Why Businesses Need Human Decision Support to Fight Digital Fraud
Digital fraud has escalated past the crisis point. A new study from Juniper Research say that the cumulative merchant losses to online payment fraud globally between 2023 and 2027 will exceed $343 billion. In the United States alone, more than $10 billion in losses from online scams were reported to the FBI in 2022, the highest annual loss in the last five years. But how can businesses fight digital fraud? Many businesses are investing in artificial intelligence (AI), but AI alone is not enough. They also need human judgment and emotional intelligence. The human factor can help enterprises take on fraudsters and beat them at their own game.
Modern fraudulent activities include money laundering, terror financing, payments fraud, account takeover, payments abuse, cyber threats, and more. Large organizations are typically turn to technology to fight fraud. For instance, they have:
- Used machine learning (ML) models to detect fraud patterns.
- Trained deep learning neural networks to predict and prevent fraud in real-time.
Fraud detection algorithms, complex business rules, ML models, advanced data analytics, rules and alerts are all amazing tools to prevent fraud. But they are not perfect. They do not have emotional intelligence. They do not think and react like humans.
For example, when a new pattern of fraudulent activity emerges, it might take days for the ML models to identify it, and teach itself to implement a preventive mechanism. Also, technology is not regional, cultural or ethnic in nature, so it cannot read the mindset, thought process and socio-economic factors to combat fraud emerging from different parts of the world. Even the most advanced neural networks find this too complex to achieve.
Another major challenge with technology is to ensure that customer experience is not affected when a business attempts to resolve potential fraudulent activity. Businesses need to react quickly without making it harder for customers to conduct legitimate transactions with a business.
The Solution: Human Decision Support
In order to better combat modern fraud, businesses need technology as the first and foremost line of defense. However, as fraudsters keep getting sophisticated, finding new loopholes in disconnected systems or unchecked processes, it is imperative to have qualified human decision support to partner with technology and mitigate fraud.
For instance, businesses need fraud analysts to review cases using static and dynamic indicators. They must evidence from multiple data sources, integrated systems, and third party-tools -- with a focus on inconsistencies and anomalies in the information.
Even the most advanced fraud prevention system with more than 98 percent efficacy might report:
- Unknown risk values. These are fraud threats that a system does not catch, which leads to loss.
- False positives. This happens when a fraud prevention system incorrectly classifies a person’s legitimate behavior as being suspicious. False positives can result in a customer being inconvenienced (such as having their debit card canceled or their account frozen).
This gap in the fraud prevention system can only be bridged using manual reviewers, which is why trained human beings are needed.
During this process, fraud analysts gain valuable insights to take informed decisions to detect newer fraud patterns, take required actions, and ensure zero impact on customer experience. The analysts also provide significant insights and regular feedback to ML teams and business teams to optimize their front-line technology to combat fraud and eradicate design flaws, if any.
Manual reviewers become even more critical for global businesses, as the fraud patterns and fraudster mindsets differ from region to region, and it becomes impossible to train the AI models on such parameters. Moreover, fraudsters are always inventing newer ways to bypass even the most advanced AI powered fraud prevention systems. So, it becomes even more crucial to add an extra layer of security in the form of a fraud analyst team.
A combination of right technology and a qualified team ensures that an efficient fraud prevention program will mitigate fraud losses and improve customer experience while continuously optimizing active learning and improving ML accuracy.
How Centific Can Help
Our approach to combating fraud consists of an AI platform that detects and classifies fraud complemented with a fraud squad of expert analysts equipped with a very high emotional intelligence, ensuring digital safety throughout your ecosystem.
The AI Fraud Protection Platform creates a circle of trust across the customer journey, from account protection and purchase protection, while protecting your business through loss prevention. Account protection mitigates account takeovers and purchase protection correlates the transaction patterns of potential bad actors performing fraudulent activity. Loss prevention detects anomalies throughout the transaction history, mitigating financial loss.
To learn more, download our white paper on fighting digital fraud and contact us.