How to improve fraud risk monitoring to tackle evolving threats

Fraud is evolving fast. Institutions must shift to proactive, data‑driven monitoring to stay ahead, protect customers and maintain trust.

In brief:

• Strengthen real-time fraud monitoring to detect risks earlier.
• Use clear metrics to guide faster, sharper decisions.
• Turn insights into action to mitigate fraud and boost trust.

Fraud in the financial sector is a persistent and growing threat, evolving in step with advancements in technology and being a key source of income for criminals. Today, public expectations are that financial institutions, regardless of size, not only respond when fraud occurs but also remain a step ahead, actively protecting their customers and their assets at every turn. 

However, failure to provide relevant and timely monitoring of fraud risks leaves institutions vulnerable, undermining both their defenses and customer confidence. While the larger institutions are at the forefront, strengthening their anti-fraud frameworks, small and medium-sized institutions and their customers risk lagging behind, thereby becoming prime targets for fraudsters. By advancing their fraud risk monitoring, institutions can not only safeguard their own operations but also build stronger, lasting relationships with their customers. 

In this article, we explore some actionable strategies for elevating fraud risk monitoring, helping enable institutions to proactively strengthen their fraud prevention efforts while reinforcing the foundation of customer trust.

The argument for comprehensive fraud risk monitoring

Nordic financial institutions operate in an environment characterized by high digitalization and rapidly changing consumer behavior. This complexity, while driving innovation, also opens new avenues for fraudsters. Consequently, traditional approaches with a point-in-time fraud risk assessment combined with retrospective analysis of fraud losses are no longer sufficient. Instead, institutions must adopt a forward-looking and nuanced strategy that leverages comprehensive fraud metrics to identify patterns, anticipate emerging threats and respond proactively. 

Additionally, the coming payment services regulation (PSR) brings further onus on institutions to increase their focus on managing current and emerging fraud risks. The exact date is yet unknown, but the PSR is expected to be implemented by the end of 2027 and covers, among other topics:

Transaction monitoring

The draft PSR introduces enhanced requirements for transaction monitoring. Under the PSR, institutions must implement advanced, real-time monitoring systems to detect and prevent fraud.

Shift in liability

One of the most significant changes in the PSR is the introduction of a new liability regime for authorized push payment (APP) fraud. The PSR is set to require institutions to reimburse consumers who are victims of impersonation fraud, i.e., where a fraudster tricks a customer into authorizing a payment by pretending to be, for example, a bank employee. The burden of proof for gross negligence or fraud will be on the institution, and the bar for denying reimbursement is expected to be higher than under existing regulation.

Fraud awareness

The proposed regulation also emphasizes the importance of consumer and employee awareness as a key anti-fraud measure. Institutions will be required to implement ongoing customer education initiatives about new fraud typologies and to provide regular training for employees on payment fraud risks and trends.

Effective fraud risk management with monitoring as a key element is not just about meeting regulatory requirements or mitigating financial losses; it is, and should be, a strategic move for safeguarding customer trust and protecting the institution’s reputation.

Key principles for monitoring fraud risks

To strengthen their anti-fraud frameworks, institutions should adhere to four key principles for monitoring fraud risks.

1. Support decision-making through actionable metrics
   
   Leadership must receive more than just raw data. They need concise, relevant and complete information that enables them to ask the right questions, identify gaps and act. By shifting the focus from retrospective reporting to forward-looking risk identification, institutions can empower leaders to anticipate challenges, plan effectively and act proactively.
   
   
2. Holistic risk perspective
   
   Monitoring should cover the full spectrum of financial, operational and reputational impacts of fraud. This includes tracking operational expenses associated with fraud prevention, the total amounts of fraud prevented and detected, fraud losses, and the effects on revenue growth, customer retention, and overall customer experience.
   
   
3. Put metrics and efforts in context
   
   Metrics should be presented in a relevant context. For example, presenting fraud losses as a percentage of revenue, transaction volume, or customer attrition rates provides a more nuanced understanding of the impact of fraud relative to the institution’s overall performance. This helps management pinpoint vulnerabilities and track trends over time.
   
   
4. Leverage advanced analytics and artificial intelligence
   
   As the approaches employed by fraudsters become more sophisticated, institutions should consider furthering the use of advanced analytics and AI to spot emerging fraud typologies, identify control gaps and establish early warning indicators. These tools enable proactive detection and real-time response to threats and, when all the dots are connected, can provide critical insights for informed decision-making.

Developing and implementing effective fraud metrics

When developing and implementing fraud metrics, institutions should consider their own size, risk appetite and operational complexity. 

Relevant metrics should be based on the key principles above and thus should include, but are not limited to:

• Risk appetite metrics: Define acceptable levels of fraud risk and evaluate whether the institution is operating within approved boundaries. Institutions should, in setting the risk appetite, look beyond fraud losses and instances of fraud and evaluate if existing operational risk limits and approach to limit setting are appropriate.
• Key risk indicators (KRIs): Monitor trends in risk exposure, such as the percentage of monthly disputes confirmed as fraud or the trend in confirmed fraud cases per number of accounts.
• Key performance indicators (KPIs): Track operational performance, including fraud prevented as a percentage of transactions, average time to resolve cases, and funds recovered as a percentage of total fraud amounts. Consider including customer satisfaction metrics and attrition among affected customers in line with the principles.
• Key control indicators (KCIs): Verify the effectiveness of controls, such as the percentage of flagged transactions reviewed within a specified time.
• Quality assurance metrics: Monitor process execution and accuracy.

Leadership and control functions should collaborate with operational teams to identify which metrics provide strategic insights and which are more suitable for team-level management. Once established, the selected metrics and any thresholds or limits should be regularly reviewed and refined to ensure they remain relevant and actionable.

From metrics to action

While collecting the relevant metrics is foundational, it is by analyzing the data and through storytelling the metrics come to life and can support action.

Build comprehensive dashboards

Develop dynamic dashboards that present executive summaries alongside trend and variance analyses. Dashboards should highlight KPIs, visualize trends over time and focus on deviations.

Craft a compelling narrative

Bring metrics to life with a narrative that provides context around the data. Metrics should be interpreted, explaining what the numbers mean for the organization and proposing actions for breached thresholds. For example, improvements in fraud detection rates, reductions in fraud losses as a percentage of sales, and positive trends in customer satisfaction should be clearly communicated, including the root cause, such as internal initiatives or external factors.

Add supporting metrics

Leverage additional data points available to reinforce analysis, such as geographic heatmaps of logins, the percentage of logins blocked, fraud incident counts and trends, and customer retention rates among accounts affected by fraud. These metrics provide a comprehensive risk perspective and support decision-making.