The standard required for data accuracy has never been higher, says Steph Willcox – Head Actuary at Dynamic Planner. The question is, what can paraplanners do to ensure that recommendations become stronger and clients have better opportunities for good outcomes?
Whenever new FCA guidance notes are published, there’s almost always the same issue: too many firms give advice on information that is incomplete, unverified or simply out of date. In its review of retirement income advice, the regulator identified “firms relying on information without considering accuracy” as its first key finding, emphasising that financial planning is impossible without reliable data.
With Consumer Duty raising expectations around evidencing suitability, demonstrating value, and avoiding foreseeable harm, the standard required for data accuracy has never been higher. But improving data quality doesn’t have to mean adding friction to the advice process. With the right systems, habits and workflows, paraplanners can strengthen the foundations of every recommendation without slowing anything down.
1.Fact-finding is more than just collection
The FCA is clear that paraplanners must not accept client-provided information at face value if it appears inconsistent or incomplete. This means it’s important to not only collect data, but also to interrogate it. A robust process might include:
- Ensuring all income sources are captured, using structured prompts or checklists.
- Comparing expenditure against external benchmarks, such as the PLSA Retirement Living Standards, to spot unrealistic expenditure.
- Validating income vs expenditure, so that any expected surpluses in month to month banking can be evidenced. If these surpluses do not really exist then incomes or expenditures may be incorrect.
- Verifying valuations rather than relying on manual inputs taken from memory.
The goal is not to distrust clients, but to ensure that the financial picture being modelled is complete enough to support suitable advice
2. Set a minimum standard
Every “TBC”, “approx.” or “client unsure” weakens the integrity of a cash flow model. But too often, we accept estimated values because the pressure to keep cases moving is real.
A stronger approach is to adopt a minimum data threshold. This is a set of criteria below which a case simply cannot progress into modelling. This is likely to be firm specific but could include:
- Up‑to‑date investment valuations within the last three months.
- Clear breakdown of contributions and employer matching.
- Confirmed debt levels and interest rates.
- Accurate details of protection premiums and cover levels.
If essential items are missing, the case can be paused until the information is obtained, rather than moving on and having to rework the whole process later
3. Use automation to remove human error
Manual transcribing, copy‑pasting and switching between systems are some of the biggest sources of data faults. Now that most advice firms use a multi‑system tech stack, paraplanners should aim for a “touch once” approach where data flows from capture to cash flow with as few manual interventions as possible.
As AI continues to advance, this is where technology can shine, by removing any of the manual re-keying of data
4. Create a data hygiene cycle
Data accuracy is not a one‑off event and client information degrades faster than most firms realise.
Ideally, firms should include a cyclical data hygiene process, which might include:
- Quarterly reviews of client portfolios for valuation drift.
- Annual refreshes of income, expenditure, protection cover and risk profiling.
- Trigger‑based reviews (for example, following a platform migration or corporate action).
- Automated alerts for valuations older than a set threshold.
These cycles not only keep models up to date but create a clear audit trail showing that the firm actively monitors accuracy, and therefore demonstrating a key part of Consumer Duty
5. Document assumptions
Even with excellent data, cash flow modelling always involves assumptions. The FCA’s guidance emphasises the need for a “reasonable and justifiable basis” for all rates and inputs.
Paraplanners should therefore document:
- Why particular growth rates were chosen (or supporting documentation if the growth rates are set by a third party).
- How inflation assumptions align with firm standards.
- Any assumptions made due to missing data.
- Any stress‑testing scenarios applied.
Clear documentation not only protects the firm but makes future case reviews far easier.
Conclusion
Consumer Duty has reshaped expectations for data quality in financial planning. For paraplanners, this is a chance to redefine what “good” looks like: fewer estimates, cleaner integrations, structured verification, and a proactive approach to data maintenance. When the foundations are solid, every recommendation becomes stronger, and every client has better opportunities for good outcomes.
Main image: velizar-ivanov-wT_eP8BVA0I-unsplash
