Scam Detection

Prevent Scams by Understanding Intent, Not Just Identity

Uncover social engineering behaviors, signs of coercion and authorized push payment (APP) fraud, as well as scam reviews and listings on marketplaces.

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Financial Scams

Spot APP fraud tied to investment, romance, or impersonation scams. Detect coercion, payment anomalies, and remote access tools in real time.

Purchase Scams

Expose fake listings through text/image similarity. Identify sellers using proxies or multiple accounts, and flag buyers bypassing platform rules.

Travel Scams

Flag suspicious listings and fake reviews. Detect linked buyer / seller accounts, and booking anomalies that warrant deeper investigation.

Look at the full content of the payer / payee transaction. Harness historical behavioral analytics relating to the senders normal pattern of logins and payments, including transaction velocities and volumes. Are they paying a new beneficiary? Have they made any small test payments?

Disrupting the Payment Journey of Scams with Darwinium

AI is supercharging APP fraud and scams, enabling fraudsters to craft convincing ads, listings, and messages that appear legitimate and trustworthy. Armed with vast data and generative tools, attackers can socially engineer customers into paying for fake goods, services, or travel bookings. Darwinium detects these threats in real time by identifying subtle behavioral anomalies, suspicious listings, and unusual beneficiary patterns, uncovering scam journeys before the payment is made.

Defending Against AI-Driven Scams with Behavioral Intelligence

According to the Global Anti-Scam Alliance, one in four of the global population is affected by scams, and this figure is only set to rise. To defend against this human-to-human fraud, organizations need to understand human behavior across digital journeys, peeling behind who the user is, to understand the context and intent of their interaction.

Understand Behavior Across the Entire Customer Journey

Darwinium provides user behavioral analytics across complete digital journeys, with long look backs to ascertain patterns of trust, and flag anomalies as they happen. Access additional context of what has happened prior to login, and between a login and payment event. Detect behavioral biometrics flags such as page delays or dwell time, and live call detection.

Fine-Grained Behavioral Biometrics to Identify Subtle Changes

Monitor the way a user interacts with their devices across web and mobile to detect unusual behaviors such as hesitations or longer dwell times, and indications of remote access software. Harness mobile sensor data including orientation and accelerometer for indications of live calls and signs of potential social engineering, or coaching through a payment journey.

Integrate Any Third-Party Intelligence to Augment Risk Decisions

Simply ingest any third-party data using the Darwinium API, to add context to what the user is doing now. This could include call centre data, phone intelligence and live remote access session detection. Remove the integration effort of managing multiple solutions, consolidating all data required to make a more informed risk decision.

Dynamic Tailored Interventions

When deployed on the edge, via your CDN, Darwinium can dynamically tailor a customer journey in real time, using warning messaging relating to the transaction or beneficiary. This aims to disrupt warning fatigue and alert blindness, while Introducing appropriate friction for high-risk payments.

When deployed on the edge, via your CDN, Darwinium can dynamically tailor a customer journey in real time, injecting warning messaging relating to the transaction or beneficiary. This aims to disrupt warning fatigue and alert blindness, and break the spell of the scam payment. This capability can also be used to introduce appropriate friction for high-risk payments.

Since implementing Darwinium, we’ve seen a significant improvement in our ability to detect and respond to suspicious activities - particularly around account takeover, mule detection and payment fraud scenarios. The real-time alerts, device intelligence, and behavioral analysis have proven to be extremely effective in helping us safeguard our customer accounts.

D'fiama Pandiyan

Fraud Operations Lead at Boost

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Ready to Outsmart AI-Driven Scams and Social Engineering?

Take control of scam detection, harnessing journey-level visibility of user behavior and intent. See how Darwinium can help you proactively detect scam scenarios in real time.

Frequently Asked Questions (FAQs)

Scams are one of the fastest growing and most pernicious of all fraud typologies, having a profoundly devastating impact on victims, who are often exposed to weeks of social engineering, believing they are in a legitimate relationship or part of a large investment opportunity. Many victims lose their life saving, and some even commit suicide. Given customers often approve payments from their own accounts, it can be extremely hard to recover money, with only some countries offering limited reimbursement criteria. The best defense against large scale investment, romance and purchase scams, is real time identification and remediation, using complete context of user behavior over time, and across every touchpoint in the user journey.

Darwinium looks at the way a user behaves across every point in the customer journey, and over time, to detect subtle signs of coercion, social engineering, or anomalies that might indicate a potential scam scenario. This can include changes to login velocities or payment amounts, changes to the way a user traverses a payment journey, live call detection, presence of remote access software, and unusual beneficiary intelligence.

This all depends on whether you choose to make appropriate friction part of your remediation strategy. For example, in some high-risk scenarios where a scam is suspected, financial institutions could chose to pause a payment after reviewing Darwinium intelligence, and intervene with the customer directly. Likewise they could choose to use Darwinium to inject dynamic, tailored messaging to encourage the user to call the bank or visit a branch. These types of interventions may be appropriate to try and protect a customer from making a scam payment.

Darwinium's approach to scam prevention is based on understanding every piece of context relating to the way a user is interacting online across the entire customer journey and not just at the point of payment. Darwinium focuses on uncovering behavioral patterns and anomalies, comparing these to both trusted behaviors, and confirmed scam events. When deployed at the edge, banks and financial institutions can also benefit from the ability to dynamically tailor a customer's payment journey in real time, potentially helping to break the scam spell and prevent a payment being made to a fraudster or mule account.