Insurer keeps human touch to the fore as it streamlines claims
Insurer Suncorp says it builds ethical considerations into its uses of artificial intelligence from the outset.
'While we are exploring a portfolio of use cases, we are fully aware of the associated ethical challenges and risks that accompany the GenAI technology,' says Priyanka Paranagama, Suncorp's chief technology officer.
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AU Financial Review
a day ago
- AU Financial Review
Smarter, relevant search is reshaping the future of generative AI
'But at the same time, I'm already seeing countless examples of how Australian businesses are putting the technology to work in meaningful ways.' Relevance is the missing piece Among the early adopters is one of the nation's largest banks, Macquarie, where relevancy breakthroughs are helping deliver smarter digital services. Macquarie Bank's chief digital officer Luis Uguina says search has become a strategic lever. 'Leveraging GenAI's ability to provide contextually relevant and highly personalised search results has significantly reduced the time it takes to retrieve and extract critical information, both for our customers and internal teams,' says Uguina. That shift is freeing employees from repetitive tasks so they can focus on innovating and continuing to improve customer experiences. 'Customers now receive answers that are not only accurate but also aligned with their specific needs and preferences,' Uguina says. 'That's resulted in increased engagement and satisfaction, with noticeable improvements in metrics like customer recommendation scores.' For GenAI to deliver this kind of value, speed and scale are not enough. Relevance - in context, in real time - is what makes the difference. 'There will, of course, be challenges along the way,' says Pell. 'While we're seeing lots of successful GenAI use cases, an organisation's approach to data management can pose significant challenges to the success of its projects.' And the shift is happening across sectors. In mining, BHP is using GenAI to analyse complex, interdependent operational variables. In retail, Coles is extracting insights from thousands of customer survey comments. In finance, firms like Macquarie are anticipating user intent with precision. Underpinning these advances are techniques like retrieval-augmented generation (RAG), which enhance LLM responses with proprietary data. By feeding AI systems with business-specific context, RAG helps organisations move beyond generic outputs. It allows them to use their own internal knowledge base to improve accuracy and usefulness. 'All organisations have a responsibility to mitigate security risks, eliminate blind spots in their security posture and identify and respond to threats quickly,' Pell says. For Macquarie, proprietary data is a cornerstone of their AI strategy. Ashwin Sinha, the bank's chief data and AI officer, says it gives the organisation a competitive edge. 'Proprietary data plays a crucial role in enhancing search outcomes by providing unique insights,' Sinha says. 'It allows us to deliver more accurate, relevant and personalised results, tailored to the specific needs of our customers.' Macquarie's internal datasets are used to model customer intent and streamline service workflows. 'It means we can anticipate user needs more effectively and provide results that are not only accurate but also contextually meaningful,' Uguina says. But it's not just about performance - trust and governance remain key. 'We ensure that the use of proprietary data is handled responsibly, adhering to strict privacy and ethical guidelines to maintain trust with our customers,' Sinha says. Solving for complexity and compliance Getting to that point has meant solving for both complexity and compliance. 'One of the primary challenges we encountered was balancing the complexity of advanced search algorithms with the need for speed, accuracy and efficiency,' Sinha says. Optimising infrastructure, adopting distributed computing, and building in privacy protections such as encryption and differential privacy were part of the solution. 'We implemented rigorous testing and validation processes, as well as ongoing audits of our algorithms,' Sinha says. Transparency and user feedback loops were also built in to detect and address any unintended outcomes quickly. The payoff has been measurable. Uguina says GenAI-based search techniques have improved the customer experience and internal operations. 'One of the most notable outcomes has been a substantial improvement in our digital experience, with user satisfaction increasing and our online help resources more useful for our customers,' says Uguina. At the enterprise level, search is also streamlining knowledge retrieval. 'It has enhanced enterprise knowledge retrieval by surfacing actionable insights from vast datasets,' Sinha says. 'That's improved decision-making and increased operational efficiencies.' Elastic's Pell says this type of capability is now essential. 'Most businesses have vast amounts of structured and unstructured data, and the key to unlocking tremendous value from both is to be able to find, analyse, and use data from any source in real time,' Pell says. This is particularly evident in customer-facing applications. While many companies began with GenAI-powered chatbots, more advanced use cases are now emerging. In retail, this includes intelligent product recommendations and real-time sentiment analysis. In financial services and telecoms, it's about speeding up transactions and supporting staff with personalised data. 'There is also a role for generative AI in transactions where human-to-human interaction remains vital, by enabling call centre staff and bank tellers to access relevant, up-to-date data fast and efficiently, giving them the real-time insights they need to resolve issues faster and keep wait times to a minimum,' Pell says. 'It can also provide these employees with personalised recommendations to pass on to their customers.' Security is another area seeing rapid change. With cyber threats on the rise, organisations are starting to use GenAI and search to boost their defensive posture. According to the Australian Signals Directorate, financial losses from cybercrime continue to grow, with average costs per incident reaching $30,700 last financial year. Security teams are using AI-enhanced search to surface relevant signals faster and receive guided recommendations for action. 'Having a search platform helps modernise security operations by providing greater context that includes both public and private data related to security issues,' Pell says. Despite the promise, businesses remain mindful of the risks. Concerns around bias, data sovereignty and regulatory uncertainty are front of mind, especially in sectors like finance, health and government. Pell notes that while GenAI offers clear benefits, many organisations remain unsure how to proceed because 'the absence of specific regulations in this country creates uncertainty regarding compliance', particularly in sectors such as banking, healthcare and the public sector, which must still align new models with APRA's stringent data protection guardrails. Sinha agrees that governance is crucial. 'Advanced search techniques often rely on very large datasets, which can sometimes introduce biases or inaccuracies,' he says. For that reason, Macquarie invested early in frameworks to monitor fairness and build privacy-preserving systems. Even with these guardrails, the momentum is clear. Elastic research shows 88 per cent of Australian IT decision-makers expect to increase their AI investment. The Tech Council of Australia estimates GenAI could add $115 billion to the economy annually by 2030. The next frontier - conversational AI Looking ahead, Macquarie's Uguina sees conversational, intent-aware search as the next frontier. 'Generative AI is making it possible for users to interact with search systems in a more natural, dialogue-like manner,' he says. 'That evolution is transforming search into a more dynamic and personalised experience.' Sinha says the implications for decision-making are profound. 'AI allows us to process vast amounts of data - from transaction histories to market trends - and surface insights that were previously inaccessible,' he says. 'It also enables better risk management by detecting anomalies or threats in real time.' Ultimately, Uguina says, it's about shifting from reactive to proactive. 'With advancements in machine learning and AI, banks will be able to anticipate the needs of their customers before they arise,' he says. 'This shift will make banking not just a transactional experience but a truly supportive one.' As generative AI continues to evolve, the real differentiator will be its ability to deliver relevant, timely, context-aware outcomes. Organisations that get search right won't just improve productivity - they'll unlock entirely new ways to serve, protect and engage their customers.
AU Financial Review
02-06-2025
- AU Financial Review
Insurer keeps human touch to the fore as it streamlines claims
Insurer Suncorp says it builds ethical considerations into its uses of artificial intelligence from the outset. 'While we are exploring a portfolio of use cases, we are fully aware of the associated ethical challenges and risks that accompany the GenAI technology,' says Priyanka Paranagama, Suncorp's chief technology officer.
Sydney Morning Herald
08-05-2025
- Sydney Morning Herald
Why this long-serving bank boss can sleep better at night
Outgoing ANZ Bank boss Shayne Elliott says moves during his tenure to sell dozens of businesses and slash the number of major corporate clients on the bank's books will set it up for a more volatile world and the next inevitable financial crisis. Elliott, who will be replaced by Nuno Matos next week, delivered his last result as chief executive on Thursday, as the bank posted flat half-year profits of $3.6 billion. After more than nine years leading ANZ, Elliott cited a phrase often used in the industry – that in banking, it's better to be 'boring' – especially when the world is heading into a more disruptive era of rising geopolitical tensions and the unwinding of globalisation. As CEO, Elliott made major shifts at ANZ including selling about 30 non-core businesses and scaling back ANZ's presence in Asia; shrinking the number of big business clients on its books; and buying Suncorp's retail bank for $4.9 billion. The Melbourne-based bank has also been slapped with a $1 billion capital charge over governance failings in its markets division, and critics say its digital transformation has been underwhelming. Elliott, the longest-serving current big four bank boss, argued changes under his tenure had made ANZ a less risky and simpler bank, and it was much more picky about its biggest clients than when he joined as the head of ANZ's institutional bank in 2009. He said at that time, the 10 biggest clients of the bank were 'vibrant and exciting', but higher-risk and 'not a world for banks'. Loading 'I think banks are much better to be boring,' he said. 'I'd be very happy to say we're boring and safe in terms of our customer selection, and I sleep better at night because of that, and I know our shareholders do.' During Elliott's time as CEO, banks have also faced major changes from events including the COVID-19 crisis and what Elliott called the industry's 'crisis around culture' – the 2018 royal commission into banking misconduct.
