The cost of an erroneous report can include damage to a firm's credibility since it reveals deficiencies and inadequacies, eroding the trust that underlies client relationships, Private Client Resources writes.

Here is a guest article from Private Client Resources, which provides RIAs, family offices and private
banks with outsourced reporting solutions and integrated technology. Family Wealth Report is pleased to share these insights and welcomes any reader responses.

As a private wealth manager, you rely heavily on performance
reports that demonstrate the value of your advice and service to your clients.
Yet with so much of your credibility and the ultimate value of your services riding
on the quality of these reports, what steps are you taking to ensure the
accuracy of the data?

If you are like many private wealth managers, you simply
assume that your reports are being created in a standard way and with the
highest level of data accuracy. The problem with this assumption: there is no
industry standard regarding processing procedures or even requiring a minimum
level of data accuracy. It is up to each reporting firm to determine its own
standard for accuracy.

Accuracy takes work

“Perfection is our goal,” says Robert Fiore, president and chief
executive of Private Client Resources, the Connecticut-based private wealth
reporting firm. But according to the company’s measurement standards, even PCR
falls a little shy of accuracy perfection, though by less than a rounding
error.

PCR performs
more than 100 data quality assurance checks daily and follows procedures that
identify and address any incidences of inaccuracy. The firm views every error it catches as
an opportunity to develop a new procedure to keep that specific error from ever
recurring. It’s an approach that has led us to achieve what we believe is an
industry-leading accuracy standard of 99.7 per cent and counting.

The more data used in a calculation, the higher the
likelihood that the data file will contain erroneously entered numbers. In
fact, 90 per cent of all Excel spreadsheets with more than 150 rows of formulae
contain material errors (source: Society of Actuaries CompAct Electronic
Newsletter, January 2011, Issue 38)

Why superior accuracy
matters

Reporting inaccuracy doesn’t just compromise the integrity
of your decision-making or impact how your fees are calculated. Productivity is
lost to correcting the resulting errors. The cost of an erroneous report can
also include damage to your credibility since it reveals deficiencies and
inadequacies, which will erode the trust that underlies your client
relationships.

If you are not receiving accurate data, you are not going to
be able to deliver what your clients need and expect from you. Not knowing the
level of data quality creates exposure to risk that can put more than your
relationships on the line. It can quickly erode your reputation and impact your
business.

Indeed, 16 per cent of client relationship management time
is lost on administration and error resolution (source: New Era: Redefining
Ways to Deliver Trusted Advice, Global Private Banking and Wealth Management
Survey, PriceWaterhouseCoopers, 2009).

This is why it is so important that you start asking more
questions about the accuracy levels of your reports and how that accuracy is
achieved. You have too much riding on the quality of your private wealth
reporting capabilities to rely on unquestioned assumptions.

Six measures of accuracy

The elimination of data inaccuracy requires that your
reporting firm be managed with a focus on quality. That means it should employ
the following procedures when processing your reports:

- If it isn’t measured, it can’t be managed. All elements of
the quality assurance program must be measured and managed.

- Data should be collected directly from the source. Each
data source has unique policies and data conveyance procedures. Having a direct
relationship leads to a quicker response time when questions arise and helps
resolve issues before they become problems. The direct line of communication
also facilitates the realization of more consistent results.

- Root cause analysis should be used when issues arise. In
order to prevent a data issue from recurring, a firm needs to focus on
understanding what caused that issue in the first place. Companies that embrace
learning and then adapt better training policies and procedures, and regularly
update technology are better positioned to deliver higher levels of accuracy.

- Preventative measures are the best defense. Quality
assurance procedures and processes need to be incorporated at every data
interaction point. This means establishing practices that yield predictable
results in every interaction with data from access, extraction, and capture, to
reviewing and reporting. If an unpredictable result is produced it needs to be
investigated and resolved immediately.

- Consistency in all practices is key. All interactions need
to be consistently executed by the same people. A strong sense of familiarity
is needed by the individuals who interact with the data and make decisions
about it.

- Responsibility and accountability lead to improved
accuracy. Eliminating inaccuracy is a team goal. However, errors are typically
created or caused by individuals. Therefore, people should be assigned to, and
encouraged to, own every data interaction point. By assuming such
accountability, they are better positioned to achieve a standard of performance
and learn from any mistakes they make.