The Total Economic Impact™ Of Mastercard Decision Intelligence And Rules Services

Fraud Loss Reduction

Evidence and data. Prior to deploying DI&RS with Mastercard, interviewees described fraud environments characterized by sudden spikes, emerging attack patterns, and delayed containment, which resulted in elevated losses and repeated customer impact. Fraud teams were often forced to respond after losses had already occurred, particularly as fraudsters rapidly shifted tactics.

With DI&RS, interviewees described earlier detection of fraud attacks, driven by access to network‑level velocity signals and consortium intelligence not available through internal or processor‑only tools. Interviewees said this earlier visibility helped them stop attacks sooner, limit the size of loss events, and avoid the large swings in fraud performance they had seen previously.

• The fraud strategy officer in banking described how, prior to using Mastercard’s network‑based capabilities, fraud losses tended to spike as new attack patterns emerged, requiring reactive mitigation after losses had already accrued. After deploying DI&RS, the interviewee emphasized that fraud losses stabilized as attacks were detected and mitigated earlier, before they could escalate. They explained: “What we’ve seen with DI&RS is fraud has stabilized over the last year. We’ve seen far fewer spikes as the velocity, whether it be merchant level or [bank identification number] level, has been effective at capturing those attacks and mitigating much earlier.” That earlier intervention translated into measurable basis point improvements in fraud losses. They continued, “We have dropped our gross fraud basis points by, I believe, 2 to 3 basis points.”

• The fraud analytics manager in banking also highlighted a direct link between improved rule quality, reduced false positives, and materially lower fraud losses: “We’ve been able to refine a lot of the rules and get the false positives down while we still continue to stop the fraud. In saying all that, we also reduced our losses by almost 50%.” The same interviewee reinforced that reduced customer impact and loss reduction went hand in hand, especially when fraud was stopped earlier in the transaction lifecycle. They said, “We had such poor-performing rules before DI&RS and a whole lot of impact on genuine clients that were still losing more than what we’ve achieved now with fewer alerts.”

• The head of CLM in banking similarly said, “Our fraud losses in the past six months, compared to before we you were doing this manually with fragmented processes, have definitely been halved, and we have definitely been back in our threshold that is acceptable for the bank.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• Credit card transactions for the composite total 40,000,000 in Year 1, 45,000,000 in Year 2, and 50,000,000 in Year 3.

• The transaction fraud rate is 0.05%, which is reduced by 12% due to DI&RS.

• The average fully loaded cost per fraudulent transaction ($175) includes the transaction loss as well as downstream operational and remediation costs.

Risks. The impact of this benefit will vary among organizations based on the following factors:

• The organization’s processing volume with DI&RS.

• The organization’s previous fraud alert processes and intelligence before DI&RS and the tools that it retains with DI&RS.

• The organization’s baseline fraud-alert-per-transaction ratio.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.1 million.

Reduced Alert Volume

Evidence and data. Before DI&RS, interviewees consistently described alert volumes that overwhelmed fraud and operations teams, forcing fraud analysts to process thousands of alerts per day with minimal time per decision. This environment drove inefficiency, error risk, and excessive staffing requirements across both onshore and offshore teams.

As false positives declined, interviewees reported meaningful reductions in alert volumes, which freed fraud analysts to spend more time on complex cases and, in some cases, reduce reliance on offshore or temporary staffing. Interviewees quantified these improvements using alert volume reductions, time‑per‑alert context, and team size reductions.

• The head of CLM in banking described a highly manual, multitier alert process prior to DI&RS: “We had a team sitting in a different offshore jurisdiction where they were dealing with alerts. Then the alert comes back to [the] onshore [team]. If it is a true alert, then a level two team is sitting here. DI&RS has already reduced false positives for us. That means fewer alerts coming onshore, and the team here can focus on actual risk rather than just discounting the alerts. We were able to reduce the workforce sitting offshore by 20% or so.”

• The vice president of fraud management in banking said: “The previous software we were using was not that effective. There were a lot of false positives. … Earlier, the false-positive rate was 70%; it has now reduced to 40%.” The interviewee attributed this partially to DI&RS, along with other tool improvements.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization experiences 200,000 alerts before DI&RS, which it is able to reduce by 20% with the solution.

• As a result, the composite saves 500 hours per year in fraud analyst time.

• The average hourly burdened rate of a fraud analyst is $52.

• In addition to reducing alert‑handling effort, the solution reduced downstream operational work triggered by a subset of false‑positive alerts, such as customer verification or secondary review, at an average blended cost of $4 per instance.

Risks. The impact of this benefit will vary among organizations based on the following factors:

• The organization’s complete environment with tools that complement DI&RS.

• The organization’s team size and processes for handling alerts.

• The organization’s rate of false positives before DI&RS.

• The average fully burdened hourly rate for a fraud analyst and the cost to follow up on false positives.

Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $153,000.

Unquantified Benefits

Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:

• Improved customer experience and reduced friction. Interviewees reported that DI&RS improved the overall customer experience by reducing unnecessary transaction declines and minimizing friction during legitimate purchases.

They said that more accurate decisions led to fewer unnecessary declines at the point of sale and faster resolution when fraud occurred, reducing customer frustration and complaints. The fraud analytics manager in banking said, “Even though we don’t formally track churn tied to fraud controls, we see fewer legitimate customers being disrupted.”

Earlier and more accurate fraud detection limited the scope of fraud incidents and reduced the number of customers affected by downstream remediation processes. The fraud strategy officer in banking reported a significant reduction in card reissuance volumes after improving early detection of fraud attacks. They shared, “By catching fraud earlier, we reduced card replacements by about half, which significantly reduced customer disruption.” The interviewee gave a single concrete, high-level example: “Rules Services picked up one of the stolen cards for a high‑value client. By following that, we had at least $25,000 in savings.” This illustrates how earlier declines directly prevented material fraud losses.

The fraud analytics manager in retail banking said their organization experienced fewer inbound customer calls related to declined or blocked transactions, reducing overall disruption to customers. They said, “With fewer false positives, we saw a noticeable drop in inbound customer calls related to declined transactions.”

The head of CLM in banking said: “Reducing the number of genuine customers being impacted was a big win for us. Fewer declines meant fewer frustrated customers at the checkout.”

The head of fraud in retail banking noted that customers increasingly perceived fraud monitoring as a protective service rather than an obstacle, reinforcing trust in the bank’s ability to safeguard transactions.

• Increased fraud stability and predictability. The fraud strategy officer described how prior to implementing DI&RS, fraud patterns sparked sharply during BIN attacks. This stabilized after the organization adopted DI&RS. Fraud spikes often triggered emergency rule changes, leadership escalation, and operational disruption, all of which carry costs and risk exposure.

Interviewees said that DI&RS reduced volatility in fraud performance by enabling earlier detection of emerging fraud patterns and limiting sudden spikes in fraud losses. Instead of reacting to new attack vectors after losses had already escalated, the interviewees’ organizations experienced more stable and predictable fraud trends over time.

The fraud strategy officer in banking said: “Before Rules Services, fraud would spike when a new attack hit and we’d have to react. Since implementing it, fraud has been far more stable month to month.” The head of CLM in banking shared a similar sentiment. They said, “Having network-level intelligence helped us identify issues earlier, rather than dealing with sudden increases after the fact.”

• Improved decision quality and fraud analyst confidence. DI&RS improved the quality of and confidence in fraud decisions by ensuring that alerts reaching fraud analysts were more meaningful and actionable, preventing downstream costs that would be visible to customers and internal teams alike. With fewer low-quality alerts to review, teams made decisions with greater accuracy and less second-guessing, reducing both missed fraud and unnecessary customer declines.

The fraud analytics manager in retail banking noted that reduced alert volumes lowered fraud analyst error rates, even though those improvements were not formally quantified. They noted, “With fewer alerts coming through, our analysts weren’t rushing decisions anymore, and we saw far fewer mistakes.” The vice president of fraud management in banking highlighted greater confidence in fraud classifications as a key benefit of improved scoring accuracy. They said, “The accuracy of classification improved, which gave us more confidence that high-risk transactions were truly risky and low-risk ones were safe.”

• Reallocated effort toward higher-value work. DI&RS allowed fraud teams to shift effort away from reactive, low-value work toward more strategic activities such as rule optimization, fraud trend analysis, and cross-team collaboration. Even in cases where headcount was not reduced, teams spent less time firefighting and more time strengthening long-term fraud controls. With fewer low‑quality alerts to manage, fraud teams were able to spend more time proactively tuning rules and reviewing trends instead of reacting to large volumes of false alerts, which increased agility.

The fraud strategy officer in banking reported reallocating approximately 10 hours per week from reactive response to longer-term fraud strategy. The interviewee said, “It allowed me to stop being purely reactive and spend more time on longer-term fraud strategy and rule improvements.” The head of CLM in banking also described improved collaboration among fraud, onboarding, and risk teams as signal quality improved. They shared, “Better signal quality meant our teams could focus on actual risk instead of just discounting alerts.”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement DI&RS and later realize additional uses and business opportunities, including:

• Increased organizational agility and future-readiness. As fraud environments continued to evolve, institutions needed adaptable controls that could scale with transaction growth and product expansion. Interviewees viewed DI&RS as foundational infrastructure that could support future transaction growth and new payment channels without requiring proportional increases in fraud operations staffing, which positioned their organizations to adopt new payment channels, digital wallets, and fraud capabilities with greater confidence and lower incremental risk.

Interviewees described DI&RS as foundational infrastructure that strengthened readiness for future digital offerings and evolving fraud threats. The head of CLM in banking said, “Mastercard’s solutions became foundational infrastructure for us. It’s not just about today’s fraud but being ready for what comes next.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).