Software Development for Finance - 7 Key Trends in 2024

AI-powered product personalization

AI-powered product personalization in the finance industry represents a revolutionary shift towards more customer-centric services and offerings. By leveraging artificial intelligence, financial institutions can now analyze vast amounts of data in real-time to understand individual customer behaviors, preferences, and needs.

This deep, data-driven insight enables banks, investment firms, and insurance companies, among others, to tailor their products and services to meet the unique requirements of each customer, enhancing satisfaction and engagement. Some examples of this at play include:

• Chatbots like Bank of America's 'Erica' use AI to provide personalized financial guidance, demonstrating the move towards more engaging and customized customer support.
• Platforms like the Cleo App analyze customer data to offer bespoke financial products and advice, catering to individual preferences and needs.
• Tools like Zbrain offer financial companies a way to provide AI-powered, target product recommendations.

Increased investments in IT security

In recent years, finance companies have been facing an escalating threat landscape that has significantly impacted their operations and customer trust. According to the Federal Trade Commission, US consumers reported losing more than $10 billion to fraud in 2023 - the first time that fraud losses have reached that benchmark. Similarly, the amount of fraud committed in the UK more than doubled to £2.3bn in 2023, marking the second-biggest year for scams in the last two decades

These financial crimes encompass a broad spectrum of illegal activities, including account creation and access fraud, investment fraud, business email compromise, and phishing, all of which have heavily targeted financial companies.

Consequently, there's been a pronounced shift toward bolstering IT security frameworks as part of the financial software development process in order to safeguard against these sophisticated threats. By integrating more robust security protocols into financial software, employing advanced fraud detection systems, and fostering greater awareness among consumers, financial institutions aim to mitigate the impact of these crimes and protect their customers from potential losses.

Open banking practices

Open banking practices are revolutionizing the financial industry by providing secure access to customers' financial data across traditional banks and other institutions through application programming interfaces (APIs). This approach not only empowers customers to have greater control over their data management but also facilitates a seamless integration of technologies into banking systems, enhancing process efficiencies.

Data from 2023 shows that total payments made via open banking have doubled. This uptick underscores a growing preference for making payments directly through third-party providers (TPPs), bypassing the need for cards and heralding a shift in consumer expectations towards open banking services.

In 2024, the focus on leveraging open interfaces and APIs is becoming increasingly important. Moving from "vertical" legacy technologies to "horizontal" thinking, financial IT teams are embracing open banking practices that facilitate partnerships and technology integrations.

Lending-as-a-service and embedded insurance

Outside of open banking, financial institutions are looking for ways to offer their customers a fully-integrated experience. One way we’re seeing this play out is through embedded offerings across ecommerce transactions.

Lending-as-a-service and embedded insurance are two such examples of this trend that we’re witnessing in 2024. Offering payment plans, lending options, and product-specific insurance within an ecommerce checkout experience provides customers with more frictionless financial transactions and also provides financial institutions additional revenue streams.

As this new model matures, we’ll likely see software development work around embedding other services, potentially including investment services, tax assistance, and personalized financial advice. This approach not only streamlines the user experience but also opens up new avenues for financial institutions to deepen customer engagement and diversify their offerings.

Adoption of real-time payment technologies

In an effort to meet the needs of consumers for instant, convenient access to financial services, we’re seeing a pivot towards the adoption of real-time payment technologies.Unlike traditional payment methods that rely on card networks or wire transfers, these real-time solutions offer immediate fund transfers, enhancing the user experience by providing both speed and security. Several regions and companies are at the forefront of this trend, showcasing the global momentum towards embracing real-time payments:

• BLIK in Poland: A pioneering system developed by Polish banks, BLIK allows users to make secure payments and money transfers instantly without the need for cards or wire transfers, directly through their mobile devices.
• RIX-INST in Scandinavia: Part of a broader European push towards instant payment systems, RIX-INST in Sweden represents the region's commitment to real-time payments, facilitating immediate transactions across the Scandinavian financial ecosystem.
• TIPS (TARGET Instant Payment Settlement) in the European Union: As a pan-European standard, TIPS supports instant money transfers between banks, streamlining transactions across the EU with speed and efficiency that traditional payment methods cannot match.

AI for improved customer experience

While one of the major applications of AI in the finance sector is to provide personalized experiences, more broadly, we’re also seeing companies leverage AI for improved customer experiences. AI-driven initiatives are transforming the way banks and financial institutions interact with their customers, ensuring more efficient, secure, and responsive operations

Some key examples of how we’re seeing this play out include:

• AI-powered chatbots and virtual assistants: These tools are revolutionizing customer service by providing 24/7 assistance, reducing response times, and offering instant solutions to common queries, allowing banks to manage a high volume of interactions efficiently.
• Predictive analytics for preemptive problem-solving: Banks use AI to anticipate potential issues, from system outages to unusual account activities that could indicate fraud, proactively addressing concerns to offer a more secure customer experience.
• Streamlining internal processes: AI technologies improve the efficiency of banking operations, including credit assessments and risk management, leading to reduced operational costs and faster services for customers, such as quicker loan approvals and more accurate investment advice.

Predictive analytics for better decision-making

In an era where 90% of the world's data was generated in the last two years, and data volumes double every two years, financial institutions face the monumental task of navigating through this deluge of information. Amidst this, predictive analytics emerges as a critical tool, transforming vast data into actionable insights for competitive advantage, strategic foresight, and enhanced decision-making.

In 2024 we’re seeing finance companies embrace predictive analytics, leveraging its power to address a multitude of critical areas, including:

• Stock price returns and volatility predictions are being utilized to enable informed investment decisions, maximizing returns and minimizing risks. This offers significant value through stable financial planning and effective portfolio management.
• Audit and compliance predictions help companies proactively identify potential regulatory issues, thus avoiding fines and reputational damage. This effort is crucial for securing investor confidence and ensuring market stability.
• Customer acquisition and attrition predictions are leveraged to optimize marketing and loyalty strategies. By improving customer retention and acquisition, companies directly impact revenue growth and expand their market share.
• Credit risk assessment and default predictions play a key role in informing lending decisions, setting appropriate interest rates, and mitigating potential losses. This is essential for maintaining a healthy credit portfolio and ensuring overall financial stability.