Smart Compliance: Automating Data Classification and Lifecycle Management in Financial Services

2025 is a crucial year for Australia’s financial services industry, as the industry faces ever sophisticated cyberthreats and more rigid regulatory mandates. The Australian Prudential Regulation Authority (APRA) reflects this urgency, committing AU$73.2 million in additional funding over four years to upgrade cybersecurity, data, supervision, and technology systems. The aim is to support data-driven supervision, enabling entities to submit information more easily to APRA and fortify internal cyber controls.  

Amid these strategic shifts in regulatory expectations, APRA’s CPS 234 – Information Security emerges as a key compliance mandate for banks, insurers, and superannuation funds, reinforcing the need for proactive information security and governance.

This evolution reflects a broader commitment to safeguarding sensitive data and ensuring operational resilience as generative AI (GenAI) and AI agents continue to make waves in a tech-driven environment. Yet, many financial organisations still rely on manual data classification and retention processes, which keep them struggling to keep pace with the scale, speed, and complexity required to meet standards like CPS 234. These approaches often result in inconsistent data handling, increased risk exposure, and operational inefficiencies. 

AI-powered automation offers a smarter, more scalable approach to addressing these issues — one that enables precise data classification, retention, and disposal of sensitive content while also meeting compliance standards and reducing risk.

The Compliance Imperative in Australia’s Financial Sector

Australia’s financial services industry operates in a strictly regulated environment. CPS 234 requires regulated entities to maintain all information security capabilities that are appropriate to their size and complexity of operations. It also requires timely incident reporting and clear accountability for data governance.

As a result, these organisations are obliged to have visibility and control over vast volumes of sensitive financial data: This means information spread across different cloud platforms, a number of legacy systems, and third-party vendors.  

The staggering volume of data generated across financial systems presents a growing challenge. Still, many financial organisations rely on manual classification and retention policies that are not only difficult to enforce consistently but also leave them vulnerable to risks.

Non-compliance with APRA’s CPS 234 can result in the following: 

• Regulatory penalties: Enforcement actions, financial sanctions, and increased supervisory oversight that can strain resources and limit business operations
• Reputational damage: Loss of customer trust and market confidence, potentially affecting client retention and new business acquisition opportunities

• Operational disruption: Mandatory system remediation, business restrictions, and diverted resources that impact day-to-day operations and strategic initiatives 

The risks are real and rising. Financial organisations must shift from reactive compliance to intelligent automation — driving not just efficiency, but resilience, trust, and long-term sustainability across Australia’s financial ecosystem.

Automating Data Classification with AI for Accuracy and Scale

AI is transforming how financial institutions manage information, driving efficiency and insight across payment transactions and customer data. However, effectively harnessing AI requires accurate, clean, and well-governed data. 

Automated data classification leverages AI to identify and label sensitive information based on its content, context, and usage patterns, eliminating any guesswork or inconsistency that results from having to manually tag each piece of content. This also ensures that data is handled appropriately from the moment it enters the organisation’s digital environment.

Think about AI’s capability to detect personally identifiable information (PII), financial records, or even confidential communications across email, files, or collaboration platforms. Following detection, AI can then apply the correct retention policies or access controls automatically.

Automated data classification delivers far-reaching benefits, improving compliance and operational resilience while freeing teams to focus on strategic initiatives rather than manual audit reporting.

Industry priorities make it clear that this shift is non-negotiable: In 2025, 72% of CFOs in financial services confirm that analytics, metrics, and reportings are top priorities, with automation emerging as a key driver of smarter, more strategic growth.

The AvePoint Confidence Platform supports this shift through comprehensive data security posture management (DSPM) capabilities that provide continuous visibility into sensitive data across your entire digital estate. By offering intelligent classification capabilities that integrate seamlessly with Microsoft 365, Google Workspace, and Salesforce, the platform enables organisations to not only discover and classify sensitive data but also monitor its security posture in real-time — creating the foundation for robust reporting and proactive risk management.

In the case of a financial organisation, the AvePoint Confidence Platform can seamlessly apply sensitivity labels to client investment reports stored in SharePoint. Leveraging Microsoft sensitivity labels in the financial services industry supports several areas of compliance, risk mitigation, and governance: 

• Enabling regulatory compliance at scale. Sensitivity labels help financial institutions meet Payment Card Industry Data Security Standard (PCI-DSS) and APRA CPS 234 requirements by automating classification, encryption, and access controls.
• Mitigating data breach risks. Clear labelling of confidential information (personally identifiable information or PII, financial reports, trading strategies) reduces accidental exposure and malicious exfiltration risks, particularly in hybrid work environments.
• Empowering secure collaboration. Labels enable secure document sharing through enforced policies like read-only access, watermarking, and auto-expiry without disrupting productivity.
• Driving data governance and visibility. Labels provide visibility into data usage and sharing, enabling better governance, auditing, and incident response for high-value financial data assets.
• Supporting zero trust architecture. Seamless integration with Microsoft Purview and Defender enables context-aware protection, ensuring only authorized personnel access sensitive financial data under appropriate conditions.  

Lifecycle Management for Risk Reduction and Regulatory Alignment

Once data is accurately classified, effective lifecycle management becomes essential to ensure ongoing compliance and risk reduction.

As AI-enhanced cyberattacks continue to evolve and regulatory demands shift, one thing remains certain: Financial organisations must prioritise effective data lifecycle management — not only to reduce risk, but to exceed baseline compliance and build long-term resilience. CPS 234 expects organisations to manage data throughout every phase of its lifecycle, from creation and active use to archiving and defensible disposal.

When organisations forgo automation, data lifecycle policies are often applied inconsistently, leading to data sprawl, rising storage costs, and increased vulnerability to breaches. Without proper oversight, orphaned accounts, outdated records, and redundant information can quickly become operational and compliance liabilities.

In contrast, AI-powered lifecycle management tools can automatically enforce retention schedules, archive inactive data, and dispose of information that no longer serves a business need or meets regulatory purposes. This supports defensible deletion and ensures that sensitive data is not retained a moment longer than absolutely necessary.

The AvePoint Confidence Platform offers lifecycle management capabilities that help financial institutions automate retention and disposal across cloud environments.

Consider a superannuation fund, which could use the AvePoint Confidence Platform to identify and archive inactive OneDrive accounts belonging to former employees, guaranteeing that sensitive data is not left unmanaged while also reducing unneeded storage costs.

The Risk Posture Command Center in the AvePoint Confidence Platform also provides visibility into vulnerable assets, empowering teams to proactively address ransomware risks and compliance gaps well before they escalate.

In Australia’s financial services industry, a bank could use this dashboard to consistently monitor its exposure across collaboration tools, effectively flagging shared documents containing client account details that lack sufficient encryption or access controls. 

Smart Compliance: Charting a New Chapter for Financial Services

As the Australian financial services industry continues to evolve, so must its approach to compliance. Manual processes are no longer sufficient to meet the demands of CPS 234 or to protect sensitive data in a fast-moving digital landscape.

For financial institutions exploring how to modernise their compliance posture, the AvePoint Confidence Platform provides a comprehensive foundation for smart compliance — combining automation, visibility, and governance to help financial organisations stay ahead of regulatory expectations and digital transformation goals.

AI-powered automation offers a smarter, more resilient path forward. Whether it’s automating retention policies for client communications or gaining comprehensive insights into data risk, the AvePoint Confidence Platform empowers teams to take control of their information lifecycle with confidence.