The financial sector is at a turning point! The pressure to innovate, provide faster and more personalized experiences to customers and, still, ensuring efficiency has never been so high. In this scenario, for companies that still maintain part of their operations in legacy technologies, cloud migration emerges as one of the main enablers for data integration, scalability of operations and is crucial for the adoption of artificial intelligence (AI). This process, however, brings significant challenges and continues to be one of the latent pains of institutions that were not born digital
By allowing companies to scale their operations and integrate large volumes of data, the cloud becomes the foundation on which AI solutions can be builtFor the granting of credit, for example, the analysis of customer behavior has become a crucial tool, enabled by access to massive real-time data. AI allows for pattern identification, anticipate risks and provide more assertive decisions. But, for that, it is essential that the data be accessible and organized in a flexible and scalable infrastructure, characteristics that the cloud offers in an adaptable way to each phase of the process, how model training and their operation.
The migration of legacy systems to the cloud, however, presents a series of obstacles. Many financial institutions, especially those with more traditional infrastructure, still operate on local systems developed in past decades. These, although robust for their original functions, they were not designed to handle the flexibility and connectivity required by modern platforms.
The restructuring for a cloud environment involves not only technological adjustments, but also a profound transformation in business processes, ensuring that the data migrates securely and that daily operations are not interrupted
Furthermore, the preparation of data for use in AI solutions requires more than just transferring it to the cloud. Legacy systems, many times, store information in a fragmented or hardly accessible way,what prevents the availability for an intelligent analysis. Data transformation, from rough to structured, requires a series of cleaning steps, normalization and standardization — and any failure in this process can compromise the effectiveness of AI algorithms
The competitive force of new digital institutions
For companies that were born in the digital environment and in the cloud, the scenario is quite different. Financial startups and fintechs, many times, they avoid the challenges faced by traditional banks, taking advantage of the benefits of a modern infrastructure from the beginning. These companies focus on using this infrastructure and AI models in their core strategy, as part of the core business and the value delivery they offer – what can often be linked to values such as agility and economy. Furthermore, the competitiveness of these institutions translates into a greater ability to offer personalized and innovative services, how predictive analysis for credit granting, with an efficiency that challenges the major players in the market
Traditional institutions, on the other hand, they have much larger amounts of data, that are not always accessible, but has the potential to underpin more robust analyses.
Although the complete migration to the cloud may seem like a monumental task for these large institutions, there are strategies that can facilitate this process in a more gradual and controlled way. Incremental approaches, how the modular modernization of legacy systems, allow companies to make updates in small steps, reducing the risk of critical failures and service interruptions. With each update, companies can test and adjust integration with new technologies , ensuring a smoother and more effective transition
These small-scale approaches consist of selecting critical business processes that can, potentially, to benefit from AI-based solutions, remodel them and keep them in parallel with traditional processes, so that both challenge each other and generate evidence about the viability and impact of the new solutions..
This method, besides being financially more viable, allows companies to maintain service continuity and protect data integrity. More important still, he creates a solid foundation for that, in the future, the company can take full advantage of the cloud and AI, without the pressure of a radical and immediate transformation. Implementing AI is not about making a revolution all at once.
Whether for traditional companies in the process of modernization or for digital startups, the migration to the cloud has ceased to be a trend and has become a practical requirement. Competitiveness in the financial sector, driven by Artificial Intelligence, depends directly on the ability to integrate and manage large-scale data, with efficiency and safety. Ignoring this change can limit innovation potential and restrict growth in an increasingly digital and competitive environment
