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Why Smart AI Starts with Smarter Data

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Getting the Most Out of Your AI by Improving the Quality of Your Data
AI is transforming how payments businesses, financial institutions, and corporates operate by improving efficiency, fraud monitoring, and customer experience. The value AI delivers hinges on the quality of the data it processes, a key theme discussed at Cuscal’s Curious Thinkers 2024 event.

AI applications are already making an impact in financial services with customer service bots, predictive analytics, and fraud monitoring systems. According to the Wall Street Journal, businesses are already using AI to provide personalised offerings to clients, identify clients, and identify fraud in real-time.

AI adoption in financial services is accelerating, with a recent ASIC review identifying 624 AI use cases across banking, credit, insurance, and financial advice. Over half (57%) were developed in the past two years or still in progress, and 61% of licensees plan to expand AI use within the next year. This momentum reflects the sector’s commitment to leveraging AI-driven solutions to stay competitive and deliver enhanced value to customers.

These advancements are delivering measurable benefits, but they are only as effective as the data that supports them. As IBM notes, poor-quality data can undermine AI initiatives, leading to unreliable outputs and heightened business risk.

The Opportunity for Payments Businesses
Generative AI is reshaping industries, offering both economic and operational advantages. J.P. Morgan Research estimates that generative AI could boost global GDP by as much as 10%, adding between $7–10 trillion to the economy. Over the next few years, it is also expected to drive a significant surge in workforce productivity.

Closer to home, AI adoption is delivering tangible economic benefits for Australian businesses. Recent research from Microsoft and Mandala estimates that by 2035, the AI economy could generate $18.8 billion in annual revenue for Australia. Additionally, businesses investing in generative AI are seeing a $3.50 return for every $1 spent, often within just 14 months.

The success of these AI systems, however, hinges on the quality of the data driving them. AI tools process enormous amounts of datasets to generate insights. When those datasets are incomplete, inaccurate, or poor quality, the results can be unreliable—or worse, damaging.

The Quality Question
Payments providers and financial institutions handle vast amounts of data every day. From transaction histories to customer profiles, this data feeds into AI models that help businesses make smarter decisions and optimise operations.

When data quality is neglected, the consequences can ripple across the organisation and may contribute to:   

  • Misjudged risk assessments, leading to financial losses or missed opportunities 
  • Flawed market insights, resulting in poor investment decisions
  • Inaccurate customer recommendations, damaging trust and satisfaction

As AI adoption accelerates, so too does the importance of ensuring data is accurate, complete, and relevant. Details that might have been overlooked in the past—such as timestamps or metadata—now play a critical role in delivering reliable AI outputs.

Steps to Improve Data Quality
Investing in data quality is critical for payments businesses aiming to leverage AI effectively. Taking action in these areas can make a significant difference:

1. Data cleaning: Removing or correcting errors ensures accuracy and improves performance. IBM highlights how this step reduces risks and enhances results.
2. Data governance: Establishing clear processes for collecting, storing, and managing data creates consistency and reliability.
3. Regular monitoring: Ongoing audits help identify and fix data quality gaps before they affect AI outputs.

By addressing these challenges, organisations can unlock smarter decision-making, better customer outcomes, and a competitive edge. Because high-quality data isn’t just a technical asset—it’s a strategic one.

The Future of AI in Payments
The payments industry is evolving rapidly, with AI playing an increasingly important role in shaping it’s future. Organisations ready to invest in data quality will be the ones leading the way.

References
Australian Securities & Investments Commission, ‘Beware the gap: Governance arrangements in the face of AI innovation, Report 798’, Australian Securities & Investments Commission website, report, October 2024, accessed 10 January 2025,<https://download.asic.gov.au/media/mtllqjo0/rep-798-published-29-october-2024.pdf>

Belle, L 2024, ‘These New AI Bots Will Do Just About Anything for You’, Wall Street Journal, article, 24 August 2024, accessed 10 January 2025,<https://download.asic.gov.au/media/mtllqjo0/rep-798-published-29-october-2024.pdf>

Bousquette, I 2024, ‘Visa Has Deployed Hundreds of AI Use Cases. It’s Not Stopping’, Wall Street Journal, article, 1 November 2024, accessed 10 January 2025, <https://www.wsj.com/articles/visa-has-deployed-hundreds-of-ai-use-cases-its-not-stopping-4febe1b4>

J.P. Morgan, ‘Is generative AI a game changer?’, J.P. Morgan website, global research, 14 February 2024, accessed 10 January 2025,<https://www.jpmorgan.com/insights/global-research/artificial-intelligence/generative-ai>

|Microsoft, ‘New research identifies Australia’s most promising opportunities in the new global AI economy’, Microsoft website, features, 7 November 2024, accessed 10 January 2025, <https://news.microsoft.com/en-au/features/new-research-identifies-australias-most-promising-opportunities-in-the-new-global-ai-economy/>

Rogers, J 2024, ‘What Is Data Cleaning?’, IBM website, article, 29 November 2024, accessed 10 January 2025,<https://www.ibm.com/think/topics/data-cleaning>

Why Leadership Holds the Key to AI-driven Growth

Lady standing with her arms folded.

CEOs are crucial to maximising the benefits of AI
The rise of AI opens up exciting opportunities for payments businesses to grow quickly, but it also brings its share of challenges. CEOs are uniquely positioned to guide their organisations in using AI effectively and across the board.

The challenges of using AI to scale
One key learning from Cuscal’s Curious Thinkers 2024 event – scale is invaluable to businesses. Particularly when it comes to keeping their valued customers happy and creating the payment solutions of the future.

We are living in exciting times. New technology—especially AI—has kicked open the door of opportunity for businesses, offering new pathways to expand and grow.

According to Accenture’s report on the state of AI Maturity, scaling with AI comes down to mastering a set of key capabilities in the right combinations—not only in data and AI, but also in organisational strategy, talent and culture. To maximise its potential, it must be applied effectively across the business as a whole, ensuring:

  • the use of AI supports the overall business objectives,
  • innovation and creativity are encouraged, and
  • everyone is on board with the approach, from leaders to teams.

If you are currently using AI for small projects, the thought of transitioning to widespread use might be overwhelming – it can be a formidable task.

Many businesses operate in silos, which can lead to mixed efforts, poor communication, and inefficiencies. AI initiatives often highlight these problems even more.

There can also be fear around AI—it can feel complex and risky. To succeed, it’s crucial to get everyone in the organisation to understand and support its value.

CEOs must lead the way
Scaling doesn’t happen without teamwork, but the CEO plays a critical role in its success.

As the person with the big-picture view, the CEO has the influence needed to break down the barriers between teams and keep everyone focused on their shared goals.

In fact, a study from Accenture found that when CEOs lead AI efforts, companies tend to see better results because they are uniquely positioned to:

  • Set a clear vision for what AI can achieve,
  • Build trust and confidence in the technology, and
  • Ensure AI projects are part of the larger business strategy.

The same study also reported that when leaders believe in AI early on, not only is adoption accelerated, it also drives positive changes across the business. This highlights the CEO’s crucial role as both a guide and a champion for AI.

Turning opportunity into action
Recent articles in IT Wire and IT News highlight an exciting turning point for Australian businesses. With groundbreaking technological shifts, the opportunities to unlock new growth are immense—and bold CEO’s are leading the charge.

Telstra’s CEO, Vicki Brady, has implemented AI tools including AskTelstra and One Sentence Summary to enhance customer service. Similarly, Wesfarmers’ CEO, Rob Scott, introduced AI-enabled technology in Bunnings delivering real-time product information, improving both customer experience and operational efficiency. These stories underscore how decisive leadership is driving innovation and shaping the future of business.

References:
Accenture: The Art of AI Maturity | Accenture
IT Wire: iTWire – Telstra scales up AI adoption following ‘promising pilots’ of generative AI solutions improving customer experience
IT News: ‘Wesfarmers goes deeper into AI and digital

How to Build your AI Rulebook

Artificial Intelligence (AI) is fast becoming a feature of Australian business – whether senior management likes it or not. And as employees become more comfortable with tools like ChatGPT, businesses will need to create, implement and enforce rules to govern its usage.

The AI Train Has Left the Station  
One of the central themes to emerge from Cuscal’s flagship thought leadership event, Curious Thinkers 2024, was the rapid adoption of AI technology by Australian workers, many of whom are already using it in their daily tasks.  Research commissioned by Salesforce and Slack reveals that 53% of Australian professionals are actively using or experimenting with generative AI in their work environments, a notable increase from 36% in 2023. Alarmingly, 44% of employees in Australia are utilizing generative AI without the oversight or permission of business leaders, according to research conducted by automation specialist technology firm UiPath, which surveyed over 1,100 Australian workers.

During the Curious Thinkers 2024 session titled The Future of Operating Models and Workforce Shifts in the Age of AI, the panel discussed that there can certainly be benefits from employee AI experimentation and agreed that employees are often best placed to identify where AI can improve day-to-day tasks and unlock efficiencies. But without proper guidance, a ‘cowboy’ attitude to AI deployment carries numerous risks, including compliance breaches, data privacy violations, and misaligned business objectives.

Playing by the Rules 
Businesses need to develop and implement guidelines or policies for AI usage even if they’re not using the technology in any official capacity – because studies show that employees are using it without being expressly permitted.

These rulebooks will vary between businesses, but some of the ideas touched on by the panel include: 

1. Program usage 
Businesses must clearly specify which AI programs can be used by employees. This ensures that all AI tools are vetted for quality, safety, and compliance – reducing the risk of unsanctioned AI use. 

2. Data integrity 
Businesses need to define what data can be used as input for the AI. This is crucial for maintaining data privacy and security, and for ensuring that the AI operates within its intended parameters. 

 3. Train and customise 
For an AI tool to be truly fit for purpose, it needs to be trained on a business’s own data so it can refine and optimise its output. This even extends to off-the-shelf AI solutions, which should be trained using internal data to help give context to the work being done.  

 4. Align with business goals 
All AI experiments and use cases should be in direct alignment with the business outcomes that the business is driving. This helps to ensure that AI usage contributes to the overall objectives of the business, rather than becoming a distraction.

Lead, Don’t Follow 
Each payments business will need to consider its own operational structures and reporting lines. This will ensure that any AI experiments are being conducted appropriately, and that successful ones can be developed and further implemented across the organisation.   

Ultimately, the exact shape of these rules and reporting lines will depend on individual business goals, but these four common themes should provide a useful starting point for executives looking to shore up their AI practices.  

AI Adoption in Australia

  • Generational Divide: Adoption rates show that 63% of Millennials, 57% of Generation Z, and 44% of Generation X are leveraging generative AI technologies compared to just 20% of Baby Boomers . This indicates that younger generations are more likely to embrace AI technologies in their daily and professional lives.
  • Business Integration: According to an independent survey commissioned by business loan comparison platform Small Business Loans Australia 60% of Australian businesses are already using or planning to integrate AI into their operations over the next two years, with 37% having adopted it already.
  • Productivity Gains: Embracing the use of AI to improve existing processes and enhance platforms is the safest place to start your generative AI journey and deliver incremental benefit over time.

These statistics highlight not only the rapid growth and integration of AI within Australian workplaces but also emphasise the necessity for organisations to take proactive steps to ensure they harness these tools effectively while safeguarding compliance and aligning with strategic goals.