Financial fraud is increasing around the world, putting both mature and emerging digital economies at risk. The overall global economic impact of financial crime has been estimated to be $5 trillion. Furthermore, according to the 2024 Nasdaq global financial crime report, fraud losses totalled $485.6 billion worldwide. This from fraud scams and bank fraud schemes alone. As such, organisations face a series of challenges, from eroding profit margins to reputational risks to data breaches.
Many factors contribute to this growing wave of fraud. For example, digitisation in banking has created new opportunities for bad actors. With more identity data existing online, attack surfaces have expanded. Hackers now have more possible entry points to exploit vulnerabilities.
At the same time, new technologies, like machine learning (ML), artificial intelligence (AI), and automation are enabling bad actors to innovate faster and evade detection more effectively. AI, in particular, is a double-edged sword. While many businesses use the technology to improve efficiency and decision-making, it also gives bad actors a helping hand. Deepfakes and social engineering, for example, enable them to impersonate individuals with uncanny realism.
Additionally, cybercrime – especially financial crime – is becoming more sophisticated. Today, over two-thirds of financial institutions admitting they’re unprepared to defend against the rising wave of attacks.
Counting the many costs of fraud
Rising fraud creates challenges at local, national, and global levels. Financial loss is, obviously, a primary concern. But financial loss is only part of the total cost of cybercrime. Fraud also brings reputational damage, increased risk of data breaches, and potential legal consequences.
As organisations devise new strategies to tackle rising fraud, they must also heed regulatory requirements. Namely, Anti-Money Laundering (AML) registration, as well as other standards for privacy and consent. These regulations create further challenges for organisations as they aim to uphold rigorous compliance requirements without impacting sales, operating costs, or the customer experience.
It’s time for a different approach to fraud detection
On both local and global levels, mounting fraud threatens economic growth. In its Plan for Change, the UK government has recognised global co-operation will be necessary to tackle fraudsters. However, existing security strategies are too fragmented to suit the needs of diverse markets.
Emerging economies, for example, often lack mature controls, making them inherently vulnerable to hackers. Yet, with smaller digital infrastructures, they’re also less attractive targets for financial crime.
In contrast, more mature economies usually have stronger security defences. However, their larger digital ecosystems make them perhaps even more vulnerable to bad actors’ advances. After all, the more digital an economy becomes, the more fragmented and complex an individual’s identity and the more opportunities for bad actors to exploit or impersonate it.
Combatting fraud at a global scale requires going local
Considering the scale and sophistication of cybercrimes, combatting global fraud will require organisations to turn to localised data for more precise identity verification.
By integrating data from diverse, localised sources and tailoring fraud prevention strategies to market-specific risks, organisations can better detect fraud and establish identity trust. And in a way that both upholds the customer experience and promotes financial inclusion.
Combine credit, government, and digital data to enhance intelligence
Thwarting fraudsters begins with building intelligence to establish trust and verify presented identities. This is where localised data can help. By combining credit bureau data with government registries and digital signals, organisations can find a correlation across multiple digital identity attributes and digital risk signals to assess risk and enable real-time identity trust.
Credit bureau data associated with the presented identity can be used to determine risk and trust based on four vectors:
- The bureau footprint: information comprising records from multiple contributing organisations
- Activity history: evidence of recent and consistent payment activity
- Data consistency: personal data stability
- Application velocity: recent application history
Meanwhile, government information services and other registries can be incorporated to further cross-check the presented identity and strengthen verification.
By leveraging such a wide range of independent, localised data sources and correlating them with the presented identity attributes, organisations can significantly enhance intelligence to detect fraud without compromising the customer experience.
Tailor strategies to specific markets to support compliance and accessibility
It’s also important that organisations tailor their security and identity-verification strategies to the unique needs and maturity levels of specific markets. For example, in emerging economies, many people struggle to access financial services. This is often due to a lack of a formal credit history or other recognised financial records. Without this information, it can be a challenge for organisations to verify identity and reach trust decisions without inadvertently excluding legitimate users.
But by using localised data sources and market-specific strategies, organisations can make more informed decisions to bring more traditionally excluded parties into the financial system and promote broader financial inclusion without increasing risk or compromising security.
These targeted, market-specific fraud prevention strategies also help organisations with regulatory compliance. For example, for AML compliance, organisations must “identify, assess, and understand the money laundering and terrorist financing risk to which they are exposed.” Using localised data and market-specific strategies can help organisations meet this expectation by aligning fraud detection controls with region-specific threat intelligence.
Conclusion
Global financial crime continues to ramp up, creating new challenges for organisations to detect fraud, verify identities, and comply with regulations. But finding strategies to beat bad actors is made even more difficult by markets’ varying needs, maturity levels, and digital infrastructures.
To combat fraud and cyberthreats on a global scale, organisations should pivot to a localised approach. By combining credit, government, and digital data and tailoring fraud-prevention strategies to specific markets, they can enhance intelligence, maintain compliance, and better manage risk. In doing so, they can not only strengthen security but facilitate access to financial products and services for broader financial inclusion, worldwide.
- Cybersecurity in FinTech