We believe that the real key to engaging members at scale is by understanding the context of where they are in their life stage and providing relevant and contextual advice based on what they are hoping to achieve both in the short-term as well as the long-term.
Artificial Intelligence can help identify behavioural patterns and provide intelligent and contextual guidance based on the individual’s circumstances. This can offer the member a vastly improved customer journey which they are crying out for — simple, intuitive, engaging and personalised.
At a high-level, there are 4 key stages of a member journey of how they engage with their pension and in this series of articles we will tackle how AI can deliver relevant advice to help members save more depending on what stage they find themselves in.
The customers want the following things at each stage:
Stage 1: First Step
o Definitions and Context
o Needs Analysis
o Online (Multi-channel) support
Stage 2: On your way
o Ongoing Financial Guidance
o Forecasts, Dashboards, see al their money in one place
o Define their goals and stay on track
o Higher-earner communications
Stage 3: Getting there
o Online support
o Nudge communications
o Get prepared for retirement, shortfall analysis
o Advice on retirement options
Stage 4: Arrival
o Advice on whether to retire now or delay
o Transfer and transact to draw pension
o Ongoing advice
The amount of data we create and consume is expanding exponentially. With the increased awareness of the power of data comes an increased expectation of what our service providers should be able to offer. The average member of a pension will be used to Amazon’s product recommendations, Google’s auto-complete search suggestions and Facebook’s personalised ads.
The same cannot be said in the case of the pension industry. Financial providers are sitting on vast amounts of data points about their customers, and even with the advent of Open Banking, there is not a single provider that can say they have leveraged this technology to overhaul the experience of the majority of their members.
Our experience at ABAKA shows that leveraging cutting-edge AI technology can help providers process 2 to 5 million data points per day for any given member. The list includes (but is in no way exhaustive) information about a member’s personal, transactional and behavioural data, changes in spending patterns, articles they’ve read, nudges they have responded to, account balances and life events, markets and risk exposure, state and payroll taxes, rules and regulations, inflation and cost of living, location, property taxes, mortgage and refinance rates, longevity, school fees, and many more.
There is no way a human can process the vast quantities of data created and extract useful intelligence from it without significant computational power and artificial intelligence.
Most members have no clue how to deal with their pensions, and despite auto-enrolment, are still clearly not saving enough. By keeping on top of all this information, an AI-powered adviser can provide a member advice which is personalised, timely, accurate, up-to-date, and anything but generic.
Even an experienced human adviser simply cannot factor in all the details in a member’s life that AI is capable of handling with ease. AI also provides a level of control, monitoring and consistency of the advice provided which creates a highly cost-effective way to maintain and cope with ongoing compliance requirements and it can even be used to augment the capabilities of a human adviser.
Stay tuned for the next article which will highlight how AI can drive engagement with members at Stage 1 of the journey or visit our website at www.abaka.me