InsuranceERM Awards 2022
Guided Outcomes - Winner of Actuarial modelling solution of the year
28 Feb 2022
GO™ is our robo-guidance proposition which has been transforming outcomes for DC members for nearly a decade. We are delighted to have won InsuranceERM's Actuarial modelling solution of the year award for 2022.
The problem we solve – effective retirement guidance for customers who don’t have access to financial advice
The FCA recently reported there are 15.6 million adults in the UK with investible assets of £10,000 or more. Of these, 8.6m are more than 75% invested in cash. At the same time the FCA reported only 8% of UK adults received financial advice in the last 12 months. Given the cost of advice relative to the scale of most peoples’ financial assets, this isn’t a surprise.
Furthermore, the ONS reported last year that membership of Defined Contribution schemes in the UK now exceeds 22m people - primarily due to the success of auto-enrolment.
However, the lack of pensions awareness and the inaccessibility of financial advice means that millions of people are left to make important financial decisions without access to professional support.
The introduction of freedom and choice in 2015 raised the stakes further, meaning that consumers also needed to make effective financial decisions through the spending phase as well as the savings phase.
We were confident we had the tools to help with this, and it is our mission to deliver better financial outcomes to UK savers.
We already had robust economic models, investment expertise and actuarial processes to support massive DB pension schemes. Our DC consulting practice had substantial experience in this market and in engaging pension members. Plus our Digital Wealth business had the tech credentials to build and deliver digital propositions with a compelling user experience.
Combined, this meant we could deliver the guidance all pension members need, when they need it – like having an actuary in your pocket at just the right time!
Principles for success
GO is a robo-guidance model that is:
- Outcomes based – focusing on what really matters to people
- Highly personalised – giving meaningful and easy to follow information
- Comprehensive – designed to cover all parts of the savings and retirement journey
Central to our approach is the robust modelling engine that underpins the guidance, developed and maintained internally by our multi-disciplinary team of actuaries, investment experts and statistical software development professionals.
In the savings phase GO works by:
- Taking basic minimum data on each member (e.g. age, contributions, investments and retirement age)
- Applying a retirement income target to each member, projecting their benefits using our proprietary cashflow and economic scenario modelling engine and assessing the chances they will meet their target
- Using utility theory and other behavioural finance approaches to derive the optimum approach to meeting their target, if they are off track
- Continually monitoring their position and providing nudge guidance to take corrective action to improve their retirement outcome
A clear traffic light system is used to make the position clear to the member
In the spending phase the same principles apply in reverse. Members are given pro-active guidance around a sustainable spending rate and can then be monitored and nudged to stay on track. In addition, Club Vita data, the UK’s richest longevity dataset, is used to factor in the longevity risk as well as the investment risk. These are combined into a single metric to allow a simple presentation to the member.
The GO products are designed as a suite of modular APIs and widgets, meaning they can be used widely, are configurable and easy to implement in other propositions to maximise use and benefit to end consumers.
GO has had a transformational effect on pension members:
- Around 2 in 5 immediately increase pension saving after using GO
- Average total increase in contributions after GO is 4% of pay
- People’s understanding of their pension doubled after using GO (from 40% to over 80% rated their understanding as “good” or “very good”)
To find out more about our GO™ apps and APIs please get in touch with Fyona Murphy.