Poor Data Infrastructure Undermines Banks AI Profitability Drive—Report

As banks in Nigeria and across the African continent accelerate investments in artificial intelligence (AI) to enhance operations and improve customer experience, experts have warned that such investments may fail to deliver meaningful returns unless they are built on strong and reliable data foundations.

The warning comes amid growing adoption of AI technologies across the financial services sector, with banks deploying solutions for fraud detection, credit scoring, customer service automation and operational efficiency.

According to a report published by core banking technology provider Oradian in its white paper, “The Digital-First Bank’s Guide to AI in 2026,” the success of AI initiatives depends largely on the quality and accessibility of the data that powers them.

Furthermore, it noted that as much as 95 per cent of AI projects undertaken by banks fail because institutions do not prioritise the critical role of data infrastructure.

The report observed that while banks worldwide are committing billions of dollars to AI development, many institutions continue to struggle with fragmented databases, poor data governance and inadequate digital core systems, factors that ultimately limit the effectiveness of AI applications.

While it’s recognised that AI has the potential to transform banking operations through faster decision-making, improved customer engagement, automated processes and enhanced risk management.

However, experts stressed that these benefits can only be realised when financial institutions establish a solid digital foundation capable of supporting advanced analytics and machine learning systems.

According to the report, global banking institutions are projected to invest about $97 billion in AI infrastructure by 2027 as they seek to harness emerging technologies to drive innovation and competitiveness. Just as the anticipated benefits include lower operating costs, improved productivity, faster service delivery and stronger profitability.

However, experts warned that heavy spending on AI without corresponding investments in data quality, integration and governance could amount to a costly misallocation of resources.

The white paper stated that, “Every AI initiative stands on the shoulders of data. The quality and accessibility of data can make or break an AI project.”

Analysts further argued that the challenge facing many banks is not a lack of enthusiasm for AI adoption but weaknesses in execution and foundational infrastructure. They noted that institutions that successfully integrate AI are often those that first modernise their core banking systems, establish robust data management frameworks and ensure seamless access to accurate customer and operational data.

Hence, for Nigeria’s banking industry, the warning comes at a time when lenders are increasingly embracing digital transformation strategies to remain competitive in a rapidly evolving financial landscape.

Meanwhile, experts say banks that focus on strengthening their data ecosystems alongside AI investments will be better positioned to unlock sustainable value from emerging technologies and improve long-term profitability.