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Key Findings on Fraud and Financial Crime, 2021-2022

  • $102m: The average cost of scams to each FI surveyed
  • 6/10: The number of FIs who experienced an increase in their overall fraud rate
  • 43%: The percentage of FIs who experienced an increase in their false positive rate
  • 62%: The percentage of FIs who reported a Year on Year increase in fraud volumes
  • 1.29 bps: The average fraud losses in basis points per transaction for FIs
  • Fraud rates and losses increased for nearly all payment types in 2021
  • Most FIs have experienced an increase in the volume of financial attacks, and smaller FIs are getting attacked most
  • Authorized and unauthorized fraud types currently appear to be relatively equal, but scams are on the rise within authorized fraud
  • FIs using artificial intelligence (AI) and machine learning report the lowest levels of financial crimes, including fraud
  • The complexity of compliance and the challenge of integrating new solutions are barriers impeding the prevention of future attacks
  • Criminal approaches are becoming more sophisticated, and most FIs consider this to be a problem

“Without standardized fraud reporting, it is extremely difficult to understand the extent and nature of fraud across the industry. The Federal Reserve worked with the industry to develop the FraudClassifierSM model to help organizations speak the same fraud language within organizations and foster a common taxonomy across the industry. This study leverages the model’s holistic approach to classifying fraud involving payments, looking at both authorized and unauthorized party fraud. Benchmarking studies such as this one not only help in understanding a comprehensive picture of fraud today, but also how the trends are evolving over time.”

Mike Timoney, Vice President of Payments Improvement, Federal Reserve Financial Services

Combatting fraud and financial crime starts with understanding the size and shape of the challenge.

With a lack of standardized reporting to analyze fincrime trends in the market today, financial institutions in the U.S. have struggled to outsmart fraudsters and criminals.

Featurespace partnered with PYMNTS to create the most trusted benchmark of financial crime and fraud challenges, trends and prevention performance, by the industry, for the industry.

We interviewed executives across 200 U.S. financial institutions to create the first ever benchmark for volume and value of fraud and financial crime, using the FraudClassifier model from the Federeral Reserve to ensure accurate and relevant data.

Now, for the first time, financial institutions have the fraud and financial crime trends data they need to help make the world a safer place to transact.

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How fraud rates are changing by payment type

  • Comparing Year on Year (YoY) for 12-month periods
  • Cards saw the biggest increase in fraud rates of all payment types
  • Self-reported rates for BNPL and cryptocurrency appear to be down, but can likely be attributed to discrepancies in reporting and loss attribution between FIs
  • BNPL may be written off as bad debt rather than fraud in some FIs

Benchmarking against other FIs

  • Fraud rates in basis points (bps) is the most effective benchmark for comparing performance between FIs of varying asset sizes 
  • The fraud rate in bps by each payment type shows the impact of fraud over the last 12 months
  • Cards remain the largest contributor to fraud rates
  • Bank account transfers and Zelle and Venmo transactions, often associated with Authorized Push Payment (APP) scams, are also standout contributors

As a Service

Fraud growth is outstripping customer growth

The rising volume of fraud attacks necessitates innovation to outsmart organized criminal networks. Releasing resource for innovation is challenging when daily operational and regulatory demands are so high. Competing priorities for investment make it difficult for individual FIs to combat new fraud trends effectively. 

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As banks and credit unions struggle with cost to income ratios and with global markets down, they look to find efficiencies without losing innovation.

Enter issuing, acquiring, network and processing partners who are offering innovation as a service. The next innovations in their platforms are fraud prevention and Anti-Money Laundering (AML) as a Service. 

The global rise of digital transaction volumes has created great opportunities for service providers, and as fraud and financial crime has increased in lockstep they are now providing scalable and efficient fraud prevention and AML solutions to financial institutions. For Payments as a Service providers, anti-fraud and compliance investments not only help manage operational cost but can even be monetized. 


The challenge of increasing fraud

  • The rising number of fraud and financial crimes is a common challenge cited by FIs of all sizes
  • Both fraud and AML professionals see the sheer volume of transactions as a key issue to address
  • For 13.5% of FIs, tackling the increasing number of fraud and financial crimes is their biggest challenge of all

How fraud and fincrime challenges vary by FI size

  • 62% of FIs experienced an increase in the volume of fraudulent transactions in 2022 compared to 2021
  • FIs of all asset sizes, from $5bn to more than $500bn, unanimously identify the volume of fraud and financial crime as a challenge
  • For smaller FIs, between $5bn and $25bn in assets, even more executives are concerned about rising volumes than their counterparts at larger institutions 

Top 3 challenges in combatting fraud and financial crime

  1. Complex regulatory requirements
  2. Increasing sophistication of fraud schemes
  3. Increased speed of payments
  • FIs reported that in 2021 regulation, sophistication and speed were the most common challenges
  • The combination of all three presents competing priorities for investment within FIs

“Experience in implementations, processing platforms, integrated data, data science, and model governance is critical and cannot be accomplished with AI and machine learning alone. Issuers look to purchase a platform they can rely on, and they trust TSYS and Featurespace experts who have a track record in successfully deploying and maintaining the advanced adaptive machine learning model.”

Maria Adele Di Comité, Research Director IDC Financial Insights



Scams are on the rise in the U.S.

Scams now represent 2 of the top 5 categories of fraud volumes and losses for FIs, yet scam typologies are almost impossible to prevent effectively with traditional rules-based systems. The market must act now to mitigate rising risk, particularly as liability and reimbursement regulation looks set to change in favor of consumer protection.

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There's a misconception that scams are limited to payments, and in particular faster payments. This data shows that new instant payment types such as TCH RTP, Zelle or Venmo are no more inherently risky than any other payment type. Authorized fraud that occurs on cards is still a scam.

FIs in the U.S. need to modernize fraud prevention systems to combat rising scams if they want to remain compliant, preserve customer experience, and reduce losses. Scams may take many forms such as investment, romance, or impersonation but the one thing they all have in common is that they target the customer to initiate and authorize the transaction. 

Protecting against these is therefore a different challenge to traditional fraud typologies, and legacy approaches can result in increasing false positive ratios. Machine learning, and in particular adaptive machine learning, is crucial to accurately identifying when a customer is acting out of character including when they are authorizing the transaction, and even if their behavior has changed over time.


The riskiest payment types

  • Comparing the fraud rate for three groups of payment types: card, ACH and wires, and new instant payments
  • Cards remain the payment type with the highest fraud rates, as well as the greatest increase in fraud rates
  • Contrary to popular perception, instant payments are not inherently riskier than cards or other types of transactions 

Changes in fraud rates

  • Despite existing fraud rates being high, cards also show the highest increase in fraud rates in the last 12 months
  • Fraud rates for Person to Person (P2P) transfers are emerging as a growing challenge for FIs
  • P2P fraud is often authorized fraud or scams, emphasizing the need for strong scam prevention capabilities

AI and machine learning lower fraud losses

  • FIs that use machine learning or AI report a lower percentage increase in the overall fraud rate compared to those yet to adopt the technologies
  • FIs benefit doubly from AI and machine learning, reporting significantly lower rate of transactions resulting in fraud losses when new these technologies are leveraged 

“Scams are a particularly challenging threat for financial institutions because by bypassing the institution’s authentication controls, the attacker forces the institution to rely on an incomplete picture of the potential risk of a payment. In order to accurately and effectively detect scams, financial institutions would need to be able to predict why a customer is issuing a payment order as opposed to how the customer is issuing a payment order. Unfortunately, the level of sophistication required to accurately predict a customer’s intention does not presently exist in a manner that can be considered to be “commercially reasonable” which is the legal standard that financial institutions are required to meet in the U.S. market.”

Trace Fooshee, Strategic Advisor Aite-Novarica Fraud & AML Practice



Fraud and financial crime teams facing the same frontier 

Historically separate entities, fraud and AML professionals now have more in common than ever, highlighting the same challenges and investment priorities when it comes to making the world a safer place to transact. Volumes, values and validity reign, with managing the false-positive ratio a key component of both fraud and fincrime strategies. Fraud and financial crime metrics include:

  • The volume of fraudulent transactions
  • The overall fraud rate
  • The dollar cost of fraudulent transactions 
  • The overall false positive rate
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Factors inhibiting fraud and financial crime innovation

  • Regulatory constraints or difficulties
  • Complexity of using new technology systems
  • Difficulties integrating new solutions to existing systems
  • Cost of innovation
  • Higher data management costs associated with new technology systems
  • Available technology
  • Higher priority given to other areas of innovation

As new fintechs and neobanks enter the market, they bring exciting new propositions, and an increasing awareness of the need for a holistic fraud and financial crime platform and strategy.

Greenfield technology environments make implementing these combined fraud and Anti Money Laundering (AML) platforms much simpler than in legacy environments. In traditional financial institutions, where fraud and AML teams operate independently, executives specializing in money laundering are among the most likely to give high priority to innovation, but struggle to overcome technology debt and legacy constraints. A combined strategy and investment could be the answer to this challenge. 

Fraud and AML professionals are prioritizing the same technology modernizations – cloud and machine learning – and as such, converging into a holistic fraud and financial crime platform is more commonplace amongst FIs looking to innovate and manage the Total Cost of Ownership for their fraud and AML operations. 


Fraud versus AML technology innovations 

  • Although fraud and AML executives have fairly similar desires for innovation, their current implementations of technologies does differ across three categories
  1. Cloud-based fraud and financial crime platforms
  2. Rules-based algorithms
  3. Machine learning or AI

Early adopters in AML

  • AML execs are the most likely to be first to market with innovations
  • 95% of execs specialized in AML give the highest priority to innovations
  • 85% of executives specialized in money laundering mention technological  complexity and difficult integration as inhibiting factors

“Unified EFM and AML risk scoring is all about unusual/anomalous pattern detection. Whether heuristic (rules-based) or AI (machine learning [ML]-based), developing ethical, responsible, and properly version-controlled transaction risk scoring models is expensive. FRAML convergence allows FIs to use a single, integrated platform for authoring rules, developing, training, and verifying AI/ML models at a 20% to 30% lower cost, in Forrester’s estimation. AML model effectiveness monitoring can help FIs identify declining AML model performance but will also help explain lagging EFM model performance. Combined model governance in FRAML also improves model efficiencies.”

Top Trends Shaping Fraud Management And Anti-Money Laundering – Forrester, August 6, 2021, by Andras Cser, Vice President, Principal Analyst



Fast Followers Experience More Fraud

Implementing innovations is the secret to outsmarting risk. Financial institutions that launch innovative solutions before others experience the lowest average fraud losses in BPS by far, compared to those who wait even a short time. That’s because fraudsters are innovating too, constantly testing FI’s defences and changing tactics once previous scams, schemes and typologies no longer work. Fraud and financial crime prevention teams have to innovate ahead of the criminals if they want to reduce losses, and that means being first to market.

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Time to market with innovations

  • Comparing institutions’ strategies when launching innovative solutions
  • Early adopters reap the reward in the form of lower average percentage of transactions (in bps) that result in fraud losses
  • First movers: “We launch innovative solutions before others”



  • Fast followers: “We wait for some evidence of emerging trends and then act quickly to launch innovative solutions
  • Slow followers: “We wait until innovative solutions are well developed and then we integrate the most accepted solutions”
  • Latecomers: “No new solutions added until they are widely accepted in the marketplace”

Technology is both the challenge and the answer when it comes to innovation: reducing fraud losses; managing false-positive ratios for fraud and financial crime; and overcoming regulatory barriers.

Within technology strategies, the use of cloud to aid innovation and speed to market is a clear benefit. And organizations who prioritize cloud experience lower rates of transactions resulting in fraud losses. Cloud is also a path to simplification for FIs whose fraud and financial crime technology stacks have become unwieldy and ineffective.

Bigger institutions use, on average, 3.5 different technologies and report the highest total cost of fraud. So in fact, the answer to innovation is the right technology strategy, leveraging the cloud for speed and simplicity.


Strategies to improve existing solutions for fraud and financial crime

  • Improved communications with customers
  • Initiating or increasing the use of machine learning of AI models
  • Initiating or increasing the use of cloud-based fraud and financial crime platforms
  • Initiating or increasing the use of deep learning systems
  • Developing new in-house systems for fraud and financial crimes
  • Outsourcing the detection and prevention to a third party
  • No plans

Top 10 changes needed to combat fraud and financial crime 

  • FIs have reached some consensus on the strategic investments needed
  • New technologies, specifically AI and machine learning (ML) feature highly 
  • Education internally for employees and externally for customers is a recognized requirement

“Risks can be mitigated through data analysis, although fraud will always be with us as criminals seek to get around every new control. To help counter this threat, continuing to invest and quickly implement new technology and detection methods will always be of the highest importance.”

Adeola Adebonojo, General Counsel and Chief Risk Officer at Contis



Compliance at the cost of innovation

The volume and velocity of regulation impacting fraud and financial crime teams continues to grow. However, with daily operations and compliance demanding so much time and investment, releasing resource for innovation is a struggle. In fact, regulatory constraints are the top factor inhibiting financial institutions from innovating. 60.5% of FIs cite regulatory constraints or difficulties as factors inhibiting innovation or adding new features to existing solutions. This concern is echoed in FIs of sizes and innovation appetites, and by both fraud and AML professionals.

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The correlation between regulatory restraints, innovation inertia, and the cost of fraud is clear. Complex regulatory challenges are the single biggest inhibitor to fraud and financial crime innovation.

The challenges around balancing compliance and customer experience become clear when we consider that financial institutions which experience higher rates of scams (such as relationship fraud) are also more likely to see regulatory constraints as an inhibiting factor for innovation.

The potential cost of new reimbursement mandates for victims of scams threatens to overwhelm FIs who are already struggling to invest in the innovations needed to thwart these new fraud typologies. Mid-sized financial institutions are perhaps the hardest hit by the challenges of regulation, especially when coupled with higher-than-average fraud rates, losses, and costs.


Top 3 regulatory inhibitors of innovation

FIs highlight 3 key inhibitors to innovation from a regulatory perspective

  1. Complex regulatory requirements
  2. Financial sanctions compliance
  3. Cost to the bank of for reimbursing fraud-related losses
  • Complex regulatory requirements feature high on many FIs’ agenda of concerns, regardless of asset size
  • Some mid-sized FIs are less concerned about sanctions, suggesting they may be pursuing a Compliance as a Service of RegTech supplier strategy
  • Some mid-sized FIs are relatively far more concerned by the cost of reimbursements, likely due to their current fraud losses combined with rising scams and expected new contingent reimbursement regulations


Robust regulatory frameworks are one way to reduce the burden of compliance and encourage innovation in line with national priorities. Read the four enhancements Featurespace recommends to the Bank Secrecy Act and Anti-Money Laundering Regulations to deliver on the national priorities including for fraud.

“Regulatory oversight is key to protecting citizens and economies but must be balanced to ensure the smooth functioning of financial institutions (FI) operations for the benefit of 99.99% of their customers. At times, the volume of new regulations, particularly in relation to fraud prevention and anti-money laundering, can overwhelm an FI’s frontline systems and severely hinder the transacting of huge volumes of legitimate business.  Although technology innovations, such as machine learning, offer the opportunity to optimize and automate compliance, current frameworks are failing to keep pace. Regulators should provide more specificity for FI’s aiming to balance cost, customer experience, and compliance through innovations. To achieve this there ought to be greater collaboration between industry and regulators to ensure the best designed regulation is implemented to meet national priorities, while remaining efficient and effective.”

Peter Radcliffe, Chairman P20

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