Banks of every size wrestle with data modernization, quality, and compliance challenges. However, unlike their larger contemporaries, mid-tier banks face significant budget and resource constraints while navigating the same regulatory scrutiny and obligations. These burdens will only increase as emerging new and stricter regulations complicate data rationalization, governance and AI needs.

Where exactly are mid-tier banks struggling, and what’s the best path forward?

Infrastructure Limitations

Mid-sized banks are held up by legacy, closed systems that inhibit agility and scale. Transitioning from these legacy infrastructures to cloud-based platforms or data models is important for modern data demands but requires significant technology and talent investments.

Mid-tier banks usually lack the in-house resources to support emerging data management strategies such as data lakes, real-time analytics, and integration with third-party apps. Cloud adoption, for example, is especially difficult for smaller banking organizations when facing vendor lock-in, compliance challenges, and the high costs of transitioning to a cloud-based environment.

Data Governance and Reasoning Gaps

Data governance is a daunting mid-tier bank challenge. There are a host of regulations across the globe – including GDPR, PSD3, and the Bank of International Settlements’ BCBS 239 – that require strong data governance platforms to achieve compliance. Unfortunately, mid-level banks don’t have robust organizational frameworks that ensure data quality, consistency, and availability for reliable governance and compliance.

Data rationalization (i.e., getting rid of duplicate, out-of-date data) introduces more problems. Rationalization can reveal problems with how data is gathered and stored. Without effective governance, it’s almost impossible to avoid the penalties of non-compliance that come with data that is not managed in a correct and traceable manner.

Missing Out on AI’s Potential

Artificial intelligence provides a tremendous opportunity for banks to enable better decisions, enhanced customer experiences, and reduced operational cost. But AI can be heavily constrained in mid-market banks due to resource scarcity. Where big banks have access to in-house AI talent and scale to experiment, mid-size banks are left relying on outside suppliers or ready-made tools that aren’t entirely equipped to tackle their specific challenges.

Every AI-based system requires high-quality data. With existing governance and data management challenges, it’s hard for these banks to deliver what AI needs to be effective. Then there are the ethical and compliance issues to consider related to implied discrimination or data privacy and security violations that can come with mismanaged AI, which mid-tier banks aren’t well positioned to address.

Risk and Liability in the Face of Global Laws

A top three headache for middle-level banks is risk management and compliance. These institutions must follow both local and constantly evolving sets of complex international regulations, from AML and Know Your Customer requirements to the adherence to foreign banking regulations.

Compared to international banks with entire departments dedicated to compliance and risk, mid-market banks can only afford small groups, forcing them to prioritize some regulations over others. This increases exposure to risk, where deficiencies in compliance systems could slip through the cracks, leading to costly fines and negative reputational impacts.

The Compounding Effect of Limited Resources

Lack of budget puts mid-market banks in a bind, facing a choice between continuing investment in legacy solutions, or in AI and data modernization, or in robust governance and compliance systems.

Talent attraction and retention issues exacerbate the situation. Lower and mid-market banks don’t have the same types of compensation packages or growth paths as larger banks, and struggle to attract the kind of talent they need to upgrade data systems. Lack of competent people to do data engineering, AI and regulatory compliance also limits flexibility in which issues they can address at any one time.

Overcoming The Obstacles

Mid-tier banks need to strategically modernize their data and governance frameworks to handle regulatory pressures and evolving security threats. A strong option for many is adopting low-cost, scalable solutions in the form of closed-source data platforms designed for compliance. These platforms offer robust controls that align with regulatory standards while providing cost efficiency, flexibility, and scalability – crucial for banks operating within budget constraints. Choosing a compliance-focused vendor who also offers the option of a Data-as-a-Service (DaaS) or fully managed solution through a partner can further support these banks, helping to balance modernization with budget limitations.

Integrating AI-driven tools within closed-source environments can enhance risk management and streamline compliance. Tailored AI solutions, designed for the specific regulatory and operational needs of mid-tier banks, offer critical insights by identifying transaction patterns and pinpointing potential compliance risks. This approach significantly reduces the burden on smaller compliance teams by automating routine checks and flagging anomalies without the need for broad, generalized AI models.

Standing at the Corner of Data, AI and Compliance

Mid-tier banks have hit a data management dead end. There are large demands on time to modernize data centers, drive strict governance, leverage AI, and manage risk in a world where everyone is looking to be compliant.

For sustained success in a heavily regulated, data-centric world, mid-tier banks should take a measured, resource-conscious approach to modernization. By choosing technology partners who deliver compliance-ready, closed-source solutions and fostering a culture focused on data governance and agility, these banks can address regulatory demands efficiently, innovate responsibly, and stay competitive in a rapidly shifting market.

Learn more about how Pentaho is uniquely positioned to help mid-tier banks solve their data governance, quality, and compliance challenges here or request a demo.