The Role of AI in Superannuation Innovation

Machine Learning and Artificial Intelligence is changing the way super funds deliver service to its members in many facets of its operation. ML and AI adoption in superannuation is all geared to addressing specific business challenges. May it be in acquiring members, delivering customer service, providing member education services, enhancing investment portfolio and assets, and reducing member churn.


The recent global event has altered the way many industries deliver services and it is the same for super funds. Prompting them to implement Machine Learning and Artificial intelligence to innovate and improve their service to address the changed requirements of their members. This reflects not only on how services are delivered – digitally versus in-person but also where the engagement happens – smartphones, computer and other digital devices.

AI in Superannuation Marketing and Member Engagement

Artificial Intelligence in Superannuation | AI Consulting Group

Superannuation funds need a thoughtful and careful approach in marketing to accurately tailor strategies for its members that will deliver desired outcomes such as increased satisfaction and high member engagement.


AI enables funds to segment or group members better other than traditional age, gender and income. With the use of unsupervised machine learning technique called clustering, automatically identify segments from data. Doing so reduces bias and intuitive member segments generated can consist of individuals that respond to the same way to different strategies.


Another area funds use AI in marketing is for attribution, identifying set of actions from an individual that contributed to the desired outcome. For super, this could help determine advertising sources that encourage members to join. Once known, funds can optimise its marketing mix to generate the highest number of members and make the most out of each dollar spent.

AI in Superannuation Investment and Portfolio Enhancement

Super funds’ objective is to provide the best quality of life during retirement to its members, thus efficient fund management generating optimum yield possible is paramount to the business. AI helps fund managers facilitate investments and analyse the best assets and portfolio to invest in. The technology analysis correlations and patterns to make more informed investment decision. Doing so funds can better forecast revenue growth and market size and most importantly improve investment outcomes by choosing assets and portfolio with the best opportunity to gain the highest yield.

AI for Customer Service

A major innovation and AI adoption in Customer Service among funds is the implementation of chatbots. These chatbots handle basic FAQs as well as 24/7 customer assistance. More sophisticated models such as robo-advice are able to provide fund information, advise on personal tax circumstances and investment advice tailored to the member’s financial situation and life stage. Data collected from the bot can be analysed to better understand member needs and to improve call-center services and aid agents with better tools to better assist members.


Educating members on funds, financial management and other educational services is one of the many ways funds continue to serve its members. Through AI, they are able to push tailored content to specific members according to their life stage, fund knowledge, and investment profile.


By taking care of members, anticipating their requirements, and the ability to instill confidence to its members by way of good customer service and constant, consistent communication funds keep member churn percentage low.

Risk Management and Security

As a financial entity super funds and its members are vulnerable to fraud especially at this age and time when the advancement of technology has become a double-edged sword. Fraud is rampant and perpetrators are as technologically advanced if not more, proving to be a very serious threat to the financial and investment institutions. Thus, funds use AI to help detect unusual and fraudulent behaviors and prioritise anomalous activities in the system that may have otherwise gone unnoticed. It is critical in monitoring threats and activities of members and automatically flag abnormal behavior.


Apart from external threats, AI is vital in the internal process and risk management. Human error is a key risk in the industry. Data entry and processing issues may go unnoticed and this can be as critical as recording key member information and processing of contributions and payments.

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