Technological Challenges and Trends in the Modern Financial Sector

The path to digital transformation and innovation isn’t a one-size-fits-all in the financial services industry, given its diverse needs, offerings and customer bases. Despite differences between financial institutions, most of them are looking into data management, cloud governance and artificial intelligence (AI) to increase the competitiveness of their offering and improve data quality. These solutions also help meet rising customer expectations as customers now expect faster services, personalized recommendations and full control over their finances – on any device, at any time.

According to KPMG research, 86% of American banking executives think that AI adoption will enable banks to gain a competitive edge over those organizations that don’t embrace this technology. But adopting new digital solutions requires financial services companies to address internal and external obstacles that slow down their technological development. Read this article to explore key implementation challenges in the financial services industry and discover top technological trends that are making waves in this sector.

Challenges of implementing new technologies in the financial services industry

Data and information silos

Data is the top driver of any AI or data engineering project. Though financial institutions have access to a wide range of information, they rarely utilize their full business potential because data is often stored in separate systems, which discourages effective communication between departments. These data silos are a particularly common problem in organizations with complex structures where centralized data management didn’t prove successful.

Information silos make it difficult to get a full picture of the customer, analyze trends or make data-driven business decisions. To successfully overcome this issue, banks and other financial companies need to find a data management process that is tailored to their unique organizational structure and the products they offer.

Data governance

Without mature practices and proactive data management, many financial services businesse, might struggle with adapting to new regulations, such as the AI Act. However, companies that have already implemented data governance strategies and stay on top of their data governance policies usually find it easier to adjust their processes, achieve regulatory compliance and stay competitive in their markets.

Cybersecurity and auditability

Financial institutions are prime targets for cyberattacks because they store highly sensitive data and move massive amounts of money. At the same time, regulatory pressure is increasing. Banks must now comply with evolving global standards like the Digital Operational Resilience Act (DORA) in the EU and NIST Cybersecurity Framework 2.0 in the U.S., while also staying ahead of cyber threats.

What’s more, auditability – being able to track and explain every action taken by a system, algorithm or process – is no longer optional. Whether it’s a rejected loan decision or a flagged fraud alert, regulators and customers expect full transparency and traceability. Balancing compliance, transparency and security requires financial services companies to turn to modern technologies and solutions, including zero-trust architectures, real-time monitoring, secure multi-cloud governance and AI-powered threat detection.

Trends and technologies that financial services businesses are currently implementing

Technological foundations for cloud transformations

Cloud governance

As the financial services industry expands their cloud usage, cloud governance has become mission critical. Cloud migration and cloud-based solutions need to be developed responsibly, securely and in alignment with regulatory and business goals. Financial institutions often operate across multi-cloud and hybrid environments, which means they need to comply with both local and international laws. Effective cloud governance ensures consistent policy enforcement, role-based access control and visibility across the tech stack. It’s especially important for global banking groups, where subsidiaries must adapt to parent-level cloud strategies without compromising local compliance.

Cloud infrastructure security

With cyber threats growing in frequency and sophistication, securing cloud environments is a top priority. According to IBM’s 2024 Cost of a Data Breach report, the average breach in the financial industry costs $6.08 million, making proactive cloud security not just a necessity but a strategic investment. To keep their cloud infrastructure safe, financial organizations usually look into encryption, identity and access management, intrusion detection and automated compliance checks. The challenge is compounded by the dynamic nature of cloud resources and constantly rising number of new virtual machines, containers and serverless components. To stay protected, financial services companies are adopting zero-trust models, AI-powered threat detection and continuous monitoring tools.

Application migrations

Migrating applications to the cloud helps financial institutions improve performance, lower operational costs and simplify application management. Some businesses begin with lift-and-shift migrations, where legacy applications are moved as-is to virtual servers. Others also invest in cloud-native refactoring in which you redesign apps to fully take advantage of scalable architecture, microservices and event-driven design. Refactored services also integrate better with AI tools, analytics and third-party ecosystems.

Real-time solutions

Banks are increasingly turning to real-time technologies to deliver fast, accurate, and responsive services. These solutions enable financial services companies to meet customer expectations and retain users as consumers expect faster transfers, instant approvals and immediate support.

One standout example is real-time credit scoring. Using machine learning, financial institutions can now assess a borrower’s risk and make lending decisions in seconds – a process that used to take hours or days. This speed not only improves customer satisfaction but also gives banks a competitive edge.

Cloud cost optimization

Running a cloud environment at scale can be expensive, if not managed well. That’s why cloud cost optimization is now a core part of IT strategies. Financial institutions are leveraging tools like automated workload scheduling, right-sizing instances and reserved capacity planning to cut down unnecessary spending. Much of cloud spending is wasted due to underutilized or forgotten resources. Financial organizations that adopt smart governance and observability tools can reduce costs while maintaining agility and uptime.

Smart digital banking and personalization

AI-based recommendations

Financial organizations can use AI-driven recommendation systems to offer the right products to the right people at the right time. These systems analyze a customer’s behavior, transaction history and financial goals to suggest tailored offerings like a savings account, investment product or credit option. It’s the same kind of personalization customers expect from companies like Netflix or Amazon. Better personalization can lead to increased customer satisfaction, more sales conversions and long-term loyalty.

AI-supported fraud detection

Fraud detection is another major area that can be strengthened by combining AI and real-time solutions. With financial fraud becoming more sophisticated and automated, financial services companies need to detect and stop suspicious activity the moment it happens. AI-powered systems can help analyze transactions as they occur, flagging anomalies and preventing fraud before it affects customers.

Embedded lending and Buy Now, Pay Later (BNPL)

The rise of embedded finance has made it easier than ever for banks to offer instant lending solutions – from traditional loans to BNPL options – right inside digital platforms. These services are now being directly integrated with ecommerce checkouts, digital wallets and mobile apps. Customers can access short-term credit with just a few clicks, while banks use AI and real-time data to evaluate creditworthiness on the spot. This shift is helping traditional financial institutions compete with fintech disruptors, especially among younger, mobile-first consumers.

Smarter search engines and credit integration

Many markets are seeing the rising popularity of search engine–based financial tools that offer credit suggestions within shopping or search experiences. For example, customers searching for a product may receive personalized loan or financing options based on their browsing behavior and pre-approved status. This level of integration merges banking with daily digital life, turning every search or scroll into a potential financial touchpoint. As ecommerce grows, these types of data-powered integrations are expected to become more common, giving banks new channels to engage users and offer value-added services.

Data as a competitive advantage

Data management

To compete in today’s digital market, financial organizations need a single, unified view of the customer. That’s where 360-degree customer view systems come in. By pulling together data from multiple sources – transactions, credit history, support interactions and even third-party services – these platforms give banks a real-time, holistic understanding of each client. This empowers finance companies to improve various processes, from product recommendations to fraud detection and risk assessment. More importantly, it breaks down internal silos and creates a shared source of truth across departments.

AI-powered data monitoring and governance

Beyond customer-facing tools, AI can also support internal system monitoring and infrastructure management. Predictive AI models can spot patterns in application usage, network behavior or compliance logs, enabling businesses to proactively adjust cloud governance policies before issues arise. For example, if an AI model detects unusual data flow between departments, it can trigger a review of access rights or security protocols. This kind of intelligent automation helps financial services companies stay compliant and resilient while reducing manual workload and response time.

New digital solutions in financial services require the right skills

From breaking down data silos to building AI-driven platforms and securing cloud infrastructure, the financial services industry is undergoing a rapid transformation. However, according to a survey conducted by Accenture, 20% of banking executives report that a lack of skills or talent poses an obstacle to adopting digital core technologies. A combination of domain knowledge, technological expertise and deep business understanding is key to effective financial software development.

That’s why financial services companies often look to software development companies like Software Mind to boost their engineering and deliver innovative financial systems. At Software Mind, we partner with technological leaders – such as Amazon Web Services, Google Cloud Platform, Microsoft, ServiceNow, Backbase, Snowflake and IBM – to enable comprehensive system integrations that enhance financial software with various functionalities, from AI-driven analysis to improved governance and compliance. If you’d like to learn how our software experts can help you speed up your digital transformation and build user-friendly solutions, get in touch via this contact form.