How Financial Firms Are Gaining a Competitive Edge with Low-Code and AI

Low-code platforms and AI are transforming financial services by cutting costs, speeding up development, and improving customer experiences. Here's how financial institutions are leveraging these technologies to stay competitive:

• Low-Code Benefits: Speeds up app development by up to 7x, reduces costs, and improves back-office efficiency. For example, ABN AMRO cut development resources by 20-40% across 60+ apps.

• AI in Action: AI enhances customer service with 24/7 support, fraud prevention, and personalized financial recommendations. Cybercrime costs are projected to hit $10.5 trillion annually by 2025, making AI-driven security critical.

• Combined Power: Financial firms integrate AI within low-code platforms for smarter apps and real-time risk analysis, enabling faster product launches and better compliance.

Key Stats:

• 97% of finance leaders say low-code exceeds expectations in speed and cost efficiency.

• Open banking adoption surged to 64 million users, a 70% jump beyond forecasts.

Why It Matters: With legacy systems holding firms back, low-code and AI provide the tools to modernize, improve customer experiences, and strengthen security - all while reducing development time and costs.

Low-Code Platforms in Financial Operations

Core Functions and Features

Low-code platforms simplify financial operations by using visual development tools and pre-built components. They handle common workflows with features like automated code generation, drag-and-drop design, and strong security measures to support regulatory compliance.

Here’s what their technology stack typically includes:

These tools significantly enhance back-office operations, making processes faster and more efficient.

Back-Office Process Examples

Financial institutions use low-code platforms to improve back-office processes, achieving measurable results. For instance, the Development Bank of Canada implemented a core lending system in just eight months - a project that would typically take 2.5 years.

Another example comes from ING's Document & Content Services department. They automated over 2,200 tests for their outbound customer communication system. As Ed Spitteler, Expertise Lead Outbound Communication at ING, explains:

"We can say that the app is not just running, it is functionally working. We do this by automatically running a series of test scripts every four hours."
– Ed Spitteler, ING

These examples highlight how low-code platforms can be tailored to streamline specific internal processes.

Results from a Bank's Implementation

The impact of low-code platforms is clear in how they help financial firms become more agile and competitive. ABN AMRO, for example, used low-code to address inefficiencies in their shadow IT systems. Mark Bus, Product Owner of Rapid Application Development, shared:

"The second mode was where we didn't have an explicit strategy yet, which was leading to this huge portfolio of shadow IT applications. We decided to expedite our search, and it quickly became clear that low-code was the answer we were looking for."

Coast2Coast Mortgage also showcases the versatility of low-code. Their platform integrates with QuickBooks for invoice management and connects directly with their loan origination system, making sales and commission tracking much smoother.

AI Applications in Customer Service

24/7 Customer Support Systems

Financial institutions are revolutionizing customer service with AI-driven support tools that work nonstop. These systems manage routine questions and transactions, ensuring quick responses and consistent service quality.

AI phone agents bring several benefits to financial operations:

In the mortgage sector, AI agents interact with prospects as soon as their contact details are received. They conduct initial qualification calls, handle document collection, and ensure timely follow-ups on loan applications and document requests.

Custom Financial Recommendations

AI systems analyze spending habits and financial behaviors to provide tailored recommendations. By processing large volumes of data, these tools identify trends, investment opportunities, and risks. This allows financial institutions to offer customized product suggestions and proactive financial advice, helping them stand out in a competitive market.

AI-Based Security Systems

Financial institutions are leveraging advanced AI technologies to safeguard customer assets and data. These systems add multiple layers of protection:

1. Transaction Monitoring

AI continuously reviews account activities to spot unusual patterns, such as unexpected large withdrawals or international transactions. This is crucial, as cybercrime costs the global economy $600 billion annually, or 0.8% of global GDP.

2. Fraud Prevention

AI creates detailed profiles of customer purchasing behavior and flags activities that deviate from these norms. This is especially important as fraud attempts increased by 149% in early 2021 compared to the previous year.

3. Identity Protection

AI tools authenticate signatures, detect forgeries, and identify synthetic identity fraud in credit and loan applications. By 2022, over half of financial institutions had adopted AI-based fraud detection systems.

To strengthen security further, organizations can:

• Create cross-functional fraud management teams

• Regularly update AI systems with fresh data

• Implement multi-factor authentication

• Promote a security-focused workplace culture

These AI-powered measures help financial institutions reduce average annual revenue losses of 5% due to fraud, all while maintaining a smooth customer experience.

Digital Innovation In Financial Services With Low-Code No ...

Combined Low-Code and AI Solutions

Financial institutions are now combining low-code platforms with AI to stay ahead in a competitive landscape. By blending the efficiency of low-code tools with the precision of AI, these integrated solutions are reshaping the financial sector.

AI Tools in Low-Code Systems

Banks and financial organizations are using low-code platforms with built-in AI tools to create smarter, data-driven applications. These platforms connect directly to powerful AI services, speeding up the creation of advanced financial solutions.

Here are some AI-powered features found in modern low-code platforms:

For example, PostNL uses machine learning within a low-code platform to manage 1.5 million daily delivery requests. They achieve sub-millisecond response times while safeguarding data privacy through on-premise deployment.

Risk Analysis Applications

AI-powered risk management tools are revolutionizing how financial institutions assess and address risks. These systems analyze massive datasets in real time, providing actionable insights and alerts. Key benefits include:

• Real-time Credit Risk Alerts: AI models keep track of bankruptcy risks, credit scores, and changes in payment behavior.

• Automated Transaction Monitoring: Systems detect suspicious activities like money laundering by analyzing transaction patterns, while also reducing false positives.

• Precise Customer Segmentation: AI creates detailed risk categories, enabling personalized pricing based on individual risk profiles.

This advanced risk analysis helps financial institutions roll out new fintech products with greater confidence.

Fintech Product Launch Example

Coast2Coast Mortgage offers a great example of how AI and low-code can work together. They developed an automated sales and commission tracking system with seamless API integration, improving operational efficiency.

Another example is Regions Bank, which introduced a cloud-based document management system that includes:

• Automated workflows for data collection

• Secure document sharing

• Digital signature capabilities

• Smart management for document expiration

These examples highlight how combining low-code and AI allows financial institutions to build secure, efficient systems while adhering to regulatory requirements.

Setup Guide and Problem-Solving

Implementation Steps

Financial organizations need a clear plan to successfully implement low-code and AI solutions. Here's a step-by-step guide based on industry best practices:

1. Assessment and Planning
   

   Start by auditing your IT infrastructure to find areas where low-code can make an immediate impact. Launching smaller pilot projects is a smart way to build confidence and show quick results.

2. Technology Selection
   

   Select platforms that meet key requirements like:

   • End-to-end encryption

   • Proper data segregation

   • Compliance with regulations

   • Compatibility with existing systems

   • Ability to scale as your needs grow

3. Team Alignment
   

   Engage both technical and business teams early in the process. This ensures that the solutions are not only technically sound but also aligned with business goals and compliance needs.

Common Problems and Solutions

When integrating low-code and AI systems, financial institutions often encounter specific challenges. Here's a breakdown of common issues and practical solutions:

These challenges can be addressed through focused problem-solving strategies, as demonstrated by leading organizations in the industry.

"This technology makes you as smart as the smartest person in the organization. Each client is different, and AI helps us cater to each client's unique needs." - Jeff McMillan, Head of Firmwide AI at Morgan Stanley

Next 5 Years in Finance Tech

With current challenges being tackled, financial institutions must prepare for the changes coming to the industry. The financial technology landscape is evolving rapidly. According to McKinsey Global Institute, generative AI alone could add $200 billion to $340 billion annually to the banking sector.

Building on the progress from low-code and AI adoption, here are some key trends to watch:

1. Enhanced Customer Experience
   

   AI will enable large-scale personalization, providing tailored services to customers.

2. Regulatory Changes
   

   Banks should brace for stricter regulations focusing on transparency, privacy, fairness in decision-making, and model interpretability.

3. Faster Automation
   

   Areas like fraud detection, portfolio management, risk assessment, and customer service will see even greater automation powered by AI.

To thrive in this evolving landscape, organizations should focus on transparency and effectively communicate how AI-driven automation boosts both productivity and employee satisfaction.

Conclusion

The financial services industry is undergoing a major shift as low-code platforms and AI redefine how businesses compete. Companies adopting these technologies report impressive results, including reducing customer acquisition costs by up to 50% and increasing revenue by 15% through hyper-personalized services.

Research highlights that 97% of financial decision-makers believe low-code platforms offer unmatched speed and cost savings. Additionally, modern systems have driven core banking costs to be nearly 10 times lower than those of outdated legacy systems.

To stay ahead, financial institutions should prioritize these three areas:

1. Improving Customer Experience
   

   Automation and generative AI could add $200 billion to $340 billion annually by boosting productivity and enhancing customer service.

2. Upgrading Core Systems
   Embracing digital transformation is crucial. For example, Goldman Sachs saw a 20% increase in developer productivity after using generative AI tools.

3. Strengthening Security and Compliance
   

   With cybercrime expected to reach $10.5 trillion annually by 2025, investing in strong security measures and risk management is essential.

Real-world examples underline the benefits of these technologies. Western Union used low-code platforms to launch digital banking services in two countries within 11 months. Similarly, Wells Fargo’s AI-powered Fargo™ virtual assistant now handles over 20 million customer interactions each year.

These success stories show how low-code and AI can transform operations and deliver measurable results. As JPMorgan Chase CEO Jamie Dimon puts it:

"The future belongs to those who can rise above the technology and master it."

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