Bank smarter, build faster – with AI and low-code

Artificial Intelligence (AI) innovations are increasingly becoming a matter of industry import, touching upon various sectors across the globe. This power transformation is quintessential in financial services, where low-code/no-code platforms blooming with AI provide for more innovation, efficient operations, and improved customer experience.

Essentially, low-code/no-code platforms design, deploy, and manage applications with little hand-coding, or the so-called democratization of development. On top of this, they can kick the old-school application development into overdrive. AI systems then go to work on the big data, churning out real-time insights to aid decision-making. Correspondingly, putting AI-led analytics in place would hasten customization of service to customer requirements and develop engagement. Theft and other fraudulent activities aside, mundane processes-free setup by AI cut down human errors and smooth internal processes.

Market growth and potential

In uttering the current banking shift, AI being incorporated fine into low-code/no-code platforms has become very central nowadays. The numerical aspect proves that the potentialities of the global low-code development platforms are real. The market clocked a value of USD 28.75 billion last year. Looking ahead, it shall witness a rocket climb from USD 37.39 billion in 2025 to USD 264.40 billion by 2032, at a CAGR of 32.2% within the forecast period. In such a shift, the financial institutions shall benefit from the use of AI-backed low-code/no-code platforms, such as into the domains where AI algorithms could analyze transaction patterns to suspect fraud activities, thus enhancing security protocols; assess creditworthiness and process loan application automatically, thus reducing turnaround time; and also automate the generation of compliance reports, thus guaranteeing regulatory adherence. This trend is further emphasized in a report by CITI, showing that the global banking domain would reap profits by USD 170 billion or so, 9% till 2028 under the impression of AI potential.

The key advantages for financial institutions

In line with the embrace of these revolutionary technologies, it may be argued that faster adoption to market changes and customer demands may be achieved with agile development approaches. By way of analogy, operational costs could go down as well with reallocation of resources happening in financial services. Even non-technical staff might actually be in the application development arena, creating a culture of creation and innovation. This would be improved upon with the ability to smoothly and proportionally increase production with the scaling of operations.

Marrying AI with no or low code will foster a plethora of innovative areas targeted at the reshaping of financial services. These may include hyperautomation with AI, robotic process automation, and low-code development teaming up for end-to-end process automation. Generative AI integration may soon become the highest trend, with low-code platforms introducing this capability to help in code generation, chatbot creation, and report summarization with minimal input from developers. The rise of “citizen developers”—business users without professional coding knowledge—is yet another encouraging interdisciplinary innovation within banks. Predictive analytics, smart recommendations, and real-time anomaly detection are various AI-powered features finding their way into low-code environments, thereby accelerating the delivery of next-gen solutions.

The rough periods along the way

Even with such great opportunities, not without snags goes the adoption of AI-driven low-code/no-code platforms. Management of sensitive financial data calls for strict guarantees. Thus, in accordance with such laws, AI models must comply. Designing and regulating AI systems poorly could cause biases and discriminatory practices in credit scoring or fraud detection. Low-code platforms enable secure development, but maybe technical advances are required so that it may be scaled into enterprise-wide solutions. Since low-code platforms are reducing dependence on traditional coding and fund managers, they must now have human resources capable in AI ethics, model validation, and oversight.

In short, AI integration into low-code/no-code platforms is shaping banking operations into a distinctive avenue for innovation, efficiency, and being customer-centric. As these financial institutions keep exploring these technologies, the future of banking readily bears the transference into smart and agile services.

Author: Lalit Mehta, Co-Founder & CEO- Decimal