Low code and AI in banking: Driving innovation

Traditionally, banks have relied on complex monolithic systems and long development cycles. However, with the emergence of Low Code platforms powered by Artificial Intelligence, leaders across different areas can now create solutions aligned with market challenges.

Ilustración digital de un banco conectado a múltiples procesos con íconos de verificación, simbolizando control y cumplimiento en sistemas Low Code.

Use Cases in Business Areas

1. Customer Experience and Onboarding

Low Code platforms allow business teams to design and launch customer applications in weeks, not months. By integrating AI, these applications become smarter.

Virtual Assistants: Chatbots can be created using AI to respond to customer inquiries 24/7, reducing the load on customer service.
Digital Onboarding: AI can automate identity verification (OCR for documents, facial recognition) while the Low Code platform orchestrates the account opening workflow, making the process faster and less error-prone for the customer.

2. Risk Analysis and Fraud

Security and risk management are pillars of banking. Here, AI integrated into Low Code platforms offers immense value.

Fraud Detection: AI models can analyze thousands of transactions in real time to identify unusual patterns. Low Code handles creating the interface so analysts can visualize these alerts and manage cases efficiently, without the need for complex custom development.
Credit Analysis: Applications can be built to evaluate credit applications, where AI processes data from various sources to generate accurate risk scores, automating a significant part of the decision-making process.

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Low Code platforms backed by AI allow users to design application prototypes quickly and effectively, facilitating idea validation before full implementation. Harvard Business Review.

3. Internal Process and Operations Automation

In addition to customer-facing applications, the synergy between Low Code and AI is ideal for optimizing the back-office. Internal applications can be quickly created to manage complex workflows, such as loan approvals, claims management, or asset administration.

Intelligent Document Processing: AI can extract and classify information from financial documents (invoices, contracts, forms), while the Low Code platform orchestrates the workflow for review and approval by the human team. This significantly reduces errors and processing time.
Task and Approval Management: Approval workflows, often involving multiple departments, can be automated. AI can help prioritize tasks and assign cases to the most suitable employees, improving productivity and response speed.

Valuable Data for IT Leaders: Integrating Complex Systems

One of the biggest challenges in banking is modernizing operations without disrupting Legacy Systems, such as the CORE banking systems that support all transactions. They manage bank accounts, financial products, credits, loans, and payment processing. Their complexity lies in being difficult to manage while remaining vital for the business. This is why a solution like Low Code development is needed, allowing new layers to be built on top of these systems without dismantling them.

Low Code platforms, especially those with AI capabilities, are not intended to replace these systems but to act as an orchestration layer. They connect with CORE systems via APIs and microservices, allowing developers to create new applications and workflows on top of the existing data and business logic. This provides three key advantages:

Risk-Free Agility: Enables banks to innovate and launch new products quickly without touching the CORE systems, which are critical and hard to modify.
Gradual Modernization: Facilitates the creation of a modern architecture, decoupling the user experience from legacy systems.
Operational Efficiency: AI can optimize the orchestration of complex processes involving multiple internal and external systems, improving operational efficiency and reducing costs.

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According to a study by Gartner, 70% of new enterprise applications are being built with Low Code.

Conclusion

The combination of Low Code and AI is the approach the banking industry needs to bridge the gap between market demands and IT execution capacity. For business leaders, it means a faster path to innovation. For IT leaders, it represents a smart strategy to modernize infrastructure, protect investments in CORE systems, and focus their teams on other projects. It is the perfect synergy to build the future of banking in an agile and sustainable way.