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The Part 8A

The Part 8A

Di: Miko Santos of Mencari News
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The Part 8A is Mencari's news explainer podcast. Miko Santos, the host, will discuss the most significant stories of the day.

theregisterau.substack.comKangaroofern Media Lab Pty Ltd Politica e governo Scienze sociali
Episodi
  • RBA cash rate rise to 4.60 per cent: what it means for mortgages, rents and inflation

    RBA cash rate rise to 4.60 per cent: what it means for mortgages, rents and inflation
    Oct 2 2026
    This episode covers the Reserve Bank's latest cash rate rise, up a quarter point to 4.60 per cent, the fourth increase this year and the highest level since late 2011. Host Miko Santos speaks with Dr Angel Zhong, finance academic and Deputy Dean of Research and Innovation at RMIT University, about who is hurt first and why. Zhong estimates a typical mortgage holder faces $90 to $120 in extra monthly repayments once lenders pass on the rise and explains how renters can also face increases when landlords pass on their own higher costs. The conversation moves to why underlying inflation, measured by the trimmed mean at 3.6 per cent, has stayed elevated for three months, touching on labour market tightness, weak productivity, an ongoing oil shock, and a live debate about whether AI data centres are adding to price pressures. Zhong also flags the risk of unreliable social media financial advice when households are under strain.Key topics & takeaways* RBA raises cash rate to 4.60 per cent, the fourth rise this year and highest since late 2011* Typical mortgage holders face $90 to $120 extra in monthly repayments* Renters exposed to landlord cost pass-through, subject to state rent-increase rules* Trimmed mean inflation at 3.6 per cent for three months, still above the 2-3 per cent RBA target* The drivers of sticky inflation include a tight labour market, weak productivity, and an oil shock affecting shipping and groceries.* Debate over whether AI data centre demand for chips and electricity is contributing to inflation.* Financial stress raises risk of households turning to unreliable social media finance advice.Follow The Part 8A on Spotify and Apple Podcasts so next week’s episode lands in your feed.Truth matters. Quality journalism costs.Your subscription to Mencari directly funds the investigative reporting our democracy needs. For less than a coffee per week, you enable our journalists to uncover stories that powerful interests would rather keep hidden. No corporate influence. No compromises. Just honest journalism when it matters.Guest & Host InformationHost: Miko Santos, presenter of Part 8a.Guest: Dr Angel Zhong is Deputy Dean, Research and Innovation in the School of Economics, Finance and Marketing at RMIT University, and a regular media commentator on monetary policy, retail investing and financial markets. https://www.rmit.edu.au/profiles/z/angel-zhongSources, links & further reading* Dr Angel Zhong profile – RMIT University https://www.rmit.edu.au/profiles/z/angel-zhong* RBA says inflation upside risks are getting concerningly real – Banking Daily https://www.bankingdaily.com.au/articles/rba-says-inflation-upside-risks-are-getting-concerningly-real* Short-term pain, long-term gain – Riverine Herald https://www.riverineherald.com.au/news/short-term-pain-long-term-gainContent warnings & disclaimersThis episode discusses cost of living pressure and financial hardship. Comments on investing, lending and scams are general commentary, not personal financial advice.This is not a sponsored video/audio. A small commission will be paid to us if you purchase anything through some of the affiliate links in our product listings.If you want to chat more about this topic, I would love to continue the conversation with you on Twitter @realmikosantos!This podcast is powered by Kangaroofern, Australia's independent podcast management company.Thanks so much for listening to our podcast!If you enjoyed this episode, be sure to subscribe so you'll be notified when a new episode is posted in the Apple podcast, Google podcast, Spotify, Stitcher or via RSS. If you think others could benefit from listening, please share it on your socials.You can also subscribe to the podcast app on your mobile device. If you found value in this episode, leave us an Apple Podcast review. Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts and expose our show to more awesome listeners like you. This is a premium episode. If you would like to discuss this with other subscribers or get access to the episodes, visit Financial RegisterGot a News Tip?Contact our editor via Proton Mail encrypted, X Direct Message, LinkedIn, or email. You can securely message him on Signal by using his username, Miko Santos.While mainstream media serves corporate interests, you deserve the truth.Your Mencari subscription—less than a coffee per week—powers real independent journalism. Our reporters dig into the stories powerful people desperately want buried. No corporate masters. No political handlers. Just the uncomfortable truths that matter most right now.This is journalism without compromise, funded directly by readers who refuse to be misled. If this reporting opened your eyes, hit Restack so others can see what they're missing.Not ready to be paid subscribe, but appreciate the newsletter ? Grab us a beer or snag the exclusive ad spot at the top of ...
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    24 min
  • OpenAI Medicare breach explained: why "rogue AI" is the wrong label, with AI ethicist Dr Rebecca Johnson

    OpenAI Medicare breach explained: why "rogue AI" is the wrong label, with AI ethicist Dr Rebecca Johnson
    Sep 27 2026
    The OpenAI Medicare breach made headlines as a case of “rogue AI”. Dr Rebecca Johnson, an AI evaluation and governance researcher, rejects that label. On The Part 8A, she tells host Miko Santos that the agent did what its settings allowed. The failure sits with the people at OpenAI who designed the test, chose Australia as the place to run it, and waited weeks to tell anyone.She explains why most AI tests only check whether the model got the right answer, not how it got there. She also covers why Silicon Valley’s values don’t transfer neatly to Australia and why a popular ethics benchmark was built on a Reddit forum.Her argument for policymakers is direct. After the OpenAI Medicare breach, Australia should demand logs of these experiments and the right to run its independent tests on AI models designed with local communities. She says we’re moving too slowly.Key topics & takeaways* Why calling it “rogue AI” shifts blame away from the company that built and tested the agent* The gap between outcome-based testing (did it get the answer?) and trajectory-based testing (did it break through a wall to get there?)* How using Australia as a live test environment reflects values that clash with ours, according to Johnson* OpenAI’s slow notification, sent to a public Services Australia inbox rather than by phone* Johnson’s case for independent, Australian-designed AI evaluations: “Someone checking their own homework” isn’t good enough* Value pluralism, and why Sam Altman’s idea of taking the “median value of the planet” would drown out smaller communities* Bad proxies in AI benchmarks, from a Reddit forum used as aSources, links & further reading* OpenAI’s agent hacked Australia’s Medicare website, PM Albanese says – Fortune [https://fortune.com/2026/09/23/openai-agent-hacks-australia-medicare-sam-altman-anthony-albanese/]* Medicare Australia: “Extreme concern” over OpenAI breach of health database – CNN [https://www.cnn.com/2026/09/23/business/australia-openai-agent-hack-intl-hnk]* OpenAI says agent hacked Australian government website without being told to do so – CNBC [https://www.cnbc.com/2026/09/24/openai-agent-hacked-australian-government-website-.html]* Medicare hack alert went to inbox checked once a day and took five days to be escalated – SBS News [https://www.sbs.com.au/news/article/openai-agent-hacked-medicare-albanese-reveals/qas79d9ta]* Measuring the Machine: Evaluating Generative AI as Pluralist Sociotechnical Systems – Rebecca Johnson, doctoral thesis [https://arxiv.org/pdf/2604.20545]* World Values Survey – World Values Survey Association [https://www.worldvaluessurvey.org]* Aligning AI With Shared Human Values (the ETHICS dataset) – Hendrycks et al. [https://arxiv.org/abs/2008.02275]* Machine Bias – ProPublica [https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing]Content warnings & disclaimersContains brief strong language (the name of a Reddit forum) and discussion of racial bias in the US criminal justice system.Follow The Part 8A on Spotify and Apple Podcasts so next week’s episode lands in your feed.Truth matters. Quality journalism costs.Your subscription to Mencari directly funds the investigative reporting our democracy needs. For less than a coffee per week, you enable our journalists to uncover stories that powerful interests would rather keep hidden. No corporate influence. No compromises. Just honest journalism when we need it most.Five Key Takeaways* A $250 “curiosity click” on a fake Shark Tank-endorsed investment ad grew into a $2.6 million loss within three months, partly because the scammers used a legitimate-looking 100-point identity check to build trust early on.* Banks let large, unusual transfers through — including $1.1 million in under three hours — because Sylvia had sent money to the same account before, and the pattern wasn’t flagged as new.* Anti-money-laundering reporting obligations sit with government regulators, not with the customer. Sylvia argues that’s the biggest structural gap letting scams slip through.* Australia’s new Scams Prevention Framework is meant to share responsibility across banks, telcos and platforms, but Sylvia says it’s made recovery harder, since victims now have to build a case against multiple large institutions with almost no information of their own.* Sylvia co-founded the Scam Victim Alliance after meeting other seven-figure-loss victims at a 2024 Canberra press conference. The group now runs weekly support sessions and helps survivors through the AFCA complaints process.Detailed SynopsisContent note: this episode discusses financial loss, disputes with banks and, briefly, thoughts of suicide. If any of this affects you, you can contact Lifeline at 13 11 14.The ClickIt started with $250 and a television show. Sylvia was scrolling Facebook in 2019 when she saw an ad for a trading platform claiming a Shark Tank endorsement. She ...
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    29 min
  • Money mules and money laundering in Australia: how graph theory tracks dirty money

    Money mules and money laundering in Australia: how graph theory tracks dirty money
    Sep 24 2026
    Episode summaryMoney mules are often ordinary people. Many are international students or others trying to make ends meet, recruited through job ads that promise $1,000 for an hour’s work. In this episode of The Part 8A from The Financial Register, host Miko Santos talks with Professor Asha Rao, a mathematician and cybersecurity expert at RMIT University. They look at money laundering in Australia the way a mathematician does: strip away the dollars and map only the connections.Rao explains why laundering is so hard to spot inside the dense web of everyday banking, and why most cases surface only when someone spends far beyond their income. She shows how graph theory can shrink hundreds of thousands of accounts down to a network small enough for police to check.She also unpacks a tension in Australia’s AML/CTF Act. The secrecy that stops criminals learning how they’re caught also leaves researchers without data. The incoming Scams Prevention Framework won’t touch money laundering directly, she says. Her advice to anyone offered easy money: don’t react straight away.Key topics & takeaways* What a money laundering network looks like as a mathematical graph, and why nothing in the picture gives it away* Why laundering usually comes to light only when someone on a $50,000 salary suddenly owns yachts and houses* How “work from home, earn $1,000” job ads turn international students into money mules who find out only when police knock* Why police focus on stopping mules rather than blaming them, and where banks and AUSTRAC fit in* How the AML/CTF Act’s secrecy rules starved open research of data for a decade, until IBM released simulated transaction data* How graph theory narrows a network of 400,000 people to 10 or 20 accounts, giving police a starting point rather than a crystal ball* Rao’s rule for any too-good-to-be-true offer: count to 10 slowly before you react at allTimestamps* [00:00] Cold open – how criminals blend into millions of ordinary transactions* [01:12] Meet the guest – Professor Asha Rao, RMIT University* [02:38] Laundering as a graph – nodes, edges and a very dense network* [05:24] The $1,000-an-hour job ad – how money mule schemes recruit* [09:52] Blame the students or the banks? – AUSTRAC, bank penalties and what police actually do* [11:10] The data problem – why the AML/CTF Act stops banks sharing, and what that means for research* [15:02] What the Enron emails showed – shrinking a huge network to 10–20 nodes* [17:12] Protecting the innocent – how investigators check a small flagged network* [24:17] Should the law change? – why Rao wants detection methods kept secret* [25:33] The Scams Prevention Framework – why it won’t tackle money laundering* [27:32] Parting advice – don’t react, let your brain catch upGuest & host informationHost: Miko Santos, journalist and founder of Kangaroofern Media Lab, host of The Part 8A from The Financial Register.Guest: Professor Asha Rao is Professor of Mathematics and Cyber Security at RMIT University and a former Associate Dean of Mathematical Sciences there. In 2020 she became the first female director (interim) of the Australian Mathematical Sciences Institute. Her research applies graph theory to problems including money laundering detection. She was inducted into the 2021 Victorian Honour Roll of Women in the Trailblazer category. Sources, links & further reading* AUSTRAC and CBA agree $700m penalty – AUSTRAC [https://austrac.gov.au/node/260]* IBM Transactions for Anti Money Laundering (AML) dataset – IBM Research via Kaggle [https://www.kaggle.com/datasets/ealtman2019/ibm-transactions-for-anti-money-laundering-aml]* Realistic Synthetic Financial Transactions for Anti-Money Laundering Models – Altman et al. [https://arxiv.org/pdf/2306.16424]* Money laundering typologies and indicators – AUSTRAC [link needed]* Scams Prevention Framework – Australian Treasury [link needed]* Enron email dataset [link needed]* Professor Asha Rao, Victorian Honour Roll of Women 2021 – Victorian Government [https://www.vic.gov.au/professor-asha-rao]Content warnings & disclaimersCorrection: In the episode, the penalty paid by Commonwealth Bank is recalled as about $1.2 billion. The penalty agreed between AUSTRAC and CBA was $700 million, resolving Federal Court proceedings over serious breaches of AML/CTF laws. austracFollow The Part 8A on Spotify and Apple Podcast so next week’s episode lands in your feed.Truth matters. Quality journalism costs.Your subscription to Mencari directly funds the investigative reporting our democracy needs. For less than a coffee per week, you enable our journalists to uncover stories that powerful interests would rather keep hidden. No corporate influence. No compromises. Just honest journalism when we need it most.Five Key Takeaways* A $250 “curiosity click” on a fake Shark Tank-endorsed investment ad grew into a $2.6 million loss within three months, partly because the scammers ...
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    29 min
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