Key Evidence

Financial institutions face structural and financial barriers to digital transformation.

Many financial institutions struggle to modernize due to high costs, legacy systems, and competing priorities that limit investment in innovation. These structural constraints slow the adoption of new technologies and reduce institutions’ ability to keep pace with growing demand for digital financial services.

• Since the global financial crisis, banks have deprioritized digital innovation, focusing instead on regulatory compliance and repairing balance sheets. As a result, they have struggled to meet the rising demand for digital services, creating space for fintechs and big techs to lead the delivery of modern financial solutions. (Liu, 2021)
• A 2025 survey of financial services providers found that many institutions face budget constraints that limit their ability to leverage technology effectively. As a result, they struggle to optimize digital tools and support customer adoption, particularly among women, who may have limited access to digital financial services. (Women’s World Banking, 2025)

Gaps in technical capacity and organizational readiness hinder effective use of technology.

Institutions often lack the skilled staff, data systems, and internal alignment needed to leverage technology effectively. Organizational resistance to change and weak data infrastructure further limit the ability to design, deliver, and scale customer-centered digital solutions.

• Many microfinance institutions still operate on outdated, low-tech models with heavy reliance on manual processes, limiting their ability to scale and digitize. Poorly organized customer data further hampers efforts to adopt digital solutions and personalize services. To remain competitive, these institutions must modernize their systems and leverage data more effectively for digital transformation. (Accion, 2021) 

Emerging technologies create both opportunities and risks without adequate capacity and oversight.

While technologies like AI and advanced analytics offer potential to improve services and efficiency, many institutions lack the expertise and governance frameworks needed to deploy them responsibly. Without intentional safeguards, adoption can introduce new risks, including poor decision-making, bias, and weakened consumer protection.

• The integration of AI technologies, such as machine learning, natural language processing, generative AI (GenAI), and advanced data analytics, offers financial institutions powerful tools to optimize operations, improve customer experiences, design innovative products, and strengthen risk management. However, without adequate expertise, institutions and regulators risk relying too heavily on algorithmic outputs without applying critical human oversight. This can undermine consumer protection and increase systemic vulnerabilities, particularly if biases, errors, or opaque decision-making processes within AI systems go unchecked. (CGAP, 2025)
• One study finds that women-centric projects led by the ten largest FSPs in a country are more likely to succeed, likely due to their stronger capacity, better infrastructure, skilled staff, and greater resources to invest in and deploy technology. (Women’s World Banking, 2025)