Providence, RI · Independent public-finance research & analytics

Research & Insights

Twenty-five publications on financial oversight in the public sector — method, practice and the places where both go wrong. Open to everyone, without registration, permanently.

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AI in Government Finance

Where AI Actually Helps in a Municipal Finance Office

Most of the value from machine learning in local government finance is not in prediction. It is in triage — deciding which of ten thousand transactions a human should look at first.

Fraud Prevention & Detection

Anomaly Detection in Purchase Card Programmes

Purchase cards concentrate a disproportionate share of detected public-sector fraud in a small share of spending. The controls that work are unglamorous.

AI in Government Finance

Model Risk Management for Public Finance Analytics

Banking supervisors have spent fifteen years formalising model risk management. Most of it transfers to public finance at a fraction of the cost, if you drop the parts built for capital adequacy.

Fraud Prevention & Detection

Segregation of Duties in Small Finance Departments

In a department of three, ideal segregation is arithmetically impossible. Compensating controls are not a lesser substitute — but they only work if they are specified precisely.

Fraud Prevention & Detection

Vendor Master File Hygiene: The Quiet Fraud Control

Most disbursement fraud starts with a record, not a payment. The vendor master file is where the control is cheapest and least often applied.

ESG & Sustainable Finance

Climate Risk Disclosure for Local Government Issuers

Investors and rating agencies are asking. The difficulty is that the honest answer for most issuers is a range, and disclosure practice is built for point estimates.

Public-Private Partnerships

Monitoring P3 Contracts After Financial Close

The transaction team disperses, the contract runs for thirty years, and institutional memory has a half-life of about four.

ESG & Sustainable Finance

Measuring Social Outcomes in Public Investment

Outputs are cheap to count and easy to defend. Outcomes require attribution, and attribution is where most public measurement quietly gives up.

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