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Rising rates and complex products have turned minor mortgage missteps into multi-year financial drags. This case study examines how an Australian broker network redesigned its advice, data and technology stack to reduce borrower errors, protect portfolio quality and lift conversion—offering a replicable playbook for lenders and fintechs. The results point to measurable reductions in early arrears risk, faster cycle times and a clearer path to sustainable growth.

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Context: When small mistakes meet big rate rises

Australia’s mortgage market has shifted from a hunt for the lowest sticker rate to a stress test of financial resilience. The Reserve Bank’s cash rate moved from 0.10% in late 2020 to 4.35% by late 2023, leaving hundreds of thousands of borrowers rolling off ultra-low fixed loans into variable rates often 300–400 basis points higher. Industry analyses estimate more than A$300 billion in fixed-rate loans matured across 2023–2024, with repayments for many households jumping 30–60% on rollover. Household debt remains among the highest in the OECD, hovering near 190% of disposable income. In parallel, S&P’s prime RMBS arrears index ticked up through 2023–2024 (towards ~1.5%, up from ~1.0% in 2022), signalling mounting pressure.

Against this backdrop, seemingly small errors—choosing a honeymoon rate without understanding the revert, setting the wrong loan structure, ignoring offset features, underestimating living expenses, or failing to lock a rate—compound into years of excess interest or heightened default risk. The pressure is amplified for first-home buyers and self-employed borrowers, who are more exposed to documentation and serviceability pitfalls.

Brokers now originate more than 70% of new Australian home loans (MFAA), positioning them at the front line of prevention. As one industry mantra goes, “Price gets attention; structure builds resilience.”

Decision: Build an advice-grade, data-driven mortgage journey

This case study synthesises practices from multiple Australian brokerages and lender-fintech collaborations to profile a composite transformation—Project Clarity—designed to reduce borrower mistakes and improve credit outcomes. The strategic choice: shift from a rate-shopping workflow to an advice-grade, data-driven journey that is defensible under Best Interests Duty (BID), integrates Consumer Data Right (Open Banking), and hardwires stress testing and product fit into every recommendation.

The target outcomes were explicit:

• Cut application rework and document back-and-forth by double-digit percentages.
• Reduce early arrears risk by improving serviceability accuracy and debt structure.
• Lift approval conversion by matching borrowers to fit-for-purpose products (e.g., offset vs redraw, fixed/variable splits, rate-lock usage).
• Demonstrate BID compliance with transparent trade-offs and scenario testing.

Implementation: From generic rate hunts to structured, data-rich advice

Project Clarity deployed six building blocks:

1. Open Banking fact-find. With CDR consent, bank transactions were ingested and categorised to capture accurate income variability, existing debts, and true living expenses (cross-checking against HEM). This closed a common mistake: underestimating expenses that later derail approvals.
2. Serviceability and scenario engine. Policies from major and non-bank lenders were codified to model buffers (APRA’s 3% minimum), higher-rate stress scenarios, and different loan structures. Borrowers saw side-by-side projections: interest-only vs principal-and-interest, fixed vs variable, and 60/40 split options, each tested at +300–500 bps.
3. Product-fit rules and fee transparency. A rules layer filtered products not only by rate but by features that materially change outcomes (offset eligibility, package fees, cashbacks, break costs, LMI thresholds, rate-lock availability). A plain-language ‘Key Facts’ sheet made revert rates, comparison rates and total cost-to-own explicit over 3–5 years.
4. Automated document capture. OCR and e-sign tools prefilled applications; Open Banking reduced the need for manual bank statements and payslips where feasible. This addressed a chronic error driver: missing or outdated documents causing rework and pricing changes.
5. Bid-safe recommendations. Every recommendation included a rationale trail and audit artefacts: trade-off narratives, stress outcomes, and why alternatives were rejected—protecting brokers and informing customers.
6. Rate and cashflow hedges. Clear guidance on rate-lock usage, offset funding habits, and redraw implications. The system nudged borrowers to maintain 3–6 months of expenses in offset and highlighted the cost of not doing so under higher-rate scenarios.

Change management mattered as much as code: brokers were trained to lead with structure, not headline rate; lenders agreed on digitised policy updates; and fintech partners committed to service-level turnarounds so data flows didn’t become a new bottleneck.

Results: Evidence and numbers that matter

While outcomes vary by organisation, the following results are consistent with Australian pilots and global benchmarks in digital mortgage transformations:

• Cycle time: Prefill via Open Banking and automated document capture commonly reduces time-to-approval by 20–40% and cuts touches by 25–35% (in line with global lending benchmarks reported by consulting studies). Faster decisions reduce the window for adverse rate moves—a direct antidote to the “I missed the rate-lock” mistake.
• Data accuracy: Transaction-verified expense capture typically reduces material variance between stated and verified expenses by 30–50%, lifting approval conversion and lowering ‘surprise declines’ late in the process.
• Portfolio risk: Applying a consistent 300–500 bps stress scenario and steering high DTI cohorts into more conservative structures is associated with lower early-stage arrears; market indicators support the link—APRA’s tighter assessment settings coincided with the share of new lending at DTI>6 easing from peaks near a quarter of flows in late 2021 to materially lower levels by 2023.
• Customer economics: Clearer product-fit decisions drive quantifiable savings. For example, a borrower maintaining A$30,000 average offset at a 6.3% variable rate saves ~A$1,890 per year versus redraw or no-offset equivalents; over five years, the foregone interest exceeds A$9,000 before compounding. Making revert rates visible also avoids post-discount bill shock that can add 80–120 bps after a honeymoon period.
• Channel performance: The broker channel’s share above 70% reflects demand for advice; firms that operationalise BID with data trails report higher repeat/referral rates and fewer dispute escalations—critical intangible returns during tight credit cycles.

As one senior risk leader put it, “Speed without structure is just a faster way to be wrong.” The combination of verified data, scenario-led advice and disciplined product selection is what changes outcomes.

Lessons: What leaders should do next

Business impact. Borrower mistakes are an avoidable cost centre—driving rework, pricing variance, churn and arrears. Fixing them frees capacity, reduces loss given default, and preserves customer lifetime value in a high-cost-of-funds environment.

Competitive advantage. Early adopters of advice-grade workflows have a defensible edge. Product commoditisation is real; the moat is the ability to prove suitability under multiple rate paths, with a documented trail. That’s hard to copy quickly.

Market trends. Expect continued normalisation of arrears from ultra-low baselines and ongoing scrutiny of high DTI/low buffer segments. Cashbacks are waning; lenders are competing on feature-value and service velocity. Open Banking penetration will expand as more consumers consent to data sharing in exchange for faster, more accurate approvals.

Implementation reality. Start with the unglamorous plumbing: policy codification, data categorisation accuracy, and broker coaching. Measure what matters—variance between stated and verified expenses, revert-rate exposure at the portfolio level, rate-lock uptake, and split-loan suitability scores. Align incentives so brokers are rewarded for long-term suitability, not just settlement speed.

Future outlook. With inflation sticky and the cash rate elevated, resilience beats optimisation-on-paper. The next wave will blend CDR data with payroll APIs, property AVMs and behavioural nudges to coach offset usage post-settlement—turning ‘advice at origination’ into ‘advice across tenure’. Regulators will likely keep the 3% buffer in play until disinflation is entrenched; boards should plan product and risk settings for sustained higher-for-longer scenarios.

Strategic bottom line: mortgage mistakes are not inevitable. They’re a data and design problem. Organisations that re-architect for advice, verify rather than assume, and make trade-offs explicit will take share, reduce risk and earn trust—whatever the rate cycle does next.

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Rising rates and complex products have turned minor mortgage missteps into multi-year financial drags. This case study examines how an Australian broker network redesigned its advice, data and technology stack to reduce borrower errors, protect portfolio quality and lift conversion—offering a replicable playbook for lenders and fintechs. The results point to measurable reductions in early arrears risk, faster cycle times and a clearer path to sustainable growth.

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Debt consolidation is a strategic approach to managing multiple debts by combining them into a single, more manageable loan.

" ["fulltext"]=> string(5771) "

This method can simplify your payments, potentially lower interest rates, and help you pay off debt faster. However, it requires careful planning and understanding. Here are essential tips for effective debt consolidation.

Essential tips for effective debt consolidation

Assess your financial situation

Start by thoroughly assessing your current financial situation. List all your debts, including credit card balances, personal loans, and other liabilities.

Note the interest rates and monthly payments for each. This overview will help you understand the total debt you’re dealing with and identify the high-interest debts that should be prioritised in consolidation.

Understand different debt consolidation options

Debt consolidation can be achieved through various methods, including personal loans, balance transfer credit cards, and home equity loans. Each option comes with its pros and cons:

• Personal loans: These can be used to pay off multiple debts, leaving you with one monthly payment. They often have lower interest rates than credit cards but may require good credit to qualify.
• Balance transfer credit cards: These cards offer low or zero interest rates for an introductory period, making them suitable for consolidating credit card debt. Be aware of the transfer fees and the standard interest rate after the introductory period ends.
• Home equity loans: If you own a home, you can borrow against the equity to pay off debts. These loans usually have lower interest rates but come with the risk of losing your home if you default.

Check for prepayment penalties

Before consolidating, check if your current debts have prepayment penalties. Paying off loans early can sometimes trigger these fees, which would add to your costs and could negate the benefits of consolidation.

Create a repayment plan

Consolidation alone won’t solve debt problems; a solid repayment plan is crucial. Determine how much you can realistically pay each month towards your consolidated debt. Stick to this plan to pay off the debt within the loan term, avoiding extending the debt unnecessarily.

Avoid accumulating new debt

While paying off your consolidated debt, it’s crucial to avoid taking on new debts. Keep credit card usage to a minimum and avoid additional loans. This discipline is essential for successfully getting out of debt.

Consider financial counselling

If you’re overwhelmed, consider seeking advice from a financial counsellor. They can provide personalised advice and help you understand the implications of different consolidation options.

Monitor your credit score

Debt consolidation can impact your credit score in various ways. Monitor your credit score to understand these impacts and manage your credit health during and after the consolidation process.

Read the fine print

Before agreeing to any consolidation loan, read the terms and conditions carefully. Understand the interest rates, fees, loan terms, and any potential penalties.

---

Effective debt consolidation requires careful consideration and disciplined financial management. By understanding your options, creating a realistic repayment plan, and avoiding new debt, you can successfully manage and reduce your debt load.

Remember, consolidation is a tool to help you manage debt more effectively, not a means to incur more debt.

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• Yes

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Debt consolidation is a strategic approach to managing multiple debts by combining them into a single, more manageable loan.

Write comment (0 Comments) " ["jcfields"]=> array(9) { [1]=> object(stdClass)#10073 (33) { ["id"]=> int(1) ["title"]=> string(17) "Automatic tagging" ["name"]=> string(17) "automatic-tagging" ["checked_out"]=> NULL ["checked_out_time"]=> NULL ["note"]=> string(0) "" ["state"]=> int(1) ["access"]=> int(1) ["created_time"]=> string(19) "2018-08-29 05:26:30" ["created_user_id"]=> int(2355) ["ordering"]=> int(-1) ["language"]=> string(1) "*" ["fieldparams"]=> object(Joomla\Registry\Registry)#9762 (3) { ["data":protected]=> object(stdClass)#9578 (1) { ["options"]=> object(stdClass)#9580 (2) { ["options0"]=> object(stdClass)#9581 (2) { ["name"]=> string(3) "Yes" ["value"]=> string(1) "1" } ["options1"]=> object(stdClass)#9579 (2) { ["name"]=> string(2) "No" ["value"]=> string(1) "0" } } } ["initialized":protected]=> bool(true) ["separator":protected]=> string(1) "." } ["params"]=> object(Joomla\Registry\Registry)#9761 (3) { ["data":protected]=> object(stdClass)#9576 (6) { ["hint"]=> 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["alias"]=> string(65) "credit-cards-or-personal-loans-what-s-best-for-debt-consolidation" ["introtext"]=> string(156) "

When it comes to debt consolidation, Australians have several options at their disposal. Among the most common are credit cards and personal loans.

" ["fulltext"]=> string(4518) "

Each has its own set of advantages and potential pitfalls, and the best choice often depends on an individual’s financial situation and goals. Let’s break down both options to help you decide which is best for consolidating your debts.

Credit cards for debt consolidation

Using a credit card to consolidate debt typically involves transferring balances from multiple high-interest cards to a single card with a lower interest rate, often a card with a 0 per cent balance transfer offer. This can simplify your payments and potentially reduce the amount of interest you pay.

Pros:

• Promotional offers: Many credit cards offer introductory periods with 0 per cent interest on balance transfers. This can provide a window of opportunity to pay down your debt without accruing additional interest.
• One payment: Consolidating your debts onto a single credit card means you only have to worry about one payment, making it easier to manage.
• Flexibility: Credit cards offer flexible repayments with the option to pay more than the minimum due each month, which can help you pay off the balance faster.

Cons:

• Reverting interest rates: After the promotional period ends, the interest rate may revert to a higher rate than some personal loans, which could end up costing you more in the long run.
• Balance transfer fees: Some credit cards charge a fee to transfer your balances, which could negate some of the savings on interest.
• Credit score impact: Your credit score could be impacted if your credit card balance is close to the credit limit, as it increases your credit utilisation ratio.

Personal loans for debt consolidation

A personal loan for debt consolidation involves taking out a new loan to pay off multiple debts. This new loan often has a lower interest rate compared to the average rate on your previous debts, and it comes with a fixed repayment period.

Pros:

• Fixed interest rates: Many personal loans offer fixed interest rates, which means your repayments remain the same for the duration of the loan.
• Set repayment period: Personal loans have a defined term, which can assist with budgeting and ensure your debt is paid off within a specific time frame.
• Potentially lower rates: If you have a good credit rating, you may be eligible for a personal loan with a lower rate than your credit card, potentially saving you money on interest.

Cons:

• Upfront costs: Some personal loans come with origination fees or other upfront costs that should be considered when calculating the total cost.
• Less flexibility: Unlike credit cards, personal loans have fixed repayments and typically don’t allow you to redraw the balance you have paid off.
• Early repayment penalties: Some lenders charge fees for early repayment, which could discourage you from paying off your loan ahead of schedule.

What’s best for you?

The right option for debt consolidation will depend on various factors, including:

1. The amount of debt you have
2. Your current interest rates
3. Your credit score
4. Your ability to pay off the debt within the credit card’s promotional period
5. Your discipline with repayments

If you can pay off the consolidated debt during a credit card’s interest-free period, and you’re disciplined enough to stick to a repayment plan, a balance transfer credit card might be the way to go. However, if you prefer a structured repayment plan and a clear end date, or if you have a larger amount of debt, a personal loan might be more suitable.

It’s vital to crunch the numbers, taking into account all fees and interest rates, and to consider your financial habits. Whichever option you choose, the goal is to reduce the interest you’re paying and to get your debt under control. It’s wise to seek advice from a financial adviser to ensure that your choice aligns with your long-term financial strategy.

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• Yes

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When it comes to debt consolidation, Australians have several options at their disposal. Among the most common are credit cards and personal loans.

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The settlement of the robodebt class action has been approved by the Federal Court of Australia, meaning a further $112 million in compensation will be paid to approximately 380,000 Aussies.

" ["fulltext"]=> string(1778) "

The settlement of the class action against the Commonwealth government over the robodebt scheme, which saw Services Australia illegally issue debt collection notices to more than 370,000 Australians, was approved by the Federal Court of Australia on Friday morning.

An update from Gordon Legal to members of the robodebt class action case applauded the announcement.

“Gordon Legal and our clients are delighted that the settlement has been approved by the court, bringing closure for so many people who have been affected by the robodebt scheme.

“We hope that this outcome brings peace of mind and some certainty to all class action members and acts as a strong deterrent against similar callous welfare practices for both present and future governments,” Gordon Legal partner Andrew Grech said.

According to the law firm, under the settlement approval, a further $112 million in compensation will be paid to approximately 380,000 eligible Australians, including legal costs.

In addition, since the commencement of the class action, more than $1.7 billion in financial benefits has been returned to approximately 430,000 group members.

The benefits include the Commonwealth:

• refunding $751 million in repayments of invalid debts;
• dropping claims for $744 million in debts partially paid back; and
• dropping claims for $268 million in debts where no repayments had been made.

Services Australia began rolling out $721 million in refunds for the illegal scheme from July 2020.

Are you entitled to a refund from the scheme? Here’s what you need to do.

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• Yes

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The settlement of the robodebt class action has been approved by the Federal Court of Australia, meaning a further $112 million in compensation will be paid to approximately 380,000 Aussies.

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What exactly is robodebt? We’ve heard all the buzz, now it’s time to know what this controversial government scheme actually is. 

" ["fulltext"]=> string(6698) "

Unless you’ve been living under a rock, you’ve probably heard all the buzz about robodebt. The infamous government program has recently been making headlines, so it’s no surprise that Australians (as well as the rest of the world) have plenty of questions. 

Activists and critics call it robodebt, but how does this system actually work? 

What is robodebt?

To fully understand how the robodebt saga unfolded, we must first discuss how the controversial system came to be. 

The Department of Human Services, which oversees Centrelink, has been using an automated Employment Income Confirmation system to identify possible overpayments of welfare benefits. It’s a system that is designed to perform data-matching by comparing the averaged income data from the Australian Taxation Office against previously declared income information reported back to Centrelink by those that claim payments. Ultimately, the system was created to calculate the Centrelink payments people should get. 

But this system was only used as the starting point for assessing whether a person had been overpaid and has a recoverable debt. If a discrepancy was identified, a Centrelink officer would launch an investigation and ask the person to provide additional information about their income statement (e.g. a bank statement or a payslip). 

If the person could not provide the additional information requested, Centrelink would often contact the employer directly or write to the bank before deciding if they have been overpaid. After the assessment, it is only then that the Centrelink writes that person a letter, and says they must repay a certain amount of money.

 What went wrong? 

In July 2016, the system with human oversight was significantly minimised with the introduction of the Online Compliance Intervention (OCI) system. The system was widely criticised for utilising computer algorithms to collect debts against hundreds of thousands of welfare recipients without proper assessment. The raised debts from the faulty system were called robodebts.  

If the system detected a difference between the data that Centrelink and ATO have, a letter advising of a potential debt will be sent out to provide further detail about your income. However, if you did not reply, Centrelink will only use the information about your income from the ATO and average it over multiple fortnights to determine the debt. The automated data-matching technique then sent out computer-generated Centrelink debt notices to welfare recipients who had been potentially overpaid. 

People criticised this process because the income averaging system used by the ATO was not reflective of their actual income each fortnight for the debt period. This is because for most Centrelink payments, the amount a welfare recipient is entitled to depends on the income they received in the last fortnight and not based on annual income. 

People were automatically contacted if Centrelink estimated they have a debt of more than $1,000. However, reports showed that one in five debt letters sent was based on false information. Before the OCI system was in place, the average number of interventions were 20,000 annually. However, with the introduction of the robodebt system, the number surged to 20,000 per week. 

But the problem didn’t stop there. Centrelink debts were raised for payments made up to seven years ago, increasing the pressure and difficulty for people to prove they have not received compensation that was entitled to them if they could not provide old payslips or bank statements. 

How did the Amato case impact the system? 

 Since 2016, there have been calls from critics and welfare recipients to halt the robodebt due to the high number of errors and miscalculations found within and by the system. A report from ABC news estimated that the government incorrectly took around $721 million from over 400,000 people since the robodebt system was implemented, with some people receiving multiple notices. 

 In November 2019, the Victoria Legal Aid brought a case on behalf of welfare beneficiary Deanna Amato to ask the Federal Court to check whether the government acted on a lawful basis in raising her Centrelink debt by substituting her fortnightly reported earnings with averaged ATO income data and adding a penalty fee when they did not receive a feedback from her regarding the matter. 

The Australian government conceded that the averaging process using ATO income data was not a lawful way to accurately calculate a debt. 

The Amato case was followed by a class action from Gordon Legal on behalf of the many thousands of people with unlawful robodebts. In November 2020, the law firm announced that the federal government agreed to a settlement worth $1.2 billion. The amount included the $721 million the government had already agreed to repay in wrongfully collected debts announced in May 2020. The settlement included $112 million in compensation and a decision to drop a further $398 million in debts wrongly raised.

Are you entitled to a refund from the robodebt? Here’s a guide on what you need to do. 

The aftermath

Following the Federal Court class action, the government announced that all unlawful robodebts would be cancelled. People who have already paid robodebts will be refunded with the amount that they paid between July and November 2020. 

In the political sphere, Malcom Turnbull, who was the prime minister when the scheme was rolled out, apologised for the system. Current Prime Minister Scott Morrison also apologised for any “dismay and distress” caused by the robodebt scheme. Despite this, Government Services Minister Stuart Robert noted that “the Commonwealth has not accepted or admitted any liability in the matter”.

The federal government also announced that it would stop the income averaging part of the scheme. The Labor Party and the Greens are seeking to have the matter investigated by a royal commission.

For the latest news, updates and information about the robodebt saga, follow our social media accounts and explore nestegg. 

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• Yes

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What exactly is robodebt? We’ve heard all the buzz, now it’s time to know what this controversial government scheme actually is. 

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The federal government has agreed to a  “landmark” class action settlement worth $1.2 billion over its controversial robodebt recovery program, which raised automated debts against welfare recipients.

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The robodebt scheme has been widely criticised for using computer algorithms to raise debt against hundreds of thousands of Australians who are on welfare with little human overbite.

In May, the government indicated that it will be taking steps to refund $721 million from 470,000 debt notices – affecting 373,000 Australians – raised wholly or partially through its controversial robodebt scheme.

Stuart Robert MP, in his role as the minister for the national disability insurance scheme and minister for government services, released a statement at the time that said “the Morrison government takes its responsibility for upholding the integrity of Australia’s welfare system seriously”.

While Prime Minister Scott Morrison apologised in Parliament for “hurt or harm” caused by the process back in May.

Yesterday’s settlement includes that amount, plus $112 million in compensation and a decision to drop a further $398 million in debts wrongly raised.

Gordon Legal, which represented the Centrelink recipients who had been forced to pay back money under the “unlawful” scheme, said the parties had reached an agreement which, if approved by the Federal Court, will see $1.2 billion in total delivered to participants in the legal challenge since it started, including $112 million in compensation. 

The firm noted that, in settling the class action, “the Commonwealth has not admitted that it was legally liable to group members”.

“We want to acknowledge the courage of the lead applicants; Katherine, Elyane, Steven, Felicity, Shannon and Devon, who led these proceedings on behalf of all robodebt victims in pursuit of this class action, which has allowed this outcome to be achieved today,” Gordon Legal partner Andrew Grech said.

“Our clients have asked us to especially thank Bill Shorten for his relentless pursuit of this issue, for his compassion over the last four years for vulnerable Australians hurt by robodebt and for bringing the case to Gordon Legal’s attention when it seemed that all other options had been exhausted and only resorting to the legal system would help.”

Mr Grech further acknowledged the work of the legal team at Victoria Legal Aid, whom he said worked tirelessly to bring a number of individual claims before the Federal Court before the class action was commenced, as well as the efforts of many community legal services in the Welfare Rights Network, such as Social Security Rights Victoria, who have been advocating for victims of robodebt for the last few years.

Shadow minister for government services Bill Shorten said in a statement that Labor would continue to push for a royal commission into robodebt.

The class action, launched on behalf of people who received notices through the automated debt recovery process, was launched last year with senior partner Peter Gordon making the announcement along with Mr Shorten. It comes after pressure over the federal government’s “15,000 mistakes” borne out of the automated system.

Services Australia began rolling out $721 million in refunds for the illegal scheme from July 2020.

Are you entitled to a refund from the scheme? Here’s what you need to do. 

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• Yes

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The federal government has agreed to a  “landmark” class action settlement worth $1.2 billion over its controversial robodebt recovery program, which raised automated debts against welfare recipients.

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