Fraud Loss Reduction

Evidence and data. Interviewees noted that adding CFR’s score to their existing set of fraud decisioning systems and tools provided an understanding of the beneficiary account and improved their banks’ fraud prevention strategies. This increased the amount of fraud interviewees’ banks detected and reduced their losses. The manager of fraud analytics said, “CFR allows us to detect more fraud and to do so more efficiently, which means fewer losses for the bank, fewer victims, and lower operational costs.”

• The capability to better detect mule accounts was something interviewees’ banks lacked before implementing CFR. The head of fraud systems and controls said, “It gave us something that we didn’t have before — insight on the beneficiary risk.” The manager of fraud analytics said: “What CFR does well is it considers a set of risk factors about the account the money is going to — factors that are otherwise invisible to us. It gives us visibility into behavioral patterns we wouldn’t be able to see on our own.”

• CFR added an additional layer of fraud detection to interviewees’ existing strategies. The head of fraud performance and analytics said: “The value of CFR is that it enhances our existing fraud systems and capabilities. It doesn’t replace them but rather adds an important layer to our overall fraud prevention strategy.” The fraud threat risk manager said: “The more data, the better. If we can get more information on where payments are going and the risk of those destinations, that’s something we can introduce to reduce false positives and even expand fraud detection.”

• CFR helped interviewees spot shifts in mule activity faster than internal analytics, allowing interviewees’ banks to take immediate action. The senior fraud manager said: “What CFR offers is a much faster way of identifying where most of the fraud is going beyond what each bank’s own detection systems can do. We already have comprehensive models and strong detection capability, but if we can see through CFR that higher risk scores are coming back from Bank Y compared to Bank X, we can sharpen our approach immediately. Historically, that would have meant more fraud happening over a longer period before we understood where the fraudsters were cashing out. So that’s been a huge benefit for us.”

• The head of fraud systems and controls cited the impact on their business, noting, “By saving more money, the business can reinvest those funds into growth initiatives, rather than absorbing them as fraud losses.” This interviewee went on to state the amount of money their bank saved: “We’re saving £600,000 per month in pure fraud loss — an incremental benefit we wouldn’t have achieved without CFR. That’s £7.2 million a year that can be reinvested — definitely a business enabler.”

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

• The volume of outbound consumer bank-to-bank transactions is $183.6 billion annually.

• The average annual loss due to APP fraud is 2 basis points (0.0002) of the total transaction volume.

• The percentage of fraud detected due to all fraud detection tools and strategies is 55%.

• The incremental fraud detection that is attributable to CFR rules is 5%.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The maturity of a bank’s fraud prevention strategy. For example, adding CFR to a bank early in its fraud prevention journey will have a greater impact than adding CFR to a bank later in its fraud prevention journey when the improvements are more incremental.

• The presence of other fraud detection tools will contribute to the impact of CFR.

• The total volume of transactions is a key driver to the model. Variations in this volume will have a large impact on the size of the benefit.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.1 million.

Operational Cost Savings From Fewer False Positives

Evidence and data. CFR reduced the false positive rate at the interviewees’ banks because CFR’s score helped filter out low-risk destinations and flagged fewer genuine transactions for further investigation. With fewer false positives to investigate, fraud operations teams at the interviewees’ organizations freed up capacity and reinvested this time into expanding coverage to harder-to-detect scams. The head of fraud systems and controls said, “The greatest benefit CFR provides is its ability to reduce false positives while also strengthening fraud detection — both in terms of the volume and value of fraud identified.”

The manager of fraud analytics explained that the reduction in false positives gave their bank greater flexibility in how to reinvest the time saved: “You can leverage the reduction in false positives in two ways. One option is to detect the same amount of fraud at a lower cost; for example, reducing daily alerts from 1,000 to 700, which means fewer staff needed to handle customer queries. Alternatively, you can use the saved alert capacity to detect other types of fraud, keeping the same team size but increasing overall fraud prevention.”

The head of fraud systems and controls explained how the reduction in false positives led to operational efficiencies the fraud operations team could reinvest: “While CFR allows us to reduce alerts, we’ve chosen not to bank that efficiency. Instead, we use it to expand coverage, reaching a lower-risk population we previously couldn’t due to resource constraints.”

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

• The bank processes 540 million outbound consumer bank-to-bank transactions per year.

• The bank interrupts 0.06% of overall transaction volume. These interruptions generate alerts for follow-up investigations. This means 324,000 transactions are interrupted and investigated per year.

• The percentage of interrupted payment alerts that are false positives is 75%, bringing the number of interrupted payment alerts that are false positives to 243,000 per year.

• CFR reduces the false positive rate by 20%, resulting in a reduction of 48,600 false positives per year due to CFR.

• A fraud specialist investigates an average of 35 alerts per day, spending on average 20 minutes (0.33 hours) per investigation.

• The fully burdened hourly rate for a fraud specialist FTE is $52.² The cost per investigation is $17 in labor.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The thresholds a bank sets on rules triggering an interrupted payment.

• The total number of transactions is a key driver to the model. Variations in this number will have a large impact on the size of the benefit.

• The length of time investigators spend per alert. The average handling time per investigation depends on the percentage of alerts requiring deep investigation.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.7 million.

Revenue Retained Through Lower Churn

Evidence and data. Interviewees said that with CFR contributing to risk assessment, more legitimate transactions go through and fewer trigger interruptions. This meant fewer of the banks’ account holders had to deal with the disruption of an interrupted and delayed payment and the hassle of sorting out the issue with their bank. This improved customer experience resulted in fewer account holders leaving their bank due to a bad experience. The manager of fraud analytics said, “With CFR, genuine payments go straight through without delays or the need for customers to contact us, improving their overall experience.”

The senior product manager said, “CFR reduces friction for genuine customers when a payment isn’t fraudulent, and it also improves the experience for victims, allowing us to protect them in cases where we previously may not have been able to.”

The fraud threat risk manager added that CFR improved customer experience by identifying high-risk payments early and protecting account holders from fraud: “Our payment center recently achieved the best-in-class NPS [Net Promoter Score^SM] among UK financial institutions. Anecdotally, the CFR score may have contributed to this positive customer experience by identifying high-risk transactions — even when genuine — leading account holders to appreciate the added security and proactive measures.”³

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

• The bank has 19 million account holders, 70% of whom conduct bank-to-bank transactions.

• The percentage of these account holders interrupted each year due to payment alerts is 1.71%.

• Two percent of account holders who are interrupted leave the bank, resulting in an average of 4,549 account holders per year churning due to interrupted payments.

• The average revenue generated per account holder is $300 per year, with 10% operating profit. This revenue is lost when the account holder churns.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• The thresholds a bank sets on rules triggering an interrupted payment.

• The experience an account holder has with the fraud operations agent impacts churn.

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 $305,000.

Unquantified Benefits

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

• Facilitating collaboration among banks. Interviewees described how Mastercard took a broad view in its efforts to help banks reduce fraud by connecting banks with each other to share best practices and performance insights in the implementation and use of CFR. The head of fraud systems and controls said: “We learned a great deal from the other banks’ use of the data, which helped us accelerate our own implementation. Since then, we’ve held calls with other banks to help them adopt it more quickly as well. Banks share best practices and performance insights through Mastercard‑facilitated working groups.”

• Dedication to solving fraud. Interviewees stated that they believed Mastercard was committed to reducing fraud in the UK. The senior fraud manager said: “The team around CFR is dedicated to solving this problem, which is really important. They’ll work in partnership with us, and I really value the fact that they’re receptive to adapting, changing, and pivoting based on what we need or what the industry needs.”

Flexibility

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

• Consortium/network effects of CFR. Interviewees noted how CFR’s value increased as more UK banks participated, enhancing visibility into risky destinations across the Faster Payments rails. Each participating bank both contributed and consumed data, creating a powerful shared intelligence layer. As the network grew, the dataset became richer and more comprehensive. By aggregating patterns across the entire ecosystem, CFR delivered recipient risk insights that no single bank could generate on its own. The head of fraud systems and controls said: “It’s worth it if you’ve got a consortium. We didn’t want to be one of the last banks to adopt this technology because I would see an increase in fraud attacks — other banks would have stronger controls.”

• Inbound risk notifications on the horizon. With outbound CFR in place for outbound transactions, one interviewee mentioned that their bank was looking forward to implementing a new process for inbound transactions. The senior product owner at this bank said: “Our strategic goal is to move to a real-time API integration similar to outbound CFR, so inbound scores feed directly into our detection system. This would enable automated responses, such as withholding funds or triggering additional checks, based on rule engines. We aim to implement this next year. Discussions with MasterCard are ongoing, and our ultimate objective is real-time processing to unlock the full benefits of inbound CFR.”

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