Financial institutions face growing pressure to comply with evolving regulations, defend against cybersecurity threats, and adopt AI-driven financial services. Compliance today requires continuous monitoring, automated controls, and real-time auditability—all while maintaining scalable data access and efficient decision-making.

Yet many financial teams still rely on fragmented compliance workflows and manual governance processes, creating bottlenecks and increasing regulatory risk. When AI is layered onto broken processes, it doesn’t solve governance issues—it amplifies them. Without strong data lineage, access controls, and automated monitoring, financial institutions risk regulatory fines, operational inefficiencies, and lost customer trust.

If these challenges sound familiar, you're not alone. On April 9, 2025, join us at the Data Leaders Forum, a virtual event for data and finance leaders focused on the future of governance. In our session, Smarter Governance for the Future of Finance, industry experts will share how they’re strengthening compliance, automating risk management, and unlocking new opportunities through modern data governance strategies.

🔗 Register Now

Key challenges for financial data teams

Financial organizations must navigate complex regulations while ensuring that governance processes are scalable, efficient, and adaptable to evolving business needs.

1. The rising costs of fragmented compliance

Many financial institutions rely on disconnected compliance frameworks spread across multiple tools and departments. Without automation and centralization, these fragmented approaches drive up costs, increase regulatory risk, and make it harder to maintain oversight.

2. Audit readiness in a real-time data environment

Regulators now expect immediate access to audit trails, making manual reporting processes impractical. Without automated data lineage and real-time reporting, financial institutions face compliance gaps that can lead to regulatory penalties and operational delays.

3. Aligning risk, compliance, and innovation teams

Risk and compliance teams often operate separately from product and engineering groups, creating silos that slow down decision-making. A disjointed approach to governance makes it harder to balance regulatory requirements with financial innovation and business growth.

4. Managing sensitive PII across expanding fintech ecosystems

The growing volume of digital banking, AI-driven credit models, and embedded finance has dramatically increased the volume of personally identifiable information (PII) and financial transaction data being processed. To meet privacy regulations and mitigate security risks, financial firms must implement automated PII classification and enforce strict access controls.

Gaps in traditional governance models

Many financial institutions rely on legacy governance frameworks that struggle to keep pace with evolving compliance demands. These frameworks were designed for periodic compliance reviews, not the real-time regulatory scrutiny financial institutions face today. As financial services become more data-driven, these outdated models create significant operational risks:

• Reactive compliance instead of proactive oversight – Traditional governance relies on periodic audits and after-the-fact reporting, making it difficult to detect and mitigate risks in real time. Regulators now expect continuous monitoring, which many financial institutions struggle to implement.
• Siloed governance responsibilities – Compliance, risk, and IT teams often manage governance separately, leading to inconsistent controls and oversight gaps. Without a unified framework, financial institutions lack a clear, end-to-end view of data governance and security.
• Lack of control over sensitive data – PII and financial transaction data are often stored in unstructured, ungoverned locations like email threads, spreadsheets, and chat platforms. Traditional governance models lack the automation needed to classify, track, and secure this data at scale.

As regulatory expectations evolve, financial organizations must move beyond fragmented, manual governance approaches and adopt automated, integrated frameworks that provide real-time compliance visibility and risk mitigation.

Building a scalable, compliance-ready governance framework

Financial institutions that go beyond checkbox compliance and implement integrated, proactive governance models achieve stronger risk mitigation and operational efficiency. The key is automating governance processes to ensure compliance without slowing down financial operations or innovation.

Automating data lineage and risk monitoring

Manual tracking of financial data movement is no longer sustainable. Leading institutions are adopting automated data lineage solutions to provide real-time oversight and ensure compliance at scale:

• Audit readiness – Instant visibility into how financial data is created, transformed, and used, making it easier to respond to regulatory inquiries.
• Fraud detection – Automated anomaly detection helps flag irregular transaction patterns and potential security threats in real time.
• Regulatory compliance – End-to-end tracking of sensitive data ensures it remains protected throughout its lifecycle, reducing the risk of fines or breaches.

Why financial data teams are turning to centralized data catalogs

A well-structured data catalog is essential for maintaining governance at scale, enforcing policies, and reducing compliance workload. Key capabilities include:

• Scalability – Supports high transaction volumes without disrupting performance.
• Comprehensive metadata management – Ensures clear data ownership, lineage tracking, and regulatory reporting.
• Automated PII detection and classification – Flags sensitive financial data and applies access controls based on regulatory requirements.
• Seamless integration with financial systems – Connects with banking, risk management, and analytics platforms to maintain a unified governance framework.
• Automated documentation and policy enforcement – Reduces manual compliance work by ensuring policies are consistently applied across data assets.

Without a centralized data catalog, compliance efforts become fragmented and high-risk—an unsustainable approach in today’s regulatory environment. Financial institutions must leverage automation and integrated governance frameworks to stay ahead of evolving compliance demands.

Case study: Paystack’s data governance transformation

Paystack, a fintech company processing over half of Nigeria’s online transactions, faced mounting governance challenges as it scaled.

The challenge

• Data documentation was scattered across Google Sheets, Notion, and Slack, making governance time-consuming and error-prone.
• PII classification relied on manual workflows, increasing compliance risks.
• High transaction volumes required a scalable approach to tracking data movement.

The solution

By centralizing governance with Secoda, Paystack achieved:

• 80% reduction in manual data compliance tasks.
• Automated data lineage tracking to assess risk before changes were made.
• Self-service governance tools for over 100 data users.
• Faster onboarding, reducing time for new team members from 3 months to a few days.

"Secoda opened up a new world to us in terms of data lineage. Now, we can instantly know the upstream and downstream impacts of a potential change."

This transformation enabled Paystack to comply with financial regulations while maintaining the agility needed to scale.

Key takeaways for financial data teams

• Fragmented compliance workflows drive up costs and regulatory risk. Financial institutions need integrated governance solutions to ensure efficient, scalable compliance.
• Automated governance reduces manual effort and improves oversight. By streamlining compliance tasks, teams can focus on strategic initiatives rather than regulatory firefighting.
• Self-service data governance improves collaboration. Enabling risk, compliance, and business teams to access and manage data securely reduces friction and increases efficiency.
• Proactive compliance is replacing reactive audits. Leading financial organizations are shifting from periodic compliance checks to continuous monitoring and automated risk detection.

Why finance professionals should attend our forum

This panel at the Data Leaders Forum will bring together industry leaders to discuss:

• How top financial institutions are reducing compliance risk through automated, real-time governance.
• The shift from reactive to proactive compliance models that help institutions scale.
• Practical strategies for integrating governance with data management and analytics.
• Case studies from fintech leaders on how governance is driving both compliance and business growth.

The cost of disjointed compliance and governance

Many financial organizations manage compliance through a patchwork of tools and processes, creating operational inefficiencies and increasing regulatory risk. Instead of preventing issues, fragmented governance often delays the detection of data quality and security problems, leaving institutions vulnerable to costly fines and reputational damage.

Regulatory fines and legal consequences

The financial sector operates under an expanding set of data privacy and security regulations, requiring institutions to maintain strict data controls and auditability. Key regulations include:

• GDPR (Europe): Mandates secure storage and timely deletion of customer data.
  
  • Example: A leading bank in Denmark was fined over €1 million for failing to remove outdated customer records.
• Sarbanes-Oxley Act (SOX) (US): Requires financial institutions to enforce strict financial reporting controls and maintain audit trails.
• Gramm-Leach-Bliley Act (GLBA) (US): Governs the protection of customer financial data.
• 23 NYCRR 500 (New York): Establishes cybersecurity requirements for financial institutions operating in the state.
• Industry Standards: Compliance with PCI DSS (payment security), SOC 1 (financial reporting), and ISO 27001 (information security management) is critical for maintaining trust and regulatory approval.

Failure to detect risk: The Wells Fargo scandal

Weak governance played a central role in one of the most significant financial scandals of the past decade. In 2016, Wells Fargo was exposed for creating millions of fraudulent accounts due to lax internal monitoring:

• Transaction patterns went unchecked, allowing the fraud to persist for years.
• Internal governance controls failed to flag anomalies.
• The bank ultimately faced $3 billion in fines, widespread leadership turnover, and long-term reputational damage.

Had real-time anomaly detection and stronger governance controls been in place, these irregularities could have been flagged much earlier—potentially preventing the crisis altogether.

Take action now

If your financial institution is struggling with data governance costs, regulatory pressure, or inefficient compliance workflows, this panel is a must-attend.

Learn from fintech leaders from ID.me and Alegeus about scalable governance solutions that reduce compliance overhead while enabling innovation.

Register Now for the Data Leaders Forum