Data first: starting with the fundamentals the key to your technology stack

You’ve probably had technology companies or consultants reach out to you to talk about transformation. Offering AI-powered analytics, automated client engagement platforms, or sophisticated portfolio management tools. Each vendor offers compelling demonstrations of what their software can achieve. What these demonstrations rarely show is the quality of data required to deliver those outcomes. The uncomfortable truth confronting many practices is that their existing data would sabotage any new system before it generated a single insight.

The 2024 Australian Financial Advice Landscape Report from Adviser Ratings found that practices implementing technology are achieving meaningful efficiency gains, with many reporting reduced reliance on traditional paraplanner support. Yet these gains flow to practices whose foundational data can support sophisticated tools. For practices with fragmented, outdated, or inconsistent client records, adding new technology simply automates existing problems at greater speed and scale.

Before investing in the next platform, the highest-return project for most practices is the unglamorous work of data remediation.

The hidden cost of poor data

Data quality problems rarely announce themselves dramatically. They accumulate quietly: a client’s address updated in one system but not another, employment details unchanged since onboarding five years ago, beneficiary information reflecting a family structure that no longer exists. Individually, each gap seems minor. Collectively, they undermine every process that depends on accurate information.

ASIC’s Report 627: Financial advice: What consumers really think highlighted that half of advised clients have gaps in clarity around what their fees are paying for. Part of this disconnect stems from practices themselves lacking clear, current pictures of their clients. Personalised communication becomes impossible when the underlying data cannot support it. Segmentation strategies fail when client categories rest on outdated assumptions.

The compliance implications compound the service failures. Advisers relying on inaccurate data for best interest assessments or ongoing fee arrangements expose themselves to regulatory risk that no technology can mitigate.

Auditing what you actually have

Effective data remediation begins with honest assessment. Most practices overestimate their data quality because they interact daily with their best-maintained records while problematic files sit undisturbed.

Start by defining what complete, current data looks like for your practice. This typically includes accurate contact details, current employment and income information, up-to-date family circumstances, valid identification documents, current risk profiles, and accurate product holdings. Create a simple checklist representing your minimum standard.

Then apply that checklist systematically across your entire client base. The results often prove sobering. Practices undertaking this exercise frequently discover that fewer than half their client records meet basic completeness standards. Records for clients in lower service tiers, inherited from previous advisers, or onboarded before current systems were implemented tend to show the greatest deficiencies.

Quantify the gap. Knowing that 60 per cent of client records lack current employment information or that 40 per cent have outdated beneficiary details provides the foundation for remediation planning.

Prioritising the cleanup

Complete remediation across every client record simultaneously is neither practical nor necessary. Effective practices prioritise based on relationship value and compliance risk.

Begin with clients in active service agreements. These relationships generate ongoing fees and carry corresponding obligations. Ensuring their records meet current standards addresses both service quality and regulatory requirements.

Next, address records with specific compliance sensitivities: clients approaching retirement, those with complex family structures, or anyone whose circumstances have likely changed materially since last contact. The Financial Advice Association Australia’s Value of Advice research demonstrates that clients value advice most during transitions. Accurate data enables practices to identify and respond to these moments.

Finally, develop a sustainable process for maintaining quality over time. Data degrades constantly as clients change jobs, move homes, experience family changes, and adjust their financial circumstances. Without systematic refresh processes, today’s cleanup becomes tomorrow’s legacy problem.

Turning remediation into relationship building

The data cleanup process, approached thoughtfully, offers unexpected client engagement opportunities. Rather than treating remediation as back-office administration, practices can frame it as demonstrating ongoing commitment to personalised service.

A phone call to verify details becomes an opportunity to understand current concerns. A request to update beneficiary information opens conversations about estate planning. An employment verification might reveal a promotion, redundancy, or career change warranting advice review.

Some practices structure annual data verification into their service calendar, normalising the expectation that information stays current. Others embed verification into every client interaction, confirming key details as a standard meeting component.

The channel matters less than the consistency. Clients who understand that their adviser maintains accurate, current records develop confidence that advice reflects their actual circumstances rather than outdated assumptions.

Building the foundation for technology value

Clean data transforms technology from expensive overhead into genuine competitive advantage. Client segmentation becomes meaningful when categories reflect current reality. Automated communications land appropriately when contact preferences and personal circumstances are accurate. Analytics generate actionable insights when the underlying information is reliable.

Practices that sequence their technology investments wisely, addressing data quality before adding sophisticated tools, consistently report stronger returns than those seduced by feature demonstrations built on idealised datasets.

The most advanced AI cannot compensate for a client record still listing an employer from three jobs ago or a risk profile completed before the client inherited substantial assets. Technology amplifies what already exists. Amplifying quality produces value; amplifying mess produces faster, more expensive mess.

Nicholas Way

Nicholas Way is a contributing editor at The Inside Adviser and has covered business, retirement, politics, human resources and personal investment over a 50-year career.