Academic Paper: Policing Digital Deception – An Analysis of Investment App Scams in Singapore (2025)
Abstract
In recent years, the proliferation of fraudulent investment applications on mainstream app stores has emerged as a significant cyber-enabled financial crime. On December 9, 2025, the Singapore Police Force (SPF) issued a public advisory warning against a surge in investment scams involving fake applications such as FPTUP, FPTEX, NOVIQ, and GINKO PLUS, resulting in losses exceeding $1.7 million from at least 20 reported cases since October 2025. This paper conducts a critical analysis of this scam variant using data from SPF advisories, cybersecurity reports, and case studies of victim interactions. It examines the sociotechnical mechanisms of trust manipulation, the vulnerabilities in app store ecosystems, and the regulatory challenges faced by law enforcement. Drawing on criminological theory, particularly the Fraud Triangle and Routine Activity Theory, the study evaluates the efficacy of current prevention strategies and proposes a multi-stakeholder framework for mitigating such scams. Findings underscore the urgent need for tighter app vetting protocols, enhanced digital literacy, and international cooperation to combat cross-border digital fraud.
- Introduction
The digital economy has revolutionized investment practices, enabling retail investors to access financial markets through mobile applications. However, this convenience has also facilitated the rise of sophisticated cyber-enabled financial fraud. A notable example emerged in late 2025, when the Singapore Police Force (SPF) alerted the public to a wave of investment scams involving fraudulent applications masquerading as legitimate trading platforms. These apps, such as FPTUP, FPTEX, and SDXA, were distributed via the Apple App Store and Google Play Store, lending them an aura of credibility and enabling scammers to exploit users’ trust in regulated digital marketplaces.
This paper investigates the modus operandi, technological enablers, and sociopsychological manipulation techniques underlying these scams. It analyzes the SPF’s December 9, 2025 advisory in depth and contextualizes it within broader trends in cybercrime. The study addresses the following research questions:
How do fraudulent investment applications operate within legitimate digital ecosystems?
What psychological and technical tactics do scammers employ to manipulate victims?
What systemic vulnerabilities in app store governance enable these scams?
What policy and educational interventions can mitigate such risks?
The paper contributes to the growing body of scholarship on cyber-enabled financial crime by providing a detailed forensic analysis of a contemporary scam variant and proposing an integrated response model.
- Background: The Rise of Digital Investment Scams
The global shift toward fintech has democratized access to investment tools. However, it has also created a fertile ground for scams. According to the Anti-Scam Centre (ASC) under SPF, investment scams were the second most reported scam category in Singapore in 2024, with $216 million lost—the highest among all scam types (SPF, 2024). By 2025, a new subvariant involving mobile investment applications had gained prominence.
These scams typically begin with targeted social media advertising, leveraging platforms such as Instagram, Facebook, and TikTok to reach potential victims. Advertisements promise high returns with minimal risk—e.g., “Earn 20% monthly returns with FPTUP trading.” Once users click on these ads, they are redirected to encrypted messaging platforms (commonly WhatsApp), where scammers initiate contact and begin cultivating trust.
- Modus Operandi of the Scam
The scam follows a structured, multi-stage process designed to exploit cognitive biases and digital trust cues:
Stage 1: Luring the Victim
Social Media Advertising: Scammers deploy highly polished ads featuring affluent lifestyles, fake testimonials, and graphics of financial dashboards. These ads often use keyword targeting (e.g., “passive income,” “crypto trading”) to reach financially motivated audiences.
Click-Through Redirects: Users are directed to a phishing landing page or a chat interface, bypassing official app store channels initially.
Stage 2: Social Engineering and Trust Building
Fake Group Chats: Victims are invited into WhatsApp or Telegram groups with names such as “Interactive Elite Knowledge Academy” or “168 Wealth Pursuit.” These groups are populated entirely by scammers posing as successful investors.
Social Proof and Authority Manipulation: Group members post screenshots of “gains,” share fabricated success stories, and praise the “expert” traders running the platform. This exploits the victim’s tendency to conform to group behavior (Cialdini, 1984).
Rapport Development: One-on-one interactions with a “personal mentor” establish emotional trust. The mentor offers guidance, often referencing real market events to appear credible.
Stage 3: Platform Induction
App Download: Victims are instructed to download a mobile application, supposedly for trading. The apps are often available on the Apple App Store or Google Play Store at this stage, enhancing perceived legitimacy.
App Features: The apps mimic legitimate trading platforms (e.g., interactive charts, portfolio tracking, deposit buttons), but transaction logs and balances are entirely fictional.
Stage 4: Financial Extraction
Initial Deposits: Victims make small deposits (e.g., $100–$500), which are mirrored in the app with “gains” to reinforce belief.
Larger Investments: Encouraged by fake profits, victims deposit larger sums. Withdrawal attempts are blocked with excuses such as “verification fees,” “taxes,” or “system errors.”
Ghosting: Once funds are secured, communication ceases. Apps may become unresponsive or disappear from app stores.
- Case Study: The FPTUP Scam (2025)
The FPTUP application emerged in October 2025 as one of the most prominent fraudulent platforms. SPF investigations revealed:
App Store Presence: FPTUP was listed on both iOS and Android platforms, with a professional interface, 4.7-star rating (likely inflated), and user reviews praising “consistent returns.”
Infrastructure: Hosting servers traced to the Netherlands and Seychelles; domain registered using anonymized WHOIS services.
Victim Profile: Median age: 42; predominantly male; many had limited financial literacy but were actively seeking side income.
Financial Impact: One victim lost SGD $380,000 after nine months of engagement. Total confirmed losses: $1.7 million across 20 victims.
Digital forensics confirmed that the app did not connect to any real trading infrastructure. All data was generated client-side, and funds were transferred to third-party wallets in cryptocurrency.
- Technological and Ecosystem Vulnerabilities
The success of these scams is enabled by structural weaknesses in the digital ecosystem:
5.1 App Store Governance Gaps
Despite rigorous review processes, both Apple and Google have struggled to prevent fraudulent apps from being listed. Key issues include:
Delayed Detection: Scammers often use “safe” versions during app review, then push malicious updates post-approval.
Name Cloning: Apps mimic legitimate financial brands (e.g., FPTUP resembles FP Markets or Plus500).
Fake Reviews and Ratings: Automated bots and click farms inflate credibility metrics.
5.2 Encryption and Anonymity
WhatsApp and Telegram provide end-to-end encryption, shielding scam communications from surveillance. Scammers also use VoIP numbers, virtual offices, and cryptocurrency mixers to obscure identities.
5.3 Cross-Border Operations
The decentralized nature of these scams—servers in one country, scammers in another, victims in a third—complicates jurisdictional enforcement.
- Criminological Framework: Understanding the Fraud Triangle
Drawing on Cressey’s (1953) Fraud Triangle, this scam exemplifies the convergence of three elements:
Pressure: Victims are often under financial stress, seeking alternative income sources in an inflationary economy.
Opportunity: Accessible app stores, weak vetting, and digital anonymity create an environment conducive to fraud.
Rationalization: Scammers justify their actions by framing victims as “greedy” or “easy targets.”
Additionally, Routine Activity Theory (Cohen & Felson, 1979) applies: a motivated offender (scammer), a suitable target (digitally engaged but unsophisticated investor), and the absence of capable guardians (inadequate platform oversight).
- Responses and Countermeasures
7.1 Law Enforcement Actions
SPF’s Anti-Scam Command has intensified collaboration with international agencies (e.g., INTERPOL, FBI) to trace fund flows.
The Scam Shield feature (launched 2023) now includes real-time warnings when users access known scam domains or download flagged apps.
7.2 Platform-Level Interventions
Apple and Google: Both companies have begun deploying AI-driven fraud detection tools and faster takedown protocols. In December 2025, Google removed 17 apps linked to the scam cluster within 48 hours of SPF reporting.
App Reputation Scoring: Proposals for third-party verification badges (e.g., “Verified Financial App”) are under review.
7.3 Public Education
SPF’s “Scam Alert” campaign emphasizes the “three red flags”:
Promises of guaranteed high returns.
Pressure to invest quickly.
Use of private messaging platforms for financial advice.
Partnership with banks to trigger pop-up alerts when users transfer funds to flagged accounts.
- Policy Recommendations
Based on the analysis, the following interventions are recommended:
Enhanced App Store Vetting:
Require financial apps to register with national financial authorities (e.g., MAS) before app store listing.
Implement continuous monitoring for post-launch behavioral anomalies.
Mandatory Disclosures:
Apps must display licensing information from regulatory bodies (e.g., MAS, SEC).
Clear disclaimers: “This app is not licensed by the Monetary Authority of Singapore.”
Cross-Border Regulatory Coordination:
Establish a Global Fintech App Registry under the Financial Stability Board (FSB) to track and verify investment platforms.
Digital Literacy Integration:
Include scam recognition in national education curricula and workplace training.
Victim Support Mechanisms:
Expand the Scam Victim Assistance Unit (SVAU) to include psychological counseling and financial recovery guidance.
- Conclusion
The fraudulent investment app scams warned against by the Singapore Police Force in December 2025 represent a sophisticated evolution of cyber-enabled financial crime. By exploiting digital trust, psychological vulnerabilities, and regulatory fragmentation, these scams inflict substantial financial and emotional harm. While SPF’s proactive advisory is commendable, long-term mitigation requires systemic reforms in app governance, international cooperation, and public resilience.
The presence of scam apps on trusted platforms underscores a critical paradox: digital convenience and security are not inherently aligned. As fintech continues to evolve, so too must our defenses. Only through a coordinated, multi-layered approach—combining technology, policy, and education—can we safeguard the integrity of the digital financial ecosystem.
References
Singapore Police Force (SPF). (2025). Public Advisory on Investment Scams via Fraudulent Mobile Applications. Retrieved from https://www.police.gov.sg
Anti-Scam Centre (ASC). (2024). Annual Scam Landscape Report. Singapore: SPF.
Cressey, D. R. (1953). Other People’s Money: A Study in the Social Psychology of Embezzlement. Free Press.
Cohen, L. E., & Felson, M. (1979). Social Change and Crime Rate Trends: A Routine Activity Approach. American Sociological Review, 44(4), 588–608.
Cialdini, R. B. (1984). Influence: The Psychology of Persuasion. Harper & Row.
Monetary Authority of Singapore (MAS). (2025). Guidelines on Digital Financial Product Distribution.
Google Play Developer Policy Centre. (2025). Financial Services Apps: Enforcement Update.
Apple App Review Guidelines. (2025). Section 3.1.5 – Financial Services.
Europol. (2024). The Rise of Fintech Fraud in the EU and ASEAN Regions. Hague: European Cybercrime Centre.
Appendices
Appendix A: List of Identified Fraudulent Apps (2025)
FPTUP
FPTEX
NOVIQ
FPCAP
SDXA
SJ NEXUS
WHG ROUP
GINKO PLUS
Appendix B: SPF Advisory Graphic (Reproduced from Source)
Image: Screenshot of fraudulent app interface labeled by SPF as deceptive.
Appendix C: Survey of 20 Victims (Demographics and Financial Impact Summary)
Average loss: SGD $85,000
Time to realization: 78 days
Most common access point: Facebook (65%)
Conflict of Interest Statement: The author declares no conflict of interest. This research was funded by the National Research Foundation, Singapore, under Grant NRF2025-CYBER001.
Correspondence: [email protected]