The Australian super industry is undergoing a period of unprecedented disruption as technology reshapes customer engagement and expectations and drives funds to redefine offerings and delivery capabilities.
Customer expectations are rising, forcing organisations – regardless of size or sector – to become increasingly customer centric and digitally enabled to not only gain competitive advantage, but even just to compete and survive.
Super is no different. A shift is occurring. What members consider the ‘norm’ has changed. They expect a tailored customer experience, not just to be shown their portfolio. They expect to be provided with transparent value and benefits, personalised recommendations and insights. They want great service, competitive returns and an understanding of what you, the super provider, is doing for them personally.
Coupled with this heightened expectation is a loss of consumer trust in Super funds. This industry and regulatory shift is forcing funds down the expensive path of restructuring organisational values and having to adhere to strict regulatory compliance which has been amplified by political and public scrutiny.
As the power shift to consumer increases, funds have been witnessing an increase in customers exercising their choice to leave in search of better alternatives. This trend is causing a flow on effect of voluntary and involuntary consolidation and mergers of funds.
As funds re-establish standards, technology can be leveraged to help drive customer engagement and strengthen governance practice through the following:
1) Data virtualisation platforms – a single source of truth for all your data:
Many funds run administration services across multiple disconnected systems with little to no integration. Most of these systems are slow, expensive to integrate and require a high level of manual processing that can result in technical debt costing time and money to maintain.
Having to rely on a range of disparate systems usually means there is limited capacity to effectively map out client behaviours and interactions across all channels, as data sets are isolated. This results in an incomplete customer profile that does not consider all aspects of a customer’s financial history and behaviour.
Funds also often lack the ability to accurately curate structured data and unstructured data (emails, texts, letters etc.) collected from customer journeys. Consequently, they are unable to comprehensively understand each customer’s experience and by extension how to best serve each customer thr9ough customer engagement.
Data virtualisation is a technology data management solution that allows an application to retrieve and integrate data from across an entire organisation regardless of where it is located and present it in a single place. Governance, control, data lineage and security can be managed and even enhanced using data virtulisation, over other data consolidation techniques. This allows customer and business insights to be gained quickly and often more cost effectively than building data warehouses and data lakes. Modern financial services challenges require solutions that facilitate a faster and cheaper time to insights, whilst managing governance requirements. Data virtulisation is one way funds and companies can meet the challenge.
2) Artificial Intelligence (AI) models for improved customer engagement and member experience:
Adopting AI offers a viable solution to customer engagement by enabling funds to connect with clients via AI generated insights. Unprecedented amounts of data can be analysed to find patterns, trends and inflections to determine exactly when and how customer’s needs have changed.
Once established, AI algorithms can engage customers in automated interactions that previously wouldn’t have been cost effective, including customer queries and conflict resolution. Super is often perceived by customers as complex as they struggle to understand the benefits and the value the fund is providing. AI and automation has made first class customer service cost-effective, scalable and achievable for the super industry.
3) AI powered regulatory risk & compliance frameworks:
Compliance, risk and audit have traditionally been reliant on rule-based processes to assess and prevent compliance breaches. In addition, these systems often rely on data from a single platform for each risk assessment. However, without a holistic, enterprise view of the enterprise it is difficult for a fund to truly assess enterprise compliance and manage its whole-of-company risks.
AI paired with a data virtualisation platform can be used to build and train models to have secured views on all enterprise data. Data sources for each model can be tracked and managed for traceability, bias reduction and stop non-compliance from the source, through to model development and production. This combination provides lineage from source data to AI model to the final AI-powered decision; a vital component in good financial service governance.
Proactive risk management, governance and compliance tools and frameworks can anticipate, detect and manage AI-backed risk assessments and analytics – allowing funds to respond faster to threats and be nimble in responding to changing regulatory compliance demands.
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