Risk Solutions

With an evolving risk landscape and growth in technological innovation, it’s vital to stay informed. 

Equifax Risk Solutions provides the insights businesses need to make highly informed decisions helping to identify, measure and mitigate risk.

Access our articles and free resources for insights into the power of data and analytics in helping you make better risk decisions.  Shift your perspective.

How Data Analytics Helps Retailers
22nd Jan 2024

Data analytics to retailers is like a microscope to a scientist – revealing details and patterns in consumer behaviour that otherwise remain unseen. For online retailers, data analytics can mean the difference between guesswork and precise knowledge about what works. Between maintaining the status quo and adapting to dynamic market changes. Between losing revenue to fraudsters and safeguarding profits.

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Combating cybercrime may now be the single most crucial risk-management activity for every Australian company. 

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Wherever there is data, there are answers. But there are right answers, and there are wrong answers.

Good-quality data can be relied upon to give valuable insights for better decision making, but the same can't be said of low-quality data. Data that is incomplete, dated or not fit for purpose can result in inaccurate or misleading outcomes.

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Australian-based global software company, Inspect Real Estate (IRE), could see a need to make the tenant application and screening process faster and easier for property professionals and property seekers. 

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Every year from 2011 to 2021, Equifax has solicited the views of credit managers around Australia to gain insight into credit risk management practices, sentiments and trends. A decade of data provides a unique perspective of the past, the present, and the future of credit management in Australia. Here, we look at where the industry is heading and how it has transformed, including the impact of COVID-19.

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Digitalisation is driving innovation in many areas of credit evaluation, and credit scoring is no exception. 

Data availability is exploding, consumer expectations are rising, and analytic capabilities are rapidly advancing. It's a heady mix that is bringing about transformational improvement to the accuracy of credit scores.

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Many a credit officer wishes they could stop SME customer drop-offs during the loan acquisition process. Many a bank customer service rep craves to avoid badgering their customers for financial paperwork that they have neither the time nor inclination to gather. 

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There are some updates coming to the Document Verification Service (DVS) and the Commonwealth electoral roll that may impact how you use IDMatrix.

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Cybersecurity readiness doesn't come easily. Reacting to a security breach is vastly different from being ready to act should a breach occur. Many organisations haven't previously focused on proactively protecting their critical information assets, but change is coming. The increased sophistication of today's threat actors heightens the chances that more organisations will find themselves the unlucky targets of cybercrime.

 

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A potential borrower with no defaults but a poor repayment history applies for a loan with a lender who uses only negative bureau data in their credit decisioning. Other things being equal, their application is likely to be approved. The same borrower applies to a lender with access to Comprehensive Credit Reporting (CCR) data, only to have their application rejected. 

The difference? One lender made their decision based solely on negative-only credit information like defaults, bankruptcies and the number of credit enquiries. The other lender made their decision based on both negative and positive CCR data. This lender could see that the applicant had a history of paying late and had many loans with multiple lenders.

 

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Rejecting a loan applicant because there is not enough information on their credit file to determine their risk can mean giving away a creditworthy customer. 

In today's disrupted marketplace, where customer-centricity and growth are crucial, there is a significant benefit to separating the likely good borrowers from the likely bad borrowers among those with limited credit history.

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