Combatting post-disaster housing recovery grant fraud

Fraud is a growing business

The Department of Housing and Urban Development's Community Development Block Grant Disaster Recovery (CDBG-DR) program allocates billions of dollars to rebuild disaster-impacted areas and support long-term recovery. Unfortunately, fraud and misconduct can undermine such efforts, diverting funding away from those who need it most, delaying or preventing recovery efforts, and eroding public trust. Government Accountability Office (GAO) report suggests the $39.5 billion in CDBG-DR funds Congress appropriated for 2017-2019 may be at risk of fraud from contractors, applicants, and grantees, and their subrecipients.

Internal fraud is also a risk when agencies receive large amounts of funding quickly, overwhelming outdated systems and manual processes. Employees with access and knowledge of weak controls can exploit these vulnerabilities. Synthetic identity theft is a major risk, where fraudsters combine real and fake information to create new identities and apply for grants or collaborate with external parties to commit fraud.

AI can make a difference

Artificial intelligence (AI) can be used to add controls that monitor internal and external fraud risks in CDBG-DR programs, including predictive analytics, risk assessment, fraud detection, compliance monitoring, and real-time monitoring.

• Predictive analytics: AI can proactively help prevent fraud by analyzing historical data to identify potential fraudulent activities.
• Risk assessment: AI can identify high-risk grant applications that require additional scrutiny by analyzing factors such as financial history and relationships with involved parties.
• Fraud detection: AI algorithms can help detect fraudulent activities by analyzing grant management data, flagging suspicious cases, and helping authorities prioritize their investigations.
• Compliance monitoring: AI can monitor compliance with regulations and policies by analyzing data and documentation, flagging inconsistencies, and identifying non-compliance issues such as duplicate claims or misallocated funds.
• Real-time monitoring: AI can continuously monitor transactions and grant management activities for suspicious or abnormal behavior, including financial transactions, vendor relationships, and changes in project plans or timelines.

AI can help mitigate CDBG-DR program fraud by quickly processing and analyzing large amounts of data and identifying anomalies. It can extract and integrate data from various documents, recognize patterns and discrepancies, use natural language processing to understand text, and automate anomaly detection for efficiency.

Helping you mitigate fraud

Fraudsters will continue to find new and innovative ways to introduce fraud into CDBG-DR grant programs. KPMG applies leading-edge analytical techniques, AI, emerging technologies, and a mature framework to help state and local governments with identifying, mitigating, and protecting against fraud. Our teams have implemented anti-fraud models in state environments in two-to-three weeks. In addition, our KPMG Smart Grants Platform employs automated data validation tests that are designed to detect instances of fraud and duplication of benefits, helping ensure accurate, efficient, and compliant CDBG-DR grant review processes in accordance with funding agency regulations.