
Elder sextortion: The emotional and financial toll
Financial exploitation of older adults continues to evolve as fraudsters shift their tactics to digital platforms. According to the FBI's Internet Crime Complaint Center (IC3) 2024 data, more than 147,000 Americans aged 60 and older reported falling victim to online fraud, with total losses approaching $4.9 billion. This represents a 43 percent increase in reported losses compared to 2023.
Among these crimes, elder sextortion stands out as one of the most emotionally and financially damaging. Elder sextortion is a form of blackmail that combines romance scams, impersonation, and manipulation to target older adults online. A 2024 study published in Computers in Human Behavior estimated that one in seven adults globally has experienced someone threatening to share intimate images.
The FBI reports that extortion, including sextortion, among older adults increased by 134 percent year over year. These are not isolated incidents. They are part of a growing trend in digital crime affecting some of the most vulnerable members of our communities.
For community banks and credit unions, responding to this threat is not simply a matter of fraud detection. It is about protecting customers, preserving trust, and reinforcing the financial institution's role as a safe, trusted partner.
What is elder sextortion
Elder sextortion occurs when scammers deceive older adults into sharing explicit photos, videos, or engaging in private online interactions. The fraudster then uses that content, or the threat of having it, to extort money. In many cases, the scammer never actually possesses any images. Instead, they rely on fear, shame, and the victim's concern for their family, social circle, or religious community to force compliance.
These cons often begin as online romance scams. Fraudsters are patient and calculated, gradually building emotional trust before introducing explicit content or requests. The scammer starts making demands once the relationship feels real to the victim.
While financial loss is significant, the emotional toll can be devastating. Many victims do not report the crime due to embarrassment. The resulting shame may lead to social withdrawal, depression, or, in some cases, even premature death.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertHow scammers target older adults
Criminals executing sextortion scams use sophisticated tactics that take advantage of the emotional, digital, and social vulnerabilities of older adults. These include:
- Preying on loneliness or grief: Scammers identify recent widows or widowers by scanning online obituaries or public posts. They initiate contact under the guise of companionship.
- Romance scams on digital platforms: Many scams begin on dating apps, social media, or text messaging. Initial messages may seem innocent or friendly, but quickly turn flirtatious.
- The "wrong number" trick: A scammer pretends to text the wrong number. If the recipient responds, the conversation escalates into a manufactured romantic interest.
- Fake profiles and video calls: Scammers use images of attractive individuals, often stolen or computer-generated, and may encourage victims to engage in private chats. Some use deepfake technology or screen recordings to fabricate compromising content.
- Phishing links and malware: Clicking on suspicious links can give scammers access to the victim's device, camera, or personal files. Older adults with limited cybersecurity protections are particularly vulnerable.
These methods exploit both emotional trust and gaps in digital literacy. Increasingly, these scams are not random acts. Many are carried out by transnational organized crime groups that share victim information and target retirement communities or individuals identified through data breaches.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
fraud detection softwareWhen sextortion escalates
A recent case reported to the AARP Fraud Watch Network Helpline involved a 70-year-old man from Missouri. He was targeted through what he believed was a romantic relationship. After sending nude photos, he was quickly threatened with exposure unless he paid $2,500.
Soon after, another person contacted him, pretending to be a law enforcement officer. This impersonator accused him of criminal behavior related to the images and warned that his employer would be contacted if he did not send more money. The scammer knew where the man worked, intensifying the pressure.
This case demonstrates how sextortion can quickly evolve from emotional manipulation to impersonation and coercion. It also highlights the importance of financial institutions being prepared to spot signs of distress, especially when older customers make unusual transactions or appear anxious.
Protecting clients from fraud: Steps to stay safe
Fraud can happen to anyone, but the FBI advises there are practical steps financial institutions can coach their clients on to help protect them and their personal information:
- Verify before trust: If a client is contacted by someone they do not know, they should take time to research the contact’s name, phone number, email address, or the offer they are presenting. A quick online search can often reveal warnings from others who may have been targeted by similar scams.
- Avoid being rushed: Scammers often try to create urgency to pressure victims into making quick decisions. They may appeal to their emotions or promise financial gain or companionship. Advise clients to take a step back and give themselves time to evaluate the situation.
- Never share sensitive information: Clients should never give out personal or financial information, including social security number, bank details, or wire instructions, unless they have verified the legitimacy of the request.
- Take immediate action if an account is compromised: If your client suspects someone has gained access to their personal devices or financial information, they should notify their bank or credit union right away. Advise them about placing additional safeguards on their accounts and remind them to monitor their activity closely for unauthorized transactions.
How financial institutions can protect their customers from elder sextortion
Banks and credit unions serve as critical touchpoints for many older adults. When staff are trained to recognize potential fraud, they can help stop scams before more harm occurs. Proactive steps include:
- Educate frontline employees: Tellers and customer service teams should be trained to spot red flags such as abrupt wire transfers, large cash withdrawals, or changes in financial behavior. Empower staff to ask respectful, nonjudgmental questions when something seems unusual.
- Use fraud detection tools: Implement systems that monitor behavior outside a customer's typical transaction pattern. Real-time wire fraud monitoring combined with behavioral analytics helps stop fraud losses before they occur. Banks and credit unions should combine technology with transparent internal escalation processes.
- Provide targeted client education: Offer ongoing education through brochures, in-branch events, webinars, or one-on-one consultations. Topics include safe online practices, how to identify scams, and how to respond to suspicious messages.
- Partner with external agencies: Establish relationships with local law enforcement, elder protection agencies, and fraud reporting centers. Coordination can lead to faster, more effective responses when fraud is suspected.
- Foster a safe, supportive environment: Many older adults fear being judged or losing independence if they disclose being scammed. Creating a culture of support and privacy encourages disclosure and early intervention.
Why action matters
As more older adults embrace digital communication, the threat of elder sextortion will continue to grow. Financial institutions are in a strong position to detect early warning signs and respond with compassion and professionalism.
Preventing financial loss is essential, but helping clients preserve their dignity, feel supported, and recover from emotional harm is just as important. Addressing elder sextortion goes beyond risk mitigation. It reflects the core mission of community financial institutions to serve and protect. With strong fraud detection tools, well-trained teams, and a commitment to client care, banks and credit unions can be a first line of defense against this increasingly personal exploitation.

FinCEN Investment Advisor Rule delay: A shift in regulatory priorities
On Aug. 5, 2025, the Financial Crimes Enforcement Network (FinCEN) issued an Exemptive Relief Order delaying the effective date of the Investment Adviser Rule. The delayed effective date gives some breathing room to affected advisers and their banking partners for adjusting systems, training staff, and coordinating with technology vendors. However, financial institutions would be wise to nevertheless begin planning for implementation, given the importance of the rule’s ultimate goal of protecting the U.S. banking system.
Once implemented, the rule will require certain investment advisers to establish formal anti-money laundering/countering the financing of terrorism (AML/CFT) programs, maintain detailed records, and file suspicious activity reports (SARs). Finalized on Sept. 4, 2024, the rule extends long-standing Bank Secrecy Act (BSA) obligations, already applied to banks, credit unions, and broker-dealers, to segments of the investment industry that have not been covered.
It was originally set to take effect Jan. 1, 2026, but now the Treasury Department has exempted covered investment advisors from all rule requirements until Jan. 1, 2028. FinCEN intends to issue a notice of proposed rulemaking (NPRM) to propose a new effective date for the rule no earlier than Jan. 1, 2028.
Why FinCEN issued the delay
FinCEN said it issued the relief order to ensure the regulation is “efficient” and “appropriately balances costs and benefits” following industry feedback. According to the relief order, the extension is intended to:
- Allow investment advisers to design and implement effective AML/CFT programs without creating undue operational risk;
- Provide time for FinCEN to develop additional guidance and respond to industry feedback on rule interpretation;
- Support coordination between investment advisers and financial institutions to ensure consistent application of due diligence standards;
- Avoid compliance bottlenecks that could arise if thousands of newly covered entities rushed to meet the same deadline.
These statements are a significant shift from FinCEN’s stance when the rule was finalized in 2024. FinCEN issued the rule after carefully considering public comment and extensive consultations with staff and various government and industry advisors. At that time, FinCEN determined that the rule would:
- Help prevent criminals from laundering money through the U.S. financial system
- Improve the U.S. financial system’s transparency and integrity
- Provide beneficial information to law enforcement authorities
- Bring the U.S. into greater compliance with international AML/CFT standards and address a significant gap identified by the Financial Action Task Force (FATF)
The delay reflects a broader regulatory approach under the federal government’s current administration, which has emphasized deregulation to reduce perceived compliance burdens across multiple sectors. Even so, the underlying need to protect the U.S. financial system from illicit actors remains, and any delay in implementation should be balanced with measures that preserve the integrity and security of our banking system.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertWhy the delay matters to financial institutions
Even though the delay offers breathing room, it is still recommended that financial institutions begin preparing. Once implemented, the rule will influence how they work with investment adviser clients and bring greater alignment in compliance expectations across the industry. While banks and credit unions are not the primary targets of the rule, it will likely impact their compliance priorities, especially in customer due diligence (CDD) and coordinated financial crime prevention, assuming an effective date is eventually set.
This pause is a chance to get ahead of the ripple effects. Institutions should be ready for:
- Requests for closer collaboration from adviser clients
- More consistent application of CDD standards
- Heightened regulatory scrutiny once the rule takes effect
Acting now can help avoid last-minute disruptions, prevent operational bottlenecks, reduce compliance risk, and position banks and credit unions for smoother coordination with investment adviser clients when deadlines return.
We recommend that banks and credit unions prioritize the following actions for eventual compliance:
- Update policies and procedures: Review and revise AML/CFT policies to address the specific risks and compliance expectations tied to investment adviser relationships. Document procedures for onboarding these clients, including when to apply enhanced due diligence, how to verify beneficial ownership information, and escalation steps when unusual or suspicious activity is detected. Ensure these policies are consistent across business lines so retail and commercial teams follow the same standards.
- Evaluate technology readiness: Work with your AML software provider and core system vendor to confirm that existing platforms can handle expanded monitoring rules, higher volumes of alerts, and any additional data points associated with investment adviser accounts. Consider testing automated scenarios now to identify gaps in detection logic or reporting capabilities. Build in time for any needed upgrades, integrations, or workflow adjustments before the rule’s compliance date.
- Train compliance and frontline staff: Develop targeted training for employees on how investment adviser business models operate and the unique risks they may present. Include case studies on common red flags such as layered transactions, unexplained transfers between client accounts, or the use of complex corporate structures. Reinforce escalation and SAR filing procedures, especially as the FinCEN Investment Advisor Rule delay concludes and expectations increase.
- Refresh AML/CFT risk assessments: Update your institution’s AML/CFT risk assessment to reflect the potential impact of serving investment adviser clients. Consider how these relationships might influence customer risk ratings, monitoring thresholds, and the allocation of compliance resources. Document any changes in risk mitigation strategies so they can be communicated to regulators during examinations.
Next steps
The delay in the FinCEN Investment Advisor Rule is a limited opportunity for banks and credit unions to get ahead of future compliance demands. While the deadline has shifted, the expectation to maintain strong AML/CFT programs has not. Institutions that use this time to enhance monitoring processes, test technology, update risk assessments, and strengthen staff expertise will be well-positioned to adapt quickly when the rule takes effect. Early preparation reduces operational and regulatory risk and reinforces an institution’s role in safeguarding the U.S. financial system from illicit activity.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
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Day 2 accounting work can get tricky
Following a deal, financial institutions need to recognize the accretion or amortization of purchase accounting marks in an auditable and transparent way. Don't overlook income recognition.
Deal activity is heating up; be accounting-ready
With deal activity heating up again, bank and credit union leaders can’t afford to be caught flat-footed when it comes to the accounting side of a merger.
There were 72 U.S. banking M&A transactions in the first half of 2025, and according to a mid-year review from Ankura Consulting Group, this year could see the highest deal count in more than five years. That’s good news for institutions looking to grow, but it’s also a reminder that critical financial reporting follows a deal.
Income recognition, in particular, is one of those areas that can get overlooked until it’s too late. Now’s the time to line up a merger accounting playbook that’s audit-ready and built to scale.
Abrigo's experts handle Day 1 and Day 2 accounting, exit pricing, and other quarterly services.
See available servicesIncome recognition accounting can’t be an afterthought
Closing a bank acquisition is a big milestone, but it’s really just the start of the hard work. Day 2 accounting—particularly income recognition—is where things can get tricky fast. These purchase marks can be material to earnings, and if financial institutions aren’t paying attention to how they flow through their systems, they might set themselves up for issues with auditors and regulators. Abrigo Advisory has seen this firsthand. A lot of institutions get focused on valuation and CECL planning tied to a deal, and they treat income recognition almost like an afterthought. That can be a costly mistake.
What drives the complexity is the materiality of purchase marks (fair value adjustments). Deferred fees and costs, which are accounted for under the same accounting standard, aren’t significant enough for expedients to generate material differences.
Fair value adjustments, especially in dynamic rate environments, are significant, and it is the responsibility of management to understand how these amounts find their way into the income statement.
The core and income recognition: A recipe for auditor questions
A lot of institutions figure they’ll run the accretion through the core system or track it in a spreadsheet. The problem is, that only gets you so far. ASC 310-20 is the accounting standard that describes the treatment for recognizing fees, costs, fair value adjustments, etc., over the life of the loan as an adjustment to yield. As such, management should be able to recalculate yields, reconcile beginning and ending marks between reporting periods, accelerate and decelerate accretion in order to maintain yield, and provide loan-level positions. If not, something is missing.
To make matters more challenging, we've seen numerous cases where the valuation was calculated at a pool level with purchase marks subsequently being allocated to each underlying loan. This approach results in irrational yields and subsequent problems with loan-level accretion.
Time and time again, we've seen the inability of management to get any information or clarity from core-calculated accretion. When a parallel calculation is performed accurately, the results are significantly different. That’s why we always push for loan-level granularity from the beginning. It gives you control and defensibility.
CECL and income recognition
Some folks ask, “Well, can’t we handle all of this with our CECL model?”
If you’re talking about how marks flow into your allowance or how expected credit losses for acquired loans need to be calculated on Day 1 and for each subsequent reporting period, then yes, there’s overlap. But the allowance isn’t income recognition. They touch, but they’re not the same. As its name implies, the current expected credit loss (CECL) model is about expected credit losses. Income recognition is about amortizing or accreting a known mark into earnings over time. Different accounting standards and different processes.
Documentation matters here more than people think. If you can’t explain why income is rising or falling as those marks burn off, someone’s going to start asking questions. What you don’t want to happen is to get caught flat-footed by assuming the core system was handling it, or by the person who built the spreadsheet leaving without someone else knowing how it worked. That’s not a position you want to be in.
Abrigo built income recognition software with all of this in mind. It takes in the purchase marks, handles both base and accelerated accretion, and ties back to CECL where needed. Everything is transparent and auditable at the loan level.
But regardless of what system you’re using, the point is this: don’t wing it. You need a process that scales and holds up when someone comes asking to see the details.
Who really owns the income recognition process?
We’d also encourage banks not to treat income recognition as a bolt-on task. If you’ve got one firm doing the valuation and another firm helping with CECL, and no one really owning income recognition, you’re going to have gaps. Those gaps usually show up in audits. What you want is someone who can help you stitch the full process together, someone who’s been on calls with examiners and knows what they’re going to ask.
Income recognition isn’t the flashiest part of a deal, but it’s one of the most important parts when it comes to the integrity of your financials. It’s where the marks you put on at close start hitting your earnings every month. A problem isn’t simply a technicality; it’s visible. So get ahead of it. Build the right foundation. And make sure your process isn’t merely working—make sure it’s defendable.
See how your loan fair value estimates compare to market-based benchmarks.
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Fraud victim support: How financial institutions can respond and restore trust
As fraud schemes evolve in complexity and scope, financial institutions are called upon to do more than just detect and prevent illicit activity. Banks and credit unions often also serve as first responders when individuals or businesses fall victim to financial fraud.
Institutions that respond with urgency and empathy to support victims of fraud can rebuild trust, restore confidence, and reinforce long-term relationships with clients. But fraud victim support is about more than recouping financial loss. Understanding the common fraud schemes clients may encounter and taking an intentional approach to assist in the aftermath demonstrates an institution’s values, dedication to client care, and role as a trusted advisor within the community.
The growing cost of fraud
Reported fraud losses exceeded $12.5 billion in 2024, according to the Federal Trade Commission (FTC). The FBI documented an even higher total loss of over $16.6 billion across 859,000 complaints. These figures speak not only to the scale of financial harm but to the emotional toll these crimes leave behind.
The volume and impact of fraud are increasing across all channels. In 2024, investment scams topped the list in financial damage, with $5.7 billion in reported losses. Imposter scams followed closely at nearly $3 billion. Criminals prey on trusting and vulnerable people, and they continue to leverage digital platforms to initiate contact via email, phone, or text, and move funds through cryptocurrency, bank transfers, or wire services.
According to the FBI, phishing scams were the most frequently reported. However, business email compromise and investment fraud caused the most significant monetary damage. These trends highlight the urgent need for comprehensive fraud victim support programs that go beyond the basics of account recovery.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertUnderstanding the scope of fraud
Financial institutions must first understand the various forms of fraud affecting their clients to deliver meaningful assistance. Some of the most prevalent methods include:
- Cybercrime attacks: Cybercrime attacks occur approximately every 11 seconds, costing organizations an average of $13 million per incident. Small businesses are especially vulnerable due to limited cybersecurity infrastructure.
- Consumer fraud: Consumer fraud takes many forms, including synthetic identity theft, spoofing, romance scams, and grandparent scams. These often target the elderly and financially inexperienced.
- Business and investment fraud schemes: Scams such as Ponzi operations, business email compromise, and wire fraud continue to result in significant losses for commercial clients.
- “Pig butchering”: A particularly alarming emerging scam is known among criminals as “pig butchering” because victims are deceived over time through emotional manipulation before being persuaded to make large financial transfers.
Each scheme can leave a trail of emotional distress and financial disruption. A thoughtful, informed approach to fraud victim support is essential to help affected individuals navigate the aftermath.
A layered approach to fraud victim support
1. Prevention through education and technology
Preventing fraud begins with awareness. Banks and credit unions can help clients identify red flags by offering regular educational materials across digital and in-person channels. Topics include the creation of secure passwords, the identification of phishing attempts, and safe usage of peer-to-peer payment apps.
Technology also plays a pivotal role in prevention. Sophisticated fraud detection tools incorporating artificial intelligence and behavioral analytics can monitor suspicious activity in real time. Institutions can also empower their clients with biometric login, multi-factor authentication, and real-time fraud alerts.
- Helping clients create a response plan
Helping clients prepare a response plan before fraud occurs can reduce confusion and stress if the worst happens. Encourage clients to keep a written checklist that includes how to report fraud to their financial institutions, contact information for the FTC and FBI, and steps for freezing credit with the major bureaus. The plan should also cover resetting login credentials and enabling fraud alerts. Reviewing this plan regularly gives clients confidence that they know what to do and who to call. It is a simple way to support a long-term client relationship.
- Responding with clarity and compassion
A fast and empathetic response is critical following a fraud incident. Banks and credit unions should have clear procedures in place to support victim response plans, including measures around:
- Freezing or closing affected accounts
- Reissuing account credentials and payment cards
- Assisting with dispute processes and documentation
- Communicating directly with law enforcement when appropriate
Empowering front-line employees to handle these cases with care can help ease client anxiety and reestablish trust during a particularly vulnerable time.
- Supporting financial recovery
While banks and credit unions often must reimburse clients for unauthorized transactions, many fraud cases involve victims being tricked into authorizing payments. In these situations, reimbursement is not always guaranteed. Still, financial institutions can support victims with the following meaningful actions:
- Assist with regulatory reporting: Help victims file official complaints with the FTC, the FBI, or Consumer Financial Protection Bureau (CFPB). These reports establish a record of the incident and contribute to broader fraud tracking efforts.
- Work with law enforcement and other financial institutions: Cooperate with authorities and peer institutions to trace stolen funds and flag suspicious accounts. Swift action can help contain damage and may lead to partial recovery.
- Provide recovery resources: Refer victims to identity theft protection services, legal aid, or nonprofit support organizations. These resources can help clients manage credit impacts and protect against future fraud.
Even when full financial recovery is impossible, these steps demonstrate a commitment to care and accountability. Institutions prioritizing fraud victim support during recovery reinforce trust and deepen client relationships.
Sustained support beyond the incident
Helping a client through the immediate fallout of fraud is the first step. Ongoing protection is key to rebuilding confidence. Financial institutions can offer continued support through:
- Identity theft monitoring
- Credit and account activity alerts
- Help with placing credit freezes
- Referrals to advocacy groups for seniors or other vulnerable individuals
Staying engaged after the crisis helps banks and credit unions show they are not just financial service providers but also long-term partners in their clients’ security and peace of mind.
Making victim support a shared responsibility
An effective response to fraud must involve collaboration across internal teams. Anti-money laundering (AML), information technology, fraud prevention, and client service departments should operate under a unified plan to ensure quick and coordinated action. Regular training and updates on emerging fraud trends are essential.
Equally important is leadership support. Institutions that invest in fraud prevention tools, adequate staffing, and client education signal that fraud victim support is not a side function but a core priority.
Turning crisis into opportunity
Fraud response efforts should be viewed as risk mitigation and opportunities to lead with purpose. Financial institutions can demonstrate their commitment to ethical banking and social responsibility by standing with victims and guiding them through recovery. Banks and credit unions that take fraud victim support seriously will be better positioned to retain loyal clients, enhance their brand reputation, and serve as trusted pillars in their communities.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
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AI-driven elder fraud: Deepfakes; the newest threat
As artificial intelligence (AI) continues to advance, fraudsters are leveraging these tools to exploit one of the most vulnerable groups in our communities, older adults. According to the FBI's Internet Crime Complaint Center (IC3) data, there were $4.88 billion in losses from seniors in 2024. These numbers continue to trend upwards, and the rise of AI-driven elder fraud presents new risks to victims and financial institutions. AI-driven elder fraud involves scams that use artificial intelligence to make attacks against older adults more convincing, harder to detect, and easier to carry out on a large scale. The increased threat requires both awareness and proactive mitigation by banks and credit unions to protect clients and maintain trust in their communities.
The evolving tactics behind elder financial exploitation
Historically, seniors have fallen victim to fraud schemes such as phishing, romance scams, and complex investment schemes. Today's fraudsters are taking scams to a new level by using generative AI tools—such as deepfakes and voice cloning—to impersonate loved ones and create compelling, urgent scenarios. A deepfake is a video, photo, or audio recording that seems real but has been manipulated with AI. Perpetrators often extract voices from social media videos or manipulate photos to craft believable messages. These AI-powered deceptions can lead to hurried decisions by victims, resulting in panicked wire transfers, large cash withdrawals, or the sharing of sensitive account credentials.
In an example of an AI-enhanced grandparent scam, a fraudster might scan public social media profiles to learn a grandchild's name, see that they are vacationing abroad, and note that they call their grandparent "Nana." Using a voice-cloning tool and this easily accessible personal information, the scammer can generate a frightened phone call from the "grandchild" claiming to be in legal trouble and urgently needing bail money. The voice's realism and details make it alarmingly easy to convince the victim to send funds immediately, without stopping to verify the story. The nature of AI-driven elder fraud has made it more difficult to detect using traditional red flags. What once might have seemed suspicious can now appear legitimate, making staff training and innovative detection systems even more essential.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertWhat financial institutions can do now
Banks and credit unions are uniquely positioned to safeguard older adults through technology and personalized service. Here are some key actions institutions can take to prevent their clients from becoming victims:
- Employ robust fraud detection software: Enhance fraud monitoring systems to flag unusual activity on accounts held by older adults, typically aged 60 and above. Use tailored parameters to detect anomalies like sudden large wire transfers, frequent ATM withdrawals, or new payees that do not align with the client's typical behavior. These targeted settings improve your institution's ability to catch early signs of AI-driven elder fraud and take timely action.
- Train employees to recognize new scams: Equip front-line staff and fraud teams with practical training to identify signs of AI-driven elder fraud. These signs can include clients who appear anxious, confused, or unusually secretive during large transactions, or those referencing family emergencies with limited or inconsistent details. Staff should know how to respond empathetically, ask clarifying questions, and escalate concerns when needed. Regular training helps teams stay alert to evolving scam tactics and reinforces a culture of prevention.
- Clarify communication protocols: Remind clients, especially seniors, that your institution will never request sensitive information like passwords or social security numbers by phone, email, or text. Understanding communication methods is critical as AI-driven scams increasingly use cloned voices and urgent messages to pressure victims. Make it clear that legitimate staff will not use threats or demand immediate action. Encourage clients to hang up, verify requests by calling a published number, and ask questions. Reinforcing this message during visits, alerts, and outreach helps build confidence and reduce the risk of fraud.
- Build trust through relationships: Strong relationships with long-time clients are key to spotting and preventing fraud. Encourage staff to visit clients when something feels off, using a conversational tone to avoid alarming or upsetting the client. For example, saying, "That's a larger transaction than usual. Is everything okay?" can open the door for a helpful discussion. Building trust before issues arise makes it easier to address concerns if signs of elder fraud appear later.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
fraud detection softwareUnderstanding regulatory expectations
Financial institutions are expected to play a central role in identifying and reporting elder financial abuse. With AI-driven elder fraud rising, examiners and enforcement agencies may scrutinize how effectively institutions adapt to emerging typologies. The Financial Crimes Enforcement Network (FinCEN) has named fraud one of its national AML/CFT priorities, emphasizing the importance of proactive detection and reporting. Filing a suspicious activity report (SAR) is just one component; maintaining a culture of vigilance and continuous training is equally critical.
Institutions integrating fraud detection with anti-money laundering (AML) processes are better positioned to respond quickly to evolving threats. AI and machine learning can enhance monitoring by identifying unusual behavioral patterns that are common in modern fraud cases. While operational functions may remain separate, collaboration between fraud and AML teams is essential. Working in silos is no longer effective in detecting complex, AI-driven fraudulent activity.
Community education can prevent losses.
Technology is essential, but it is not the only solution. Many cases of AI-driven elder fraud can be avoided through targeted education and outreach. Consider hosting in-person fraud awareness sessions at senior centers, places of worship, or branch locations, where trusted staff can explain how fraudsters use AI to manipulate voices, images, and personal information. Partnering with local organizations or law enforcement can add credibility and help reach broader audiences. Institutions can also distribute printed guides or quick-reference tip sheets that walk through common scam scenarios, what to look out for, and how to respond. Posting short educational videos on your website or sharing alerts through account notifications and email campaigns reinforces these lessons and helps keep seniors informed between visits. A consistent focus on community education builds trust and positions your institution as a proactive ally in fraud prevention.
Practical tips to share with clients
Educating seniors with simple, actionable steps can go a long way in preventing AI-driven elder fraud. Consider sharing the following guidance during outreach efforts or in printed materials at branches:
- Confirm unexpected requests: If someone claims to be a relative in trouble or a representative from the bank, urge clients to hang up and call back using a known, trusted number, never the one provided in the message or call.
- Be cautious with links and urgent messages: Remind clients not to click on links, download attachments, or send money based on a single phone call, text, or video, even if the message appears to come from a loved one. AI tools can make fake messages seem personal and convincing.
- Enable account alerts: Encourage seniors to set up text or email alerts for large transactions or unusual activity. These real-time notifications can provide an early warning and allow for quick intervention.
- Review account activity regularly: Suggest checking account statements frequently or enrolling a trusted family member to help monitor for suspicious transactions.
Sharing these tips in clear, non-technical language can empower clients to act confidently and avoid becoming victims of increasingly sophisticated fraud attempts.
Protecting seniors in the age of AI
As fraud tactics evolve with AI, so must the strategies used to stop them. Financial institutions have a unique opportunity, and responsibility, to protect older clients through education, collaboration, and well-equipped fraud detection programs. By combining personal relationships with innovative technology and ongoing awareness efforts, banks and credit unions can serve as a first line of defense against AI-driven elder fraud. Staying informed and proactive today means safeguarding trust and financial well-being for the seniors who rely on you tomorrow.

AI value opportunities for banks and credit unions: A sample
AI is reshaping how financial institutions operate, compete, and deliver value. Learn some of the areas in banking where predictive and generative AI are creating the most value and where to start.
A framework for AI opportunity for financial institutions
Artificial intelligence (AI) is no longer a future-facing technology — it’s a present-day differentiator. Across banking, AI is reshaping how financial institutions operate, compete, and deliver value. From marketing to compliance, the most promising AI use cases in banking help organizations improve decision-making, reduce operational risk, and grow more efficiently. This article explores a sample of opportunities where AI creates the most value today by showing major areas of banking where artificial intelligence (either predictive or generative) can be useful. It also explains how financial institutions can safely begin or accelerate their AI journey and identify applications for the technology in their own banks or credit unions.
Learn the basics of AI and an approach to adopting it.
download whitepaperExamples of current AI applications across banking
There are two primary forms of AI driving transformation: predictive AI, which forecasts outcomes and detects patterns, and generative AI, which creates new content from existing data sources.
The graphic below illustrates dozens of current AI applications across the banking lifecycle.
Current applications of artificial intelligence across banking fall into six core areas of opportunity, described below along with examples of how financial institutions are already benefitting from AI on these fronts:
- Marketing and sales
AI enables personalized engagement and smarter targeting for bank and credit unions’ marketing and sales.
- Predictive models forecast customer lifetime value
- Generative tools create hyper-personalized messaging and offer recommendations
- AI segments audiences for cross-sell campaigns and streamlines onboarding
Personalizing content on JPMorgan’s mobile phone apps helped increase engagement rates by 25%, the company said during its May Investor Day.
- Prospecting and onboarding
AI can reduce friction in early-stage customer interactions for banking services.
- Automate document verification and identity validation
- Prepopulate onboarding forms and streamline KYC workflows
- Use chatbots for initial data collection and customer guidance
Costs to verify investment bank clients are down 40% where AI is being deployed across the workflow, JPMorgan also said.
- Credit risk underwriting and review
AI enhances accuracy and speed in credit decisions, helping lenders make good decisions quickly.
- Predictive models analyze cash flow, credit scores, and risk thresholds
- Generative AI assists in drafting credit memos and narrative summaries for loan reviews
- Real-time data integration supports more holistic, dynamic underwriting
Bankers Trust, a $7 billion community bank, reduced its commercial loan process for certain loans from two weeks to three to five days using Abrigo’s loan origination for smaller commercial loans, which automates decisioning and features AI-powered loan scoring. And Abrigo’s Loan Review Assistant allows credit risk review staff to evaluate credit quality and document insights in minutes rather than days.
- Operations
Financial institutions can improve back-office efficiency with AI automation.
- AI routes payments, classifies documents, and extracts insights
- Automated financial spreading saves hours of manual entry
- Collections strategies are optimized through borrower-level pattern recognition
NVIDIA’s latest survey of financial institutions’ use of AI found that more than 60% of respondents credited AI with helping reduce annual costs by 5% or more.
- Customer support
With artificial intelligence, financial institutions boost service quality while scaling support teams.
- Chatbots answer common questions and reduce call center volume
- AI listens to and analyzes call transcripts to coach agents and spot risk indicators
- Personalized engagement improves retention and satisfaction
Bank of America’s AI-driven virtual assistant for employees, Erica for Employees, reduced calls into the IT service desk by more than 50%, the bank said. Similar support improvements can benefit clients.
- Risk and compliance
Both predictive AI and generative AI enable institutions to meet regulatory demands with precision and agility.
- Alert narratives and ongoing due diligence tasks can be automated
- AI helps detect fraud patterns across transactions
- Compliance checks are embedded into loan review and audit workflows
Texas National Bank uses Abrigo’s AI-driven check fraud detection to identify fraudulent checks before they are cashed. Within just two months, the bank identified and prevented over $377,000 in fraudulent check transactions.
Altogether, these banking AI use cases drive measurable business benefits: faster loan decisions, higher operational efficiency, improved accuracy, and reduced churn.
Check out helpful AI resources for bankers, including an AI-readiness checklist.
AI resourcesHow to prioritize projects when implementing AI
The range of available AI use cases in banking can feel overwhelming. But successful institutions typically begin with focused, high-impact projects that align with their data readiness and staffing capacity.
To start:
- Partner with trusted providers who understand regulatory frameworks and can integrate AI into existing systems. Abrigo prioritizes data security and privacy by developing AI technology with stringent data protection measures, using encrypted data environments and robust access controls to secure client data. Make sure that any vendors you choose have similar controls in place. You may choose to consider vendors that specifically work with financial institutions so that you can be sure their solutions fully comply with banking regulations. Vendors should be continuously monitoring regulatory landscapes to ensure their solutions meet legal and regulatory requirements.
- Experiment with pilot programs such as automating credit memos or onboarding flows to introduce AI one process at a time. Identify and prioritize low-risk, high-value pilot projects, and make sure that leaders from across the organization are united when assessing the feasibility, risks, and intended outputs before starting a project. Once an AI tool is adopted, conduct ROI analysis regularly to make sure the new process is working as intended.
- Educate your team on what AI is and what it isn’t to build buy-in across departments. While AI automates certain tasks, it primarily augments the capabilities of banking staff by allowing them to focus on more complex and strategic activities. Done well, this enhances job satisfaction and productivity. Make sure staff are well-trained and emphasize that a human-in-the-loop is always necessary to keep AI processes running smoothly.
From AI’s value potential to AI’s value creation
Long-term AI success requires thoughtful governance, clean data inputs, and strategic planning. With the right use cases and the right partners, banks and credit unions can unlock the true value of AI: accelerating growth, reducing risk, and improving every interaction.
See how an AI assistant shaves days off the loan-review process for more efficient credit risk review.
Loan review assistant
Tackling a global epidemic
With fraud at an all-time high, complex scams are at the forefront of financial concerns among consumers and small business owners (SBOs). The FBI 2024 Internet Crime Report details reported losses exceeding $16 billion for 2024, a 33% increase in losses from 2023, and the trend doesn’t seem to be slowing.
Artificial intelligence (AI) is profoundly reshaping the fraud landscape, and Americans are taking notice. While many are concerned with the fraud risks AI introduces, there is growing recognition that AI can be an essential tool for fighting financial crime. Banks and credit unions face a key challenge in protecting clients from AI-driven fraud while using the same technology to detect fraud and strengthen trust.
How is AI used to commit fraud: Client concerns and vulnerabilities
According to the 2024 Abrigo Fraud survey, more than 83% of respondents express concern about AI-assisted fraud, and nearly 60% say they are either extremely or very concerned. That level of anxiety stems in part from personal experience. One in four respondents has either been a victim of AI-related fraud or knows someone who has. The numbers for small business owners (SBOs) are even higher, with 40% reporting they have personally experienced AI-enabled fraud.
The most common concern among respondents is the loss of control over private personal information (PPI), with 57.5% citing high-tech identity theft as their top fear. Additionally, AI-generated deepfake videos and voice cloning now mimic loved ones with unsettling accuracy, making schemes like grandparent scams more convincing than ever. AI-enhanced phishing emails are harder to detect, thanks to flawless spelling, grammar, and tone. These advancements are also fueling more sophisticated business email compromise (BEC) attacks, an escalating threat that organizations of all sizes must take seriously.
Need short-term fraud or AML staffing relief? Abrigo Advisory Services can help.
Connect with an expertAI is also a part of the solution
Despite the concern, many consumers believe AI can improve fraud detection. 43.5% of survey respondents say that knowing their financial institution uses AI for fraud prevention would increase their confidence in that institution. Another 41% say they are at least interested in using AI-powered tools to monitor their accounts.
Interest among SBOs is even stronger. Nearly 70% of SBO survey respondents say AI fraud detection would make them feel more secure. This is an essential takeaway for financial institutions. Clients are not rejecting AI; they want to know it is being used responsibly and effectively to protect their financial security.
More intelligent detection with Abrigo Fraud Detection
Abrigo Fraud Detection uses AI and machine learning to identify suspicious patterns across channels while improving efficiencies. By combining behavioral analytics with real-time risk scoring, the solution helps institutions detect and stop fraud faster. More importantly, it improves operational efficiency by reducing the number of false alerts that drain time and resources.
This advanced technology matters because the true cost of fraud goes far beyond the dollar amount stolen. It includes hours spent investigating cases, losses in client trust, and emotional strain on victims. In the survey, 56.4% of fraud victims reported stress or anxiety, and 54.1% said they spent significant time resolving the issue. With Abrigo, institutions can take action earlier, resolve fraud faster, and avoid unnecessary disruptions for legitimate clients.
Awareness and education gaps remain
While many respondents hope AI can enhance fraud prevention, more than half say they need to learn more before feeling confident in its role. At the same time, 52% of respondents do not know whether their bank uses AI for fraud detection. This lack of understanding suggests that even well-developed fraud prevention programs may fall short if not clearly communicated to clients. Educational efforts that explain how AI safeguards financial data could go a long way toward building trust, especially among the most concerned demographics.
Key fraud trends for banks
The rise of AI-enabled scams coincides with broader fraud trends that clarify the urgency of the situation. In the past year alone, 26.4% of respondents experienced fraud in their financial accounts. Of those affected, more than half reported stress or anxiety, and 40% suffered economic losses. SBOs reported higher exposure and spent more time resolving fraud incidents.
These findings reflect a broader sentiment that fraud is no longer an abstract threat but a frequent and disruptive reality. Yet only 10.1% of survey respondents feel prepared to defend against emerging threats. More than 68% say banks should carry the primary responsibility for protecting consumers from fraud.
Moving forward: Clear strategy and communication
Financial institutions have an opportunity to lead in both action and education. That starts with a clear strategy for adopting and communicating the use of AI in fraud detection. It also means investing in tools that effectively detect suspicious activity and offer meaningful transparency to clients.
Clients want to know their financial institution is paying attention to the threat landscape and adjusting accordingly. They want real-time alerts, stronger authentication options, and reassurance that modern tools protect their financial data.
Understanding how AI is used in fraud is no longer just a technical issue. It is central to the client experience, risk management, and institutional trust. Banks and credit unions that take a proactive, transparent approach will be better positioned to retain client confidence and respond effectively to AI as an evolving threat.
Measuring the cost of fraud losses
The true cost of fraud goes beyond initial monetary losses. Read on for factors your institution should consider in its plans to combat fraud.
Consumer and bank fraud loss statistics
Today's financial institutions are grappling with significant rises in various types of fraud.
Check fraud has surged, driven by the exploitation of vulnerabilities in the postal system, with fraudsters using techniques like mail theft and check washing. FinCEN reports that Suspicious Activity Report (SAR) filings for check fraud in 2024 alone exceeded 521,000, nearly doubling the number of filings the previous year. Check fraud in 2024 was projected to reach a staggering $24 billion globally.
Online fraud, including investment scams and pig butchering scams, has also escalated, with sophisticated schemes targeting unsuspecting investors. While some of the recent trending fraud schemes are not new, they have been transformed to prey on communities already dealing with unprecedented times.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertThe factors mentioned above created abundant opportunities for fraudsters, and financial institutions and consumers must stay one step ahead to protect themselves from falling victim to a myriad of fraud schemes. According to the FTC, consumers lost more than $12.5 billion to fraud in 2024. This marks a 25% increase over 2023. More consumers reported losing money to investment scams—more than $4.6 billion—and the second-highest fraud category was imposter scams, with fraud losses of nearly $5.7 billion reported. The FTC also reports that consumers lost more money to bank transfer and cryptocurrency fraud than all other methods combined. This, of course, doesn’t include fraud losses that were not filed due to the victim's embarrassment or lack of knowledge on how to report. No matter the medium used, it is clear fraud continues to grow and cannot be ignored.
The true cost of fraud extends far beyond direct financial losses. There are many ways that fraud losses impact financial institutions' bottom line and its hidden costs can add up. Institutions must invest not only in advanced security measures and skilled personnel but also in client education and community engagement to combat fraud effectively.
Geographic and sector variations in fraud risk
Fraud impacts financial institutions differently depending on both their geographic location and sector.
Geography
Studies show significant variation in fraud costs across regions, with U.S. and Canadian institutions facing rising losses. Canadian firms, for example, saw a 28% year-over-year increase in the cost per dollar of fraud, reaching $4.45 in 2023, while U.S. firms averaged $4.41 per dollar lost. Within the U.S., states like North Dakota and New York experience the highest per-victim losses, but states such as Rhode Island and Alaska report the most fraud incidents per capita.
Sectors
Sector-wise, banks, fintech companies, and credit unions all report increases in fraud attempts, but the financial impact and attack vectors differ: fintechs, for instance, may face higher exposure to digital and mobile fraud, while traditional banks contend with check and ATM fraud. Understanding these geographic and sector-specific patterns is crucial for tailoring effective fraud prevention strategies.
3 pillars for evaluating the costs of fraud
Leaders within financial institutions are frequently tasked with grasping the full scope of a bank's fraud losses and their impact. It's essential to recognize that the repercussions extend far beyond the immediate monetary losses from each fraudulent transaction. To fully appreciate the actual cost of fraud, one must delve into its complex nature and wide-ranging effects.
1. Hard dollar losses
The first pillar encompasses the overall hard dollar loss rate experienced from illicit transactions. This represents the immediate financial hit impacting the bottom line, including not only the amount of funds extracted by fraudulent means but also the associated financial repercussions, such as transaction reversal costs and compensation paid to affected clients. While this tangible loss is the easiest to quantify, it merely scratches the surface of fraud-related costs.
2. Technical and human resource costs
The second pillar concerns the cost of technical and human resources dedicated to fraud prevention, detection, and remediation. The race against fraudsters demands continuous investment in cutting-edge technologies designed to safeguard against intrusion and theft. Additionally, the human capital investment—in terms of both hiring fraud prevention experts and training existing staff—constitutes a significant operational expense. These costs are necessary and ongoing, forming a crucial barrier against fraud scams.
3. Client value impact
The third pillar, the client value impact, addresses attrition rates following fraud incidents. The erosion of trust caused by fraud can lead to a decline in client retention, a critical issue for financial institutions. Each client lost to fraud represents future revenue streams that are now gone. The relationship between fraud incidents and client departure is a serious concern, as the institution not only loses the lifetime value of the client but also incurs higher costs in attempting to acquire new clients to fill the void.
By understanding these three pillars, leaders can better assess the true cost of their bank's fraud losses and allocate resources more effectively to mitigate its impact.
Additional consequences of fraud loss: Non-financial risks
Reputational risk
Separate from these pillars, financial institutions suffer reputational risk whenever a client falls victim to fraud scams. The damage inflicted on an institution’s reputation after a fraud incident can have extensive ramifications. A tarnished reputation can deter potential clients and negatively affect existing relationships, as trust is critical in a financial relationship. According to research by Javelin Strategy & Research, 31% of clients are more likely to leave the financial institution after a fraud event, even when the bank or credit union is not at fault.
Regulatory risk
Regulatory risk is yet another significant concern. Failure to meet regulatory standards can result in regulatory sanctions, fines, and a mandate for expensive corrective measures. Moreover, non-compliance can lead to enhanced scrutiny by regulators and the possibility of heightened requirements in the future.
The Financial Crimes Enforcement Network (FinCEN) has listed fraud and cybercrime as two of its National AML/CFT Priorities. This is the first time fraud has been addressed at a high level as part of AML compliance, but it makes sense considering proceeds from fraudulent activity must be laundered.
With fraud now considered an AML/CFT priority, regulatory penalties and fines around fraud may be something to consider in future exams. Regulators are expecting financial institutions to address each of the priorities in their AML/CFT program, and when there are deficiencies, you can expect criticism and possibly monetary penalties. Now is the time to be sure that your fraud, AML, and IT security teams collaborate and keep each other informed on illicit trends they are detecting.
Best practices for fraud risk management: A checklist to prevent bank fraud losses
Financial institutions must approach fraud with a comprehensive strategy that accounts for direct financial loss, resource allocation, and the broader implications on client value, reputation, and regulatory standing. It is a continual battle requiring vigilance, innovation, and a commitment to safeguarding all stakeholders. Things to consider include:
- Hardware: Is your business data safe, and are updates and patches applied timely? They should always be.
- Software: Do you have adequate fraud detection software? Are you able to detect various types of illicit activity, such as check, wire, and ACH fraud?
- People: Do your investigators receive proper training? Do they have the correct skill set to detect complex patterns of fraudulent activity?
- Client education: Does your institution have avenues for client education, such as written materials, online warnings, or in-person seminars for clients and prospects? If not, this is a great way to foster community goodwill and deter fraud at the same time.
Industry innovations in fraud risk management
Abrigo is at the forefront of industry collaboration and innovation, providing U.S. financial institutions with advanced technology solutions to combat fraud more effectively. By centralizing data and integrating compliance, risk management, and fraud detection tools, Abrigo enables organizations to work more efficiently and share critical intelligence across teams. Our platform supports collaboration between fraud, AML, and IT security departments, ensuring that emerging illicit trends are quickly identified and addressed.
Software solutions
Abrigo’s commitment to innovation is reflected in its comprehensive suite of fraud detection software, which leverages cutting-edge analytics to detect various types of illicit activity, from check and wire fraud to more complex schemes.
Education
Additionally, we promote industry best practices by offering resources for your professional education and community engagement, helping institutions stay ahead of evolving threats and reduce the overall cost of fraud.
For more information about Abrigo’s collaborative approach and solutions, visit our Fraud Prevention and Fraud Detection Software pages.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
fraud detection software
How financial institutions can disrupt financially motivated sextortion
Teenagers are being targeted online, coerced into sharing explicit content, and extorted for money, sometimes with devastating consequences. Financially motivated sextortion of minors is a rapidly growing crime, fueled by organizations exploiting digital platforms and payment systems. As the financial gateway for many of these transactions, banks and credit unions are uniquely positioned to intervene and help protect the most vulnerable members of their communities. According to the FBI, financially motivated sextortion schemes have led to a troubling number of victim suicides.
While sextortion is not new, its evolution into an organized, profit-driven enterprise run by transnational criminal organizations (TCOs) introduces a new front in the fight against financial crime. Understanding the financial red flags of this illicit activity is critical for institutions committed to protecting their clients and communities.
What is financially motivated sextortion?
Financially motivated sextortion of minors involves offenders, often impersonating teenage girls, coercing boys into sharing explicit content. Once obtained, perpetrators demand payment under the threat of exposure. These scams unfold rapidly, exploiting the victim's fear and isolation.
Criminals frequently operate through fake social media or gaming accounts, gaining victims' trust before launching their threats. As detailed by the FBI, these actors often work in networks, and many are based overseas, using digital tools to remain anonymous and evade prosecution.
According to the FBI, while both boys and girls are victims of sextortion, the majority of victims in financial sextortion cases are boys. This distinction is important because traditional sextortion (motivated by a desire for sexual gratification or control) more often targets girls, but financially motivated sextortion disproportionately affects boys. Most victims are aged 14 to 17, though younger children are also targeted.
This crime has become widespread in the U.S.. In 2024, the FBI received 54,936 complaints about sextortion with $33.5 million in losses. If financial institutions can detect and stop the flow of payments, they can help reduce both the incentive and the harm.
Staying on top of fraud is a full-time job. Let our Advisory Services team help when you need it.
Connect with an expertThe flow of money in sextortion
Teen sextortion victims often lack access to traditional banking tools, which makes them more likely to use financial products that don't require adult co-signers or government-issued ID. These include:
- Peer-to-peer (P2P) payment apps like Cash App, Venmo, and Zelle
- Prepaid or gift cards purchased with cash
- Digital wallets like Apple Pay or Google Pay
- Cryptocurrency wallets or ATMs
The Thorn.org report found that Cash App was the most frequently used payment method in recent sextortion reports to the National Center for Missing and Exploited Children (NCMEC), followed by gift cards, PayPal, and Venmo. These platforms offer easy access and, in many cases, limited oversight of these types of transactions.
Some perpetrators also use teen victims as money mules, coercing them to receive payments from other victims and forward the funds. This tactic adds another layer of complexity, making tracing funds directly to criminal networks harder.
Find out how Abrigo Fraud Detection stops check fraud in its tracks.
fraud detection softwareRed flags for financially motivated sextortion
Financial institutions play a vital role in recognizing the transaction patterns associated with sextortion schemes. While many financial crimes share similar indicators, this typology has several distinctive hallmarks:
- Unusual payment memos or notes
Many P2P platforms allow users to include a description or memo with a transaction. Sextortion-related payments have included phrases like:
- "delete video"
- "release"
- "for blackmailing"
- "please, I don't want to die"
Perpetrators may also instruct victims to use misleading memo lines such as "for tutoring" or "gift," which can be an attempt to bypass detection. Transactions with emotionally charged, unusual, or vague descriptors warrant scrutiny, especially from teen-linked accounts.
- High-risk activity on teen accounts
Many platforms offer limited real-time parental controls even when teen accounts are sponsored by parents or guardians (as in Cash App or Venmo teen accounts). Watch for:
- Transactions outside of regular hours (late night or early morning)
- Multiple small transfers in quick succession
- New recipient accounts with no history of prior interaction
- Attempts to override parental settings or rapidly turn off alerts
- Gift card purchases followed by digital redemption
Teens often purchase gift cards in-store and send codes to perpetrators via messaging apps. This physical-to-digital payment conversion is a hallmark of many scams, but its prevalence among teens makes it a critical red flag. Unusual spikes in gift card purchases by minors, particularly gaming or retail cards like Steam, Apple, or Amazon, could signal sextortion.
- Rapid movement of funds internationally
Some sextortion proceeds are sent to international recipients, often via cryptocurrency or P2P transfers. Transactions originating in teen-linked accounts quickly converted to crypto or routed through Zelle or Cash App accounts linked to non-U.S. phone numbers or IP addresses may suggest laundering activity.
- Behavioral anomalies
Accounts exhibiting sudden changes in behavior, such as an uptick in transaction volume or new connections to flagged geographies, should be evaluated. Financial institutions should leverage behavioral analytics to detect anomalies in teen accounts or parent-sponsored accounts.
What financial institutions can do
As TCOs become increasingly sophisticated in targeting teens for financially motivated sextortion, community banks and credit unions are uniquely positioned to serve as first-line defenders. Detecting and reporting this activity does not heighten the risk of a perpetrator releasing the explicit content; doing so would eliminate their leverage and attract greater law enforcement attention. For offenders, especially those engaged in crimes involving minors, the added exposure to child sexual abuse material charges significantly raises the stakes, making discretion far more beneficial than retaliation.
Here's financial institutions can make a difference:
- Incorporate typology training
Financially motivated sextortion should be included as a specific typology in anti-money laundering/countering the financing of terrorism (AML/CFT) training programs. Front-line staff and compliance teams should understand how this scheme differs from traditional fraud.
- Enhance transaction monitoring
Update rulesets in your fraud detection and AML software to flag:
- Memo lines with high-risk keywords
- Gift card purchase patterns by underage users
- Repeated small-value transactions from teen-linked accounts
- Transactions to or from known high-risk geographies
Advanced tools like Abrigo Fraud Detection can help automate these detections using pattern recognition and behavioral analytics.
- Implement better parental controls
For institutions offering teen-linked accounts, ensure customers understand the controls available to limit P2P transfers or set spending thresholds. Partner with payment app providers to provide education on managing sponsored accounts and monitoring activity.
- File timely SARs
When indicators of sextortion are identified, file suspicious activity reports (SARs) promptly with FinCEN, including specific payment memos, recipient information, and behavioral details. Highlight the potential involvement of a minor to prioritize law enforcement response.
- Educate customers and communities
Banks and credit unions are trusted voices in their communities. Use that influence to educate parents and youth on digital safety, safe payment practices, and how to report suspicious activity. Include tips on verifying social media connections and keeping accounts private.
The NCMEC's "Take It Down" initiative and other programs offer resources to support victimized families and can be promoted through your institution's website, social channels, and newsletters.
Protecting the vulnerable, preventing tragedy
Financially motivated sextortion is more than a financial crime; it's a devastating form of child exploitation that often ends in emotional trauma or worse. The payment systems that power these crimes are the same systems financial institutions touch daily.
When banks and credit unions take proactive steps to detect and report red flags, they do more than stop fraud. They prevent abuse, disrupt transnational criminal networks, and they protect children in their communities from irreversible harm. Financial institutions can help stop this exploitation at its source by investing in education, transaction monitoring, and community outreach. It’s the right thing to do.

Support accurate and defensible allowance estimates
Backtesting the estimate for credit losses can build confidence in the CECL model and ensure it reflects an institution's credit risk. However, be careful to avoid common backtesting mistakes.
Key topics covered in this post:
What is CECL backtesting?
The current expected credit loss (CECL) model fundamentally changed how financial institutions forecast expected credit losses, so accurate and defensible allowance estimates are critical. Backtesting the CECL model is one of the most practical tools community financial institutions can use to make sure their allowance models are holding up.
CECL backtesting, part of any CECL model validation process, examines what the institution projected for credit losses and shows how that estimate compares to losses actually incurred. By comparing “expected” credit losses from a past reporting period to the charge-offs and recoveries that ultimately occurred, financial institutions can learn exactly where a methodology might have over- or under-estimated risk.
You might also like this resource: “A banker’s guide for CECL compliance and backtesting.”
downloadAuditors and examiners care deeply about this feedback loop, because it ties your lifetime-loss estimates directly to what actually occurred. In addition, the reality check provided by backtesting gives financial institutions the ability to refine CECL methodology and bolster risk management to reduce volatility in reserves.
The process of backtesting CECL: Common steps
To monitor model accuracy and performance trends, some typical steps in CECL backtesting include:
- Selecting a defined period for comparing outcomes with model forecasts. The period should not be one used to develop the methodology.
- Comparing the actual to predicted losses to assess variances.
- Analyzing variances to determine how much of the difference was due to a change in the historical loss rate rather than other factors, such as changes in loan volume, changes to policies, or changes in the value of underlying collateral.
- Identifying any other factors that could have affected the allowance.
Remember, backtesting is aimed at ensuring the CECL model is still performing as expected and reflects your risk profile. It’s a good idea to periodically review the methodology, assumptions, and inputs, including forecast inputs and sources. Have you added new lines of business, or is a particular segment evolving or growing? Those are among the reasons an institution may need a change in methodology or the addition of a new one.
The allowance is especially material to your balance sheet, so you need to document your controls, monitoring, and testing to ensure confidence in the process and program in place for developing this estimate.
What areas should be backtested?
If backtesting the bank or credit union’s CECL calculation is on your radar, consider prioritizing these areas for comparisons:
- Historical loss projections vs. actual outcomes: Determine the model’s predictive accuracy by regularly comparing past predictions to actual charge-offs and recoveries
- Loan segments and risk profiles: Drill into the portfolio to look for trouble spots. Examine performance across diverse loan categories, borrower profiles, and risk ratings to make sure the model is capturing differences in loss behavior.
- Macroeconomic assumptions: Assess the impact of factors such as unemployment rates, interest-rate fluctuations, and GDP trends on the CECL model’s performance. Were the assumptions accurate and were that gaps?
- Model sensitivity: Test how the model adapts to economic changes and stress scenarios (such as accelerated prepayment speeds) to ensure it remains robust under varying conditions.
Short- vs. long-term backtesting:
- Short-term backtesting typically spans one year. It can quickly identify discrepancies between forecasts and actual losses. It can also allow timely adjustments to model inputs and assumptions based on recent economic conditions and credit trends.
- Long-term backtesting covers multiple years to evaluate model performance over extended periods. This view validates the accuracy of long-term macroeconomic and life-of-loan assumptions, uncovers undue reliance on historical data, and ensures the model is consistent across both growth and downturn cycles
On the surface, backtesting seems simple. But in practice, Abrigo CECL advisors see that comparing historical allowance forecasts against actual losses incurred often trips up institutions. Indeed, more than 1 in 5 attendees of a recent Abrigo webinar named model validation and backtesting as their biggest challenge related to managing the allowance.
CECL backtesting mistakes & how to avoid them
Not backtesting frequently enough
Many institutions treat backtesting as a once-a-year compliance checkbox. But CECL models don’t operate in a vacuum. They’re impacted by changing portfolios, shifting economic conditions, and internal decision-making. Waiting too long between backtests increases the risk of undetected issues, including model drift and outdated assumptions.
TIP: Build a regular backtesting cadence. Quarterly is a great goal. Frequent reviews help spot early warning signs and ensure that assumptions stay aligned with actual performance.
Using inconsistent data sets
This one comes up often. A backtest might look off, but when you dig in, the issue is simply that the model and the actual loss comparison used different data sources or definitions. Inconsistencies in timeframes, segmentation, or inputs can make results unreliable or—even worse—misleading. CECL backtesting provides the ongoing monitoring to catch those issues.
Tip: Align data definitions, timeframes, and segmentation across modeling and backtesting. Small inconsistencies can skew results, so consistency provides a clearer picture.
Ignoring loan segmentation differences
At the portfolio level, backtesting results might look fine until they’re broken down into individual loan segments. That’s where trouble spots tend to appear. It might be commercial real estate, indirect auto, or another niche that behaves differently than expected.
Tip: Always review model output against actual loss rates by loan segment. Even without the resources to dig into more granular breakdowns like geography or risk grade, segment-level analysis often reveals areas where model assumptions need attention.
Overlooking the impact of macroeconomic assumptions
When models include economic forecasts or qualitative overlays, those assumptions should be part of the backtesting analysis. Skipping a review of macroeconomic assumptions in your model is a missed opportunity to understand what’s really driving results.
Tip: During backtesting, step back and look at how macro assumptions held up. If the model expected unemployment to rise and it didn’t, or vice versa, what was the impact? These insights often lead to meaningful refinements.
Failing to document and act on findings
One of the biggest gaps isn’t in the analysis, it’s in what happens after. Some institutions run the numbers, find discrepancies, and then...do nothing. Either the findings aren’t documented properly, or the follow-up just doesn’t happen. Failing to act on insights can undermine a model’s credibility and regulatory standing.
Tip: Create a process for documenting everything, including what was tested, what was found, and any model changes made (or why no changes were made). As CECL governance matures, setting clear thresholds for when a model change is required or when holding steady is reasonable is becoming more important. Examiners want to see thoughtful, consistent decision-making in model documentation.
Relying on small sample sizes
Many community financial institutions Abrigo’s Advisory team works with have portfolios with very few charge-offs. That’s great from a credit standpoint, but it makes backtesting more difficult. Drawing conclusions from limited data can lead to misleading results.
Tip: When CECL data is sparse, try expanding the historical window or using peer data for additional context. If qualitative factors (qualitative adjustments to the CECL calculation) are needed, make sure the rationale is well-documented and tied to what the data is showing.
Improve CECL model accuracy
Backtesting isn’t about achieving perfection. Results often don’t match forecasts exactly, and that’s perfectly fine. In many cases, institutions land on the conservative side, with allowances exceeding actual losses. That can be entirely appropriate when supported by good documentation and sound reasoning, such as economic uncertainty or limited data.
Ultimately, the value of backtesting lies in the insights it provides for your CECL allowance. It reveals how the model is performing, supports stronger governance, and improves conversations with both internal stakeholders and regulators. Done thoughtfully, it becomes more than just a compliance step. It becomes a tool for building confidence in the CECL model and ensuring the model reflects the true nature of a financial institution’s credit risk.
This blog was written with the assistance of ChatGPT, an AI large language model. It was reviewed and revised by Abrigo's subject-matter expert for accuracy and additional insight.