Fintech
Exploring the interplay between data, risk and fraud at Fintech Week London
The growing focus on data, risk and fraud is driving a transformative shift in the financial technology industry.
The integration of advanced data management and risk mitigation strategies is creating a synergy that not only strengthens traditional financial processes, but also introduces new and robust mechanisms to combat fraud, safeguarding the digital economy from ever-evolving threats.
TO Fintech Week LondonThe conference’s flagship panel, “Data, Risk, and Fraud,” shed light on three of the most pressing issues in the financial technology industry.
Moderated by Gina ClarkeDirector of European content at Money 20/20, the session featured insights from Zahra ShahBoard member and co-founder of NexaQuanta, ICO, TeamUp Ventures and Seers, and Karen Zhangpartnership with fintech leaders and VCs at Google Cloud UK.
Their discussion explored the critical connections between data management, risk mitigation and fraud prevention in today’s digital economy.
The importance of these issues is evident from the statistics. on line losses due to payment fraud According to Juniper Research, they are expected to exceed $206 billion in the next five years. After all, this is revealed by the Global Data Protection Index 65% of global businesses have suffered major data breaches in the last two years.
These alarming figures not only framed the conversation, but also highlighted the urgent need for robust data security and fraud prevention strategies.
Connecting the dots: data, risk and fraud
The discussion opened with an in-depth look at the correlations between data, risks and fraud.
“With the explosion of digital assets and data usage, there is an inevitable link between these elements,” Zhang noted. The growing volume of digital transactions naturally intensifies these connections, highlighting the need for businesses to build resilient systems to manage evolving threats.
“Companies are focused on building robust systems and infrastructure to handle these challenges,” he added.
Shah reinforced this point of view, highlighting the importance of data efficiency in risk management. He emphasized that “organizations need a unique data strategy because different types of data require different governance. The ICO reports that 80% of data breaches are due to GDPR privacy issues, and 60% of these are due to simple errors such as failing to update passwords or using two-factor authentication” .
Shah also highlighted the importance of technical measures and ongoing employee training to keep up with evolving regulations and prevent human errors.
The regulations that fuel innovation
While regulations are often seen as constraints, they can also spur innovation. Shah praised the UK’s principled approach AI regulationwhich he compared with the EU risk-based methodology.
“The UK Artificial Intelligence Bill, currently in Parliament, could set a global standard by encouraging innovation while ensuring safety. This approach is more adaptable to rapid advances in AI technology,” she explained.
Zhang stressed that compliance with regulations such as the GDPR and the upcoming Digital Operational Resilience Act (Dora) is crucial for fintech companies aiming for global expansion.
“Regulations provide a framework that can effectively promote innovation. For example, Monzo is leveraging these facilities to ensure their expansion into new regions such as the US is safe and compliant.” Compliance with these regulatory frameworks not only protects businesses, but also strengthens customer trust, which is critical in the digital age.
The financial imperative for compliance is strong. Data from the European Banking Authority (EBA) shows that failure to comply with regulations such as GDPR can lead to fines of up to 4% of annual global turnover. THE EBA It also finds that comprehensive regulatory frameworks can reduce incidents of fraud by up to 30%, reinforcing the panel’s case for the benefits of regulations.
Creating a resilient future
The discussion then moved on to practical strategies to strengthen resilience against data breaches and fraud. Zhang recommended integrating site reliability engineering practices from the beginning. He advised that “startups should consider multi-tenancy, regional scalability and latency from the start. Collaboration with suppliers can provide the guidance needed to build scalable and repeatable structures.”
Shah added that focusing on responsible AI and privacy practices by design is essential from the start, noting that “it is difficult to fix problems later, especially with large language models that may contain bias. Starting with responsible AI practices ensures long-term sustainability and trust.”
He also highlighted the role of artificial intelligence in improving fraud detection and KYC (Know Your Customer) processes. “AI can accelerate data analysis and automate processes, reducing false positives and improving detection of suspicious activity,” she explained.
In support of the speakers’ arguments, a report from Accenture states that artificial intelligence could help financial institutions save up to $31 billion by 2025 through improving fraud detection and operational efficiency. Additionally, according to a report from the World Economic Forum, AI-powered KYC processes can reduce customer onboarding times by up to 90%.
Karen Zhang concluded by highlighting the need for ongoing training and internal support to keep up with rapid technological and regulatory changes.
“Organizations need to better support their employees, possibly using artificial intelligence to conduct research and enforce policies. It’s about balancing innovation with caution, ensuring teams are well equipped to manage the changing landscape,” she said.
In concluding the discussion, panelists agreed that the fintech industry is at a crossroads where robust data management, rigorous regulatory compliance and innovative risk management strategies converge. As digital transactions continue to increase, so too does the need for fintech companies to take global, forward-thinking approaches to data, risk and fraud.