability had a direct negative and statistically significant effect on financial performance. The authors interpret this as a warning against fast or excessive exploitation of digital opportunities without enough environmental understanding. In volatile markets, rapid FinTech expansion, premature technology investment or aggressive resource allocation may raise costs, increase risk and weaken short-term financial efficiency.

For managers, the study suggests that firms should not treat digital transformation as a race to implement every available technology. Instead, they need stronger sensing systems before they commit major capital to FinTech projects. Without strong sensing capability, firms may misread market signals, invest in poorly suited tools or pursue digital strategies that do not fit regulatory and economic realities.

In an uncertain environment, the first advantage belongs to firms that can read change accurately. They can identify which FinTech tools are worth adopting, when to invest, how to align resources and which risks to avoid.

Digital investment needs strategy, timing and organizational readiness

The study offers practical lessons for corporate leaders, investors and policymakers. It shows that AI and FinTech can improve financial performance, but the gains depend on the organizational systems surrounding them. Firms need not only digital tools but also the ability to interpret technological and market signals with speed and accuracy.

For managers, the clearest recommendation is to strengthen sensing capability. This means investing in data analytics, regulatory monitoring, market intelligence, competitor tracking and continuous assessment of technological trends. The authors suggest that companies should develop structures capable of monitoring developments in FinTech, AI and capital-market regulation and linking these insights to investment and resource-allocation decisions.

Such capabilities are especially valuable in emerging markets, where regulatory shifts and economic shocks can quickly change the return on digital investments. A FinTech project that appears promising under one set of rules or market conditions may become costly under another. Strong sensing capability helps firms avoid impulsive investment and improve the timing of digital initiatives.

The study also recommends a phased and flexible approach to digital transformation. Firms should avoid rushing into FinTech projects without clear alignment between technological tools, business strategy, internal capacity and market conditions. A learning-oriented approach can reduce sunk costs and allow firms to adjust digital projects as new information becomes available.

For policymakers and financial regulators, the findings highlight the importance of stable and clear digital finance rules. Regulatory uncertainty can reduce the value of FinTech investment by making implementation costly and risky. Clearer frameworks for digital banking, payments, data governance and AI use could help firms convert technological investment into financial performance.

The study treats AI not as a broad label but as a measurable organizational capability involving infrastructure, data, skills, budget, strategy and the ability to use AI effectively in decision-making. This approach helps explain why some firms gain more from AI than others. Technology alone is not enough; firms also need training, software and hardware infrastructure, available data, financial resources and a clear understanding of where AI can be applied.

The research relies on cross-sectional survey data, which means it captures relationships at one point in time and cannot fully assess long-term causality or the gradual development of organizational capabilities. Financial performance was measured through managerial perceptions, which may introduce response bias. The study also focuses only on Iran’s capital market, so comparisons with other emerging economies would be useful.