Helping clients protect and recover value through proactive cyber risk identification and management, and rapid action in response to a breach.
Helping clients to manage risk and regulatory compliance and respond to incidents of financial crime.
Uncover, analyse and clarify facts at the centre of disputes, frauds and other sensitive commercial matters.
Providing advisory and accelerated implementation services to the public and private sector.
Assists clients to grow, protect and recover value in their real estate portfolios.
Working with organisations to stabilise the business or to recover value on behalf of stakeholders.
We are Asia-Pacific’s trusted advisers in cybersecurity, financial crime, forensic, performance improvement, real estate and restructuring.
Our reach is global with offices across Australia, New Zealand, Indonesia and Singapore.
KordaMentha staff are actively engaged in giving back to their communities.
Superannuation class action seeks data analytics services.
We developed a model to simulate and analyse the growth of $3.2 billion of superannuation member funds (associated with over 100,000 members) over a four-year period under various fund portfolios.
The phase one model simulated historical transactions and was found to have 99.99% accuracy when compared to that of historical records.
Phase two’s counterfactual model simulated the transfer of member funds at various dates to various superannuation accounts and tracked their performance over the same four-year period. The outcome of the phase two modelling is still being heard by the Federal Court of Australia.
KordaMentha was engaged to provide data modelling services regarding a class action against a major superannuation fund. The class action alleged that approximately $3.2 billion of members’ superannuation funds had been mismanaged.
We developed a dynamic data analytic model that could simulate the performance of class member funds had they been transferred to various other superannuation products at specified points in time over the specified period. This included analysing each class member’s individual super contributions and deductions across a four-year period.
In a two-phased approach, we developed models that allowed a counterfactual calculation. The phase one model simulated the historical transactions and was compared to historical records. In phase two, we developed the counterfactual model which simulated the transfer of member funds under varying scenarios and tracked their performance across the same period.
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