A community bank approves a transfer, confident that its fraud controls are working. Hours later, it discovers that the request came from a deepfake video call, and the money is gone.
Stories like this capture the dilemma: some executives still treat fraud as a problem technology and training can “fix,” while others see it as an uncontrollable cost of doing business.
Fraud losses are increasing, from $16.6 billion in the U.S. last year alone to billions more globally, as criminals exploit instant payments, crypto, and AI-powered deception.
This guide breaks down what modern fraud risk management looks like today: the frameworks financial institutions rely on, the tactics that actually reduce losses, and the tools that give banks, credit unions, and fintechs the upper hand.
Key takeaways:
- Treat fraud as a managed enterprise risk: Fraud risk management is a structured, ongoing program across governance, prevention, detection, and response.
- Faster payments and AI raise the stakes: Losses are rising as criminals exploit instant rails, social engineering, and deepfakes. Always-on monitoring and rapid decisioning are now table stakes for banks, credit unions, and fintechs.
- Fix the foundations before adding new tools: Break data silos, align teams, and tune thresholds to reduce false positives without hurting good customers. Regularly refresh risk assessments to ensure budgets and controls align with your highest-impact threats.
- Use a layered framework with clear ownership: Make fraud a board-level priority, run granular risk mapping, deploy preventive controls, monitor in real time across all rails, drill your incident playbooks, and join consortia to catch cross-institution patterns early.
- Turn intent into impact with VALID Systems: VALID pairs real-time scoring and consortium intelligence to stop losses before they occur.
What is fraud risk management?
Fraud risk management (FRM) is the proactive, enterprise-wide program for identifying, assessing, and mitigating the risk of fraud, whether from external criminals or internal actors.
It differs from generic internal controls by focusing specifically on fraud schemes and patterns. Put simply, FRM is to fraud what cybersecurity is to cyberthreats: a structured, cyclical process of prevention, detection, response, and recovery.
In practice, fraud risk management (FRM) encompasses all forms of financial wrongdoing that can harm an institution or its customers. Common examples include:
- Check fraud - forged endorsements, counterfeit checks, altered amounts
- Electronic payment fraud - ACH debits, wire transfers, instant payments
- Business Email Compromise (BEC) - fraudulent invoices and executive impersonation
- Identity theft - using stolen credentials to open or access accounts
- Account takeover (ATO) - unauthorized access through phishing or malware
- Mobile deposit scams - duplicate presentment or altered images
- Internal fraud - kickbacks, loan fraud, embezzlement by employees
- Emerging threats - abuse of real-time payment rails (e.g., FedNow®), deepfake-enabled phishing, misuse of digital wallets, and crypto
Effective FRM programs weave these elements together: governance and oversight, risk assessments, policies and controls, data-driven detection, and rapid response protocols. Crucially, no two organizations face the same risks. As ACFE emphasizes, “there is no one-size-fits-all approach to managing fraud risk.” Each bank, credit union, or fintech must design a strategy tailored to its business model, customer base, and threat landscape.
Why fraud risk management matters today
Fraud has always been part of financial services, but losses are now hitting new records.
Three forces are driving today’s surge:
- Real-time payments (Zelle, RTP, FedNow) remove the buffer for clawbacks - forcing banks to monitor transactions around the clock.
- Fraud rebounds as economic shifts push up check scams, card fraud, and phishing after a brief COVID-era decline.
- Criminal tech adoption: deepfakes and generative AI now fuel scams, with AI-enabled fraud projected to hit $40 billion by 2027.
The takeaway is clear: without strong fraud risk management, financial institutions face escalating losses, regulatory scrutiny, customer attrition, and lasting reputational damage.
Common challenges in fraud risk management
Fraud risk management is complex, and institutions often encounter similar hurdles:
- Data silos and legacy systems: Many banks still operate on fragmented platforms that fail to share data.
For example, mobile remote deposit capture (RDC) has struggled to catch counterfeit or altered checks because the imaging process isn’t cross-referenced with other account activity, allowing fraudsters to exploit gaps.
- False positives and customer friction: Overly aggressive fraud rules often flag legitimate activity, frustrating customers and damaging trust.
- Rapidly evolving schemes: Fraudsters shift quickly to new tactics once old ones are blocked. After check skimming declined, scammers pivoted to mobile deposit scams and synthetic identities, while pandemic programs like PPP saw counterfeit checks cashed through RDC channels.
- Resource constraints: Smaller institutions often lack dedicated fraud teams or advanced analytics. This leaves them more exposed, especially when facing complex schemes that require constant monitoring and specialized expertise.
- Regulatory and legal hurdles: Privacy and compliance rules restrict what data can be monitored or shared. For example, analyzing social media signals for fraud risk may conflict with privacy laws, creating tension between detection and legal boundaries.
- Keeping pace with technology: Criminals now use AI, deepfakes, and anonymizing tools to scale attacks. Meanwhile, many banks still rely on batch-based fraud systems. Meta-analysis of 47 studies indicates that contemporary AI-powered fraud detection systems achieve detection rates of 87-94% while reducing false positives by 40-60% compared to traditional rule-based methods. Still, many institutions lag in implementing such tools.
6 strategies for structuring fraud risk management
Criminals evolve constantly, exploiting the weakest points in payments, onboarding, and customer trust. The institutions that win are those that treat fraud not as an operational headache but as a strategic risk with a structured defense.
This framework provides financial institutions with a structured approach to mitigate losses, safeguard customer interests, and outmaneuver fraudsters:
1. Ensure management that makes fraud a board-level priority
Without leadership buy-in, even the best fraud tools underperform. Management ensures fraud risk is not buried in compliance checklists but treated like credit or liquidity risk - visible, measurable, and discussed at the highest levels. A strong governance model creates accountability, aligns fraud controls with strategic goals, and signals to regulators and customers that fraud is taken seriously.
Action steps:
- Assign a senior executive, CRO, CISO, or Head of Fraud, as the accountable owner of fraud risk.
- Publish a fraud risk appetite that defines acceptable loss levels and tolerance for false positives.
- Require regular fraud reporting at the board level, including both losses and prevented attempts.
- Foster a culture of escalation and vigilance, with whistleblower protections and training to empower employees.
2. Run risk assessments that expose real vulnerabilities
Institutions that fail to clearly map their risks often end up spending on ineffective defenses.
A modern risk assessment identifies where fraud is most likely to occur and where it will have the greatest impact. This isn’t a one-time project but an evolving process that adapts to new payment rails, customer behaviors, and criminal tactics.
Action steps:
- Collect fraud-loss data across all rails: ACH, wires, cards, instant payments, checks, and remote deposit capture.
- Map potential scenarios: account takeovers, mule accounts, counterfeit checks, BEC scams, duplicate presentments in RDC.
- Rank these risks by likelihood and financial impact to build a fraud heat map.
- Refresh assessments annually, or whenever major changes occur.
3. Deploy preventive controls that stop fraud before it hits the books
Prevention is always cheaper than recovery. But prevention can’t be static; criminals adapt too quickly.
The key is layered defenses that combine process (dual approvals), technology (device fingerprinting), and customer education. Done well, preventive controls protect both the institution and the customer while minimizing friction.
Action steps:
- Require dual authorization and segregation of duties for large or sensitive transfers.
- Add out-of-band verification and device checks for high-risk transactions.
- Implement positive pay and account verification for checks to stop altered or counterfeit items.
- Educate customers with targeted campaigns about phishing, fake checks, and new scam tactics.
VALID advantage:
With InstantFUNDS, banks and credit unions can release legitimate deposits instantly while holding risky ones for review. This dual-track approach stops fraud before funds clear while delivering the frictionless experience customers expect, a balance that few institutions achieve without advanced fraud intelligence.
4. Monitor continuously with real-time fraud intelligence
Instant payments, RDC, and mobile banking operate 24/7, which means fraud detection must be constant, intelligent, and fast. The right monitoring system catches anomalies before they become charge-offs, while also minimizing false positives that slow down legitimate customers.
Action steps:
- Deploy fraud engines that score every transaction across rails - ACH, checks, wires, instant payments, and cards - in real time.
- Use behavioral analytics to detect mule accounts, bot-driven account takeovers, or unusual spending patterns.
- Maintain round-the-clock coverage for instant payment systems like Zelle®, RTP®, and FedNow®.
- Regularly mine historical data to uncover subtle fraud patterns that might slip past real-time scoring.
VALID advantage:
VALID’s analytics power CheckDetect, which identifies more than 75% of potential check-deposit charge-offs at the point of deposit. The same intelligence extends across rails, producing sharper alerts and far fewer false positives. Investigators spend less time chasing noise and more time stopping actual fraud.
5. Respond with speed and recover before losses multiply
Even the best-prepared institutions will face fraud attempts.
The difference between a minor incident and a significant loss lies in how fast and how well the organization responds. A defined, rehearsed playbook ensures that everyone knows their role when fraud occurs, and that recovery efforts start immediately.
Action steps:
- Develop a comprehensive fraud incident-response playbook that outlines assigned roles for investigators, operations, legal, compliance, and customer communication.
- Integrate automated workflows to freeze suspect transactions or trigger recalls as soon as fraud is flagged.
- Document every step of the response for regulators, auditors, and insurers.
- Conduct root-cause analysis after each incident and feed insights back into the fraud risk assessment.
6. Collaborate and share intelligence to stay ahead of evolving threats
Fraud is an ecosystem challenge. Criminals move across banks, fintechs, and payment rails, exploiting gaps in visibility.
Collaboration and intelligence-sharing are the force multipliers that give institutions the power to anticipate new attack patterns and stop fraud before it spreads.
Action steps:
- Join fraud consortia and industry groups that share mule account data and typologies.
- Share anonymized fraud intelligence to build stronger defenses across the ecosystem.
- Use external threat insights to train fraud models and adjust rules before attacks escalate.
- Train teams with up-to-date scenarios drawn from consortium data and real-world attacks.
VALID advantage:
Through the VALID Edge Data Consortium, institutions gain visibility into over 450 million accounts and more than $4 trillion in annual transactions. These shared data attributes and predictive features provide an edge against fraud, enabling participants to block mule accounts earlier and detect cross-institutional patterns that would be invisible in isolation.
The role of modern technology in fraud risk management
Technology is central to modern FRM. Manual reviews and static rules alone can’t keep up with high-volume, fast-moving fraud attempts.
Key tech tools include:
Artificial intelligence and machine learning
AI and ML can spot subtle patterns in transactions. For example, ML models can detect when an account’s behavior suddenly deviates (odd location, unusual merchant, atypical purchase size) and flag it faster than human monitors.
Banks use AI-driven fraud engines for card transactions, wire transfers, and now instant payments. Some institutions even employ advanced AI (including large language models) to analyze communications.
Real-time alerts and customer notifications
Because money can move instantly, many FIs use immediate alerting. This includes sending push notifications, texts, or calls to customers for out-of-pattern transactions, or enabling customers to freeze cards/payments instantly via apps. Some banks allow customers to set limits or “allow lists” on beneficiaries.
On the institutional side, automated alerts from the fraud engine prompt analysts to act in real time (e.g., blocking a wire before it goes out). This rapid alert-and-response reduces losses significantly.
For example, VALID Systems reports that implementing real-time check fraud alerts (CheckDetect) enabled a U.S. bank to prevent 85% of attempted check fraud and cut check-related losses by 73% in three months.
Decision orchestration platforms
These are systems that integrate multiple fraud controls and data sources into one “decision center.” For instance, they can route a suspicious transaction through layered checks (device ID match, velocity check, sanctions list, negative news search) and then assign a risk score. The orchestration platform decides on the fly whether to approve, decline, or escalate for review, based on business rules and risk thresholds.
Analytics and intelligence sharing
Beyond real-time tools, technology also supports retrospective analytics. For example, link analysis tools build networks of related transactions (revealing mule accounts or layered laundering). Natural language processing can scan unstructured data (call transcripts, emails, social media) for fraud clues.
VALID Systems fraud risk management: preventing losses before they occur
Fraud always exists, but institutions can contain it. By pairing innovative management with real-time scoring, cross-channel intelligence, and consortium data, financial institutions can shift fraud from a persistent drain into a controlled risk.
VALID Systems equips banks, credit unions, and fintechs to protect customers while strengthening the bottom line.
Fraud risk management today is about one thing: acting before losses hit the books. This is where VALID Systems delivers measurable impact with:
- AI-powered deposit protection: CheckDetect® flags suspicious checks in real time, stopping fraud at the point of presentment. This solution alerts you to over 75% of potential check deposit charge-offs with pinpoint accuracy, enabling you to implement efficient treatments at the point of presentment.
- Instant funds, zero losses: InteliFUNDS® clears 99% of deposits in real time and fully absorbs charge-offs, protecting your balance sheet while upgrading customer experience.
- Consortium advantage: With visibility into over 450M accounts and $4T in annual transactions, VALID’s Edge Data Consortium exposes mule accounts and coordinated scams no single institution could detect alone.
Make fraud risk management proactive, not reactive.
Learn how VALID Systems empowers institutions to detect and stop fraud before it becomes a loss.