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February 14, 2022

Preventing Fraud in Your Pension Administration System

Introduction

It’s hard to believe that the baby boomers, up until recently the largest generation in U.S. history, will be eligible for retirement in less than 10 years. This means that by 2030, one out of every five citizens will potentially leave America’s workforce. To support the impending wave of public servant retirees, pension systems have been replacing their legacy platforms with modern pension administration systems (PAS) to support robust member self-service, advanced CRM, and campaign management for responsive member care as well as retirement process instruction. Many of today’s modern PAS also incorporate Know Your Customer (KYC) guidelines to provide enhanced identification and verification protocols to minimize the risk of fraud and other cybercrimes.

Our recent Insight, Building Digital Security for Public Pension Systems, addressed Account Takeover (ATO) and identity fraud, two of the most frequent cybercrimes that plague today’s pension systems. Let’s review two other fraud situations that are prevalent today, insider and elder fraud.

Insider Fraud Basics

In most instances, insider fraud results from the combination of three factors: an individual or group motivated to commit fraud, a target that can be exploited, and the absence of competent oversight.

Examples of pension-related frauds committed by an employer include:

  • Providing false information about the assignment or allocation of a member’s pension rights or benefits.
  • Supplying false information about member contributions to their retirement fund.
  • Tax or insurance fraud, associated with the pension plan.
  • Misrepresenting a member’s monthly benefits.

Rogue individuals often commit fraud through:

  • Mortgage or loan fraud schemes that involve taking funds out of a member’s pension.
  • Digital or online fund theft from a member’s account(s).
  • Power of attorney holders abusing their privilege.

Effective Insider Fraud Prevention

The biggest challenge in identifying fraud is the sheer number of transactions that need to be monitored and reconciled. This is where the advanced technology of modern PAS, specifically Artificial Intelligence (AI), can evaluate processes, detect anomalies using statistical models or rules to compare transactions, and perform audits at scale with the required accuracy.

AI’s pattern recognition capabilities detect suspicious activity by analyzing all transaction-related information and the supporting data to determine validity. Moreover, AI can also verify the names of members against those of payment recipients, so that proxy accounts cannot be used for embezzlement. In addition to using AI to detect misappropriation, misreporting, and other kinds of accounting fraud, pension systems can also use AI to make their processes inherently fraud-proof. AI can also force dual control measures that require more than one employee to perform a task to ensure that proper protocols are followed.

Elder Fraud Basics

The internet has become a convenient avenue for bad actors to target the elderly. The reticence of seniors to report cases out of embarrassment is also why elder fraud is so widespread. Because of underreporting, no one really knows the full scale of the problem. Estimates in the U.S range from $3 billion to $36 billion per year.

Common elder fraud schemes include:

  • Fake tech support: Criminals pose as technology support representatives and offer to fix nonexistent computer issues. They gain remote access to victims’ devices and sensitive information to access their pension accounts.
  • Government impersonation: Criminals pose as government employees and threaten to arrest or prosecute victims unless they agree to provide funds.
  • Romance scams: Criminals pose as interested romantic partners on social media or dating websites to capitalize on elderly victims’ loneliness and desire for companionship.

Effective Elder Fraud Prevention

Modern PAS platforms with built-in CRM modules may be used to educate retirees about recognizing potential scams, ending all communication with the perpetrator (s), and resisting the pressure to act quickly as scammers often create a sense of urgency to encourage an immediate response.

Fund administrators can also provide guidance on reporting cases to the police, FBI, and to pension fund administrators.

Know Your Customer (KYC) Guidelines

To help guard against insider, elder, and other types of cyber fraud, KYC guidelines have become instrumental in modern PAS for customer verification and validation. Originally used for financial institutions’ anti-money-laundering processes, KYC policies incorporate identification procedures, transaction monitoring, and overall risk management to identify suspicious elements early in in the member-pension system relationship.

Final Thoughts

Modern PAS continue to evolve and building effective fraud detection and prevention protocols are significant advances to protect all constituents. Behavioral analytics with AI provide context for all irregular activity, which can determine suspicious behavior and enable swift remedial measures. Integrating PAS with KYC platforms will go a long way in building robust cybersecurity, providing pension administrators with strong protection, and retirees with well-deserved peace of mind in their golden years.

PREETAM SIRUR

Preetam Sirur, Vitech’s Chief Information Security Officer, leads all aspects of information security and privacy at Vitech. He has over 30 years of security experience in various industries. At S&P Global, he led and implemented global cybersecurity programs, including cloud transformation and data loss-prevention efforts. Before S&P Global, Preetam worked at Securities Industry Automation Corporation (a division of NYSE Euronext), where he was responsible for implementing the first wireless LAN for brokers on the trading floor. He also managed the NYSE trading floor infrastructure engineering team, executing major projects to upgrade trading floor capabilities, and led the post-9/11 trading floor recovery effort.

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