How social science can help you make a success of RDR

With RDR implementation now little more than a year away, Chris Davies, author of Winning Client Trust, explains how social science can help advisers profit from the changes.

As we are now staring down the barrel at RDR implementation, the 1 January 2013 – or ‘R’ day as it has now been renamed – continues to throw up much industry noise 
and debate.

Issues such as the RDR’s intended/unintended consequences, the ramifications of adviser charging and customer paid remuneration (CPR), business models, CRM systems, taxation and MiFIDII create endless curiosity and suspicion. Indeed in the past 24 months we have seen some 1,544 pages released from the FSA on its intentions for the RDR implementation.

White noise

The widely disparate views such cogitation brings can at times be as useful as sitting in front of the television and watching the white noise. We can become confused, disengaged, alarmist and misled by misinformation and thus take actions that may not necessarily be beneficial for our RDR journey, businesses or clients or do nothing at all.

During my 21 years spent within financial services, one of the key areas that remains an elephant in most boardrooms and needs to be addressed as an essential business strategy, is that of the cause and effect of behaviour. By this, I mean a focus on actions of intent and their consequences institutions take when met with regulatory directives, how communication skills and emotional intelligence fit; and indeed why behavioural economics need to be not only understood but explored and applied to business models to ensure both the business and their clients are aligned and fully engaged.

Social science

Firstly, the reason social science can help dampen harmful industry speculation is because it measures and manages risk so well. The interconnected world we live in is complex, with many entwined variables where nothing is certain. To deal with this uncertainty, accurate risk management is needed.

In social science terms, risk is the chance of expected results NOT happening, i.e. dealing with the uncertainty. Probability then measures such uncertainty and we employ data spreads that show the norms, or the expected value, and the standard deviations from the norm give us the variations, dispersions or gyrations, from the average expected value.

We then can begin to see that there is a larger underlying order to the apparent randomness of day-to-day industry actions and the investment markets. Social science can then allow us to harness such risk management techniques and apply reason and evidence to strategies that work.

The relevance of this is in the fact that behaviour and people are at the core of social science and it is people who build businesses, regulators and markets, people who manage them, people who work for them and people who buy from them. So how can this help with RDR implementation strategy you may ask?