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Artificial Intelligence in Banking: Polish Sector Leading the Way

TECHNOLOGYArtificial Intelligence in Banking: Polish Sector Leading the Way

Over the past few years, artificial intelligence has had a huge impact on the financial sector, particularly in banking. Banks in Poland, thanks to their openness and efficient implementation of AI, have become a benchmark for other sectors in terms of technological maturity and innovation. The industry continues to accelerate in this field. As the importance of data collection, processing, and segmentation continues to grow, technologies based on intelligent document processing and advanced machine learning models are also gaining popularity.

Solutions Tailored to Success

Although the financial industry is not typically the easiest for implementing innovations, the Polish banking sector continues to lead in this field. The main challenge is the rapid flow of large volumes of data, securing which is the top priority. Protection is needed not only for sensitive client data, but also for so-called dark data.

Artificial intelligence today plays a key role in structuring, categorising, and providing this data for analysis, compliance checks, and risk assessment. Innovative solutions based on machine learning, combined with Intelligent Document Processing (IDP) technology and integrated with other financial applications, such as ERP, CRM, BI, and SCM, through REST API interfaces, are now essential for document accuracy evaluation, workflow, and algorithms, and to reinforce the essential factor of security. Moreover, optimising time-consuming processes, such as customer data analysis, creditworthiness assessment or loan approval qualification, are among the guarantors of success for this type of business.

However, security concerns not just real-time actions, but also backup processes, which must be implemented to adequately secure data, prevent financial losses, and minimise potential operational downtime. Only knowledge of specific regulations and cooperation with specialised entities guarantee adequate preparation for such challenges. Therefore, thanks to aware practices and rapid implementation of appropriate steps, the Polish banking sector has become a reference point for other institutions, including foreign ones, in terms of technology use, as well as potential mapping and future applications.

Long-term collaboration of Iron Mountain with banks in Poland highlights the integration of technological innovation and foresight. By implementing advanced technologies, such as InSight Content Manager – supporting metadata and workflow management through artificial intelligence – and customising their strategies for operational efficiency, banks are paving the way for so-called business resilience in the rapidly changing financial landscape. An openness to innovative solutions makes the banking sector in Poland flexible, robust, and strategically prepared for the future. – Aaron Kalvani, Global AI Specialist & Business Transformation Leader

Digital Transformation: A Future-Oriented Approach

As indicated by the publication titled “2023 Banking Trends: A Perspective From Iron Mountain,” last year’s economic circumstances were not fully conducive to innovation. However, excessive caution carried the risk of falling behind, so banks did not give up deliberate development. The digitisation level of the Polish banking sector still exceeds the global average, and as many as six Polish banks are currently among the global digital leaders. Digitisation enables them to reduce dependence on paper documents, leading to greater transparency, significant cost savings, and increased efficiency.

According to a survey conducted by PMR, 81% of the surveyed financial institutions use cloud solutions, and 46% of the company’s resources are constantly stored in the cloud. Cloud-based IDP technology provides automated workflow and extracts valuable information from unconventional documents using machine learning and large language models (LLM). It reduces the workload of manual labour and facilitates informed decision-making by extracting valuable information from large data sets without human involvement. Combined with generative AI, it adds appropriate context to metadata. Actions must, however, all be safe and consistent with the banks’ strategic commitment to data security and compliance with regulations.

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