Overwhelmingly, consumers are demanding a tech-based and life goals-centered advice experience.
We will see the financial planning industry rapidly evolve into a hybrid of a 'tech' and 'coach' style profession. Those that choose not to adapt will find growth and competition a challenge. This removes friction in the value chain.
3 biggest technology trends in 2022 for the financial planning professional are:
Let’s explain each of these.
Modelling a client's current financial circumstances and future scenarios is crucial for financial planners. Robust numbers are important for providing quality advice, helping them to meet their life goals as the ultimate outcome.
Financial modelling takes up intensive computation power; taking historical, present-day and future projections and combining the results into a simulation.
Improvements in computation power via the cloud has evolved modelling from an excel based linear approach, into something more multi-dimensional.
This holistic consideration of a client's goals, net wealth, cash flows, strategies, and economic factors, means that there's an opportunity to make advice client-centric and meaningful to the end consumer.
What is multi-dimensional modelling?
It all comes down to a mathematical equation; a client's assets, income, and expenses must meet their changing life goals & life events, over time. Projecting thousands of simulations that factor in economic assumptions, goal achievability, financials, risk, and other combinations of advice strategies - all within a client-facing setting.
This live modelling analysis enables advisers to deliver an engaging financial advice experience to their clients, helping them understand all possibilities.
How will Big Data play a part in modelling?
As Big Data grows, data will become the cornerstone of financial modelling. Currently, financial models only deal with limited individual client financial data, however, this is changing. With the improvement of open banking standards and connected planning technology, there will be greater access to an abundance of data.
Machines will be able to identify more meaningful patterns in client data, determining predictive models and future scenarios from a more accurate picture of a client's spending habits, investments, and behaviour. This will help advisers to provide a more dynamic advice value proposition and ultimately better financial outcomes for consumers.
Machine Learning in planning will continue to enhance optimisation capability, by learning over time the combinations of strategies that self-determine an optimal scenario, one that puts the client in a better position in relation to their goal achievability.
How financial modelling will be driven by automation?
Today, financial modelling is limited by three main factors; the complexity of variables, the volume of calculations, and the skill set of one person to create models. The human mind is incapable of processing the complex interactions and mathematics involved.
However, computers can perform complex calculations in large volumes, they have the ability to process more and predict with higher accuracy than the human mind. This will only continue to advance.
In the future, modelling software using Machine Learning will be able to interpret and optimise various permutations of client scenarios and determine their best outcome independently. Currently, the missing piece to this is the breadth of individual client financial data. Machines need a full range of data to rule success and failure for various scenarios, the more data inputs help produce every possible outcome.
As we advance planning software and move into a world of automated data feeds that feed modelling software, computer-generated models will become just like driverless cars, functioning with little human intervention.
How Customer eXperience is the new battlefield - consumers expect more!
97% of consumers use banking apps on their mobile devices to transact their finances.
So, why can’t clients have their own interactive financial plan that tracks their progress against their goals? Why is there no live financial plan delivered via an app on their smartphone?
Today, there are no technology tools that can truly demonstrate the value of advice to consumers. Nor is their technology that can link, track and monitor advice strategies against customers’ individual life goals.
This lack of a client-centred technology has resulted in poor consumer engagement, central in the argument for regulatory reform.
We all know that financial wellbeing through quality advice is one of the most powerful things any person can experience. The purpose of financial advice is to improve clients’ lives, see new possibilities and excite them about their future.
The current financial planning process and traditional statements of advice fail to adequately engage consumers and deliver on that promise. Consumers want advice delivered in a smarter, and more appealing way. A dynamic experience they feel part of, personalised to their individual life goals.
Today, only 27% of Australians have seen a financial adviser, yet 57% want to seek advice, and with financial adviser numbers dropping from 19,651 mid 2021 to a predicted 13,000 by the end of 2023, there’s a shortage of advisers to service this demand. The only answer is to automate the advice profession and enhance the technology customer experience.
(Source FPA, ASIC & Adviser Ratings)
So what does a reimagined tech-based advice experience look like?
This reimagined advice experience warrants a new technological realm known as goals-based advice, which takes client’s financial data, auto populates strategy modelling & product comparator tools and helps determine the most optimal recommendation, based on the clients actual goal achievability as the measure – then produces an instant, digital SOA to their mobile app.
We will see the simplification of financial planning, empowering consumers to choose the way they want to receive advice via:
An interactive, tech-based financial planning process will gratify both models, from the “Do with” my adviser that assists a hybrid human and digital advice process. Further, this technology helps to commercialise ‘foundation advice’ for the “DIY” consumer – with the ability to service a much greater Australian market via an ongoing low-cost subscription-based model - all within a compliant framework.
Globally, regulators are working to ensure clients receive quality financial advice. Compliance is part of the value chain and when it’s inefficient, it adversely affects the value delivered – this cost falls on the consumer.
The recent Royal Commission, FoFA, and fee-for-service guidelines have been introduced to ensure clients' “best interests” are being met and to protect consumers from sub-standard quality financial advice.
Traditional financial planning software has failed licensees, planners, and clients. Old-world advice technology was not designed for today’s regulatory environment, nor today’s consumer. There is a lack of pre-emptive controls to monitor advice upstream of the advice process. Advice is delivered to consumers without any automated quality assurance measures.
Without quality assurance, there is a serious risk that sits with AFSL holders and often they can only be reactive, not proactive, prohibiting the delivery of quality advice at scale.
Compliance must be designed as a joint responsibility held by the consumer and adviser. What this means, is that advisers must co-create advice with their individual clients so the onus is with both parties.
How does compliance become part of the advice process?
Compliance automation needs to sit within the advice customer experience. Technology designed this way can enable advisers to co-create client scenarios jointly with their clients, capture the conversation by modelling various advice strategies, including “what-if” and “trade-offs”, and see instantly the direct impact to their goals & objectives, as well as have all the compliance ticks behind the customer experience.
Book a demo to see for yourself how a.i. is driving financial technology to an exciting new-tech based future.