Pension freedom brings both the good and the bad. As the demand for advice increases, for example, so grows the risk advice firms have to shoulder when it comes to advising on potential defined benefit (DB) transfers.
Based on well-known stories, we already know this is a complex area where the financial consequences of poor advice can be massive. We also know nervous insurers are circling the advice sector in a bid to evaluate these uncharted waters.
The danger is that firms are tempted to throw the baby out with the bathwater. The focus should always be on what is best for the client - not what is safe for the advice firm. Any good advice firm will be eying the expected wave of baby-boomers due to retire with their substantial DB pots and will be working out strategies on how best to advise them - no matter the complexities.
And complexity is something technology and artificial intelligence (AI) is much better placed to handle than the human brain, with AI easily able to weigh up billions of data points against complex calculations in seconds; something the human brain simply cannot do.
When it comes to DB advice, we know it requires specialisation on the part of an adviser and, in a rapidly changing and complex area such as DB transfers, traditional expert systems are not enough. So consider how powerful it could be if the expertise from a large, diverse group of advisers could be collated into one system that, over time, becomes a central source of best practice.
This is what AI and machine learning are doing right now - and this is how the sector will be provided with a much-needed lifeline at a time when risk is becoming the dominating concern.
While creating a one-stop DB advice solution underpinned by AI and technology has its own complexities, work has been underway for months. As an example, the development of the Wealth Wizards Smart Platform to incorporate a DB solution has necessitated working with a number of partners who are experts in DB advice alongside the Wealth Wizards expert team.
By pooling and consolidating expertise from these groups into algorithms, this will support advisers in identifying which factors support a recommendation to transfer or not, and the magnitude of those factors in that decision.
This pooled insight can be augmented with an advice firm's own expertise and opinion, and the benefit of previous DB transfer advice which has been given. Creating a single integrated solution for DB transfers, where all the required parts and processes are delivered via a single, focused and purpose-built tool, adds robust control into the DB advice process.
These new technology-driven solutions will help firms identify the strength of each individual transfer recommendation, meaning additional consideration can be afforded where a transfer (or retain) recommendation appears to be in the client's best interest, but the rationale is nuanced and the weight of evidence is not overwhelming. The one-stop solution will also ensure a firm has met advice standards with this assurance running right through the advice given - that is,. avoiding concern about hand-offs between advisers and tools.
Some may have questions about advice anomalies and the ability of AI and machine learning to cope. During the development of the Smart Platform algorithm against an advice policy written by a firm, for example, the resultant AI would not always agree with advice that had been given.
When those cases were reviewed again, the difference appeared to stem from a nuance within a specific transfer recommendation which had not been reflected in the advice policy. This suggests there is more aggregate intelligence in past advice than has been captured in a firm's advice policy.
By overlaying AI, which has trained with the benefit of past advice - both good and bad - it will provide reassurance to the adviser that decisions are generated using best practice in addition to relying solely on advice policy.
The beauty of AI
The beauty of AI is it keeps on learning - the more data, the more the one-stop solution will ‘learn' and be intelligent enough to highlight areas of potential concern. Advisers and professional indemnity (PI) insurers are sitting on huge amounts of data that can support the evaluation of risk. Together, machine learning alongside human advisers are a powerful combination - especially if the data continues to flow.
In the future, we expect industry data and evaluation to be made public for advisers to use for the evaluation of both their advice policy and individual advice cases. This will ensure the cumulative experience of the entire industry is applied to every single individual who receives advice.
One aspect Wealth Wizards is considering is how AI might be trained on large data-sets of ‘good' DB advice, and also data pertaining to some of the DB scheme scandals - this kind of model (perhaps something the regulator could support) would allow simple, macro-scale analysis of DB transfer business conducted by a firm to highlight signals in either direction.
Imagine how much better the industry would then be able to manage risk, leading to reduced incidence of claims and thereby reduced PI insurance premiums …
These new innovative products underpinned by AI can also benefit the wider industry too. There is no reason why the regulators and PI insurers should not be using tech to assess risk and as a means to publish best practice and expectations. And let's not forget internal compliance teams within firms.
Firms can struggle with the challenge of resourcing quality control for DB transfers that require really expert staff. AI can learn how they do their job and scale up their expertise, again bringing the benefits of consistency and capability to consider huge data sets.
What is clear is that, by sharing data and using state-of-the-art innovative machine-learning products, the industry as a whole will benefit thereby reducing costs and pay-outs and, most importantly, delivering the client the advice they deserve.
This article originally appeared in Professional Adviser