Tax Collections Optimization for New York State

Abstract

The New York State Department of Taxation and Finance (NYS DTF) collects over $1 billion annually in assessed delinquent taxes. The mission of DTF's Collections and Civil Enforcement Division (CCED) is to increase collections, but to do so in a manner that respects the rights of citizens, by taking actions commensurate with each debtor's situation. CCED must accomplish this in an environment with limited resources. In a collaborative work, NYS DTF, IBM Research, and IBM Global Business Services developed a novel tax collection optimization solution to address this challenge. The operations research-based solution combines data analytics and optimization using the unifying framework of constrained Markov decision processes (C-MDP). The system optimizes the collection actions of agents with respect to maximizing long-term returns, while taking into account the complex dependencies among business needs, resources, and legal constraints. It generates a customized collections policy instead of broad-brush rules, thereby improving both the efficiency and adaptiveness of the collections process. It also enhances and improves the tax agency's ability to administer taxes equitably across the broad scope of individual taxpayers' situations. The system became operational in December 2009; from 2009 to 2010, New York State increased its collections from delinquent revenue by $83 million (8 percent) using the same set of resources. Given a typical annual increase of 2 to 4 percent, the system's expected benefit is approximately $120 to $150 million over a period of three years, far exceeding the initial target of $90 million.

Forecasting recoveries in debt collection: Debt collectors and information production

“…Makuch, Dodge, Ecker, Granfors, and Hahn (), Chin & Kotak (), and Miller et al () further document considerable improvements in the profitability of debt collection firms and departments through the introduction of operational innovations. These methods partly rely on debtor and contract characteristics for making optimal workout process decisions.…”

Reward (Mis)design for Autonomous Driving

“…Specifically, a financial utility function might output the change in the expectation of net profit across all stakeholders caused by τ . Utilities expressed in currency units are common in RL when profit or cost reduction are the explicit goals of the task, such as stock trading [28] and tax collection [25], but we are unaware of its usage as an optimization objective for AD.…”

Modeling the Revolving Revolution: Debt Collection Channel

“…Examples include Fannie May and Freddie Mac in 1997 for managing delinquent mortgages (Cordell et al, 1998), and New York State in 2009 for collecting unpaid taxes (Miller, 2012). In particular, New York State increased its collections from delinquent taxpayers by $83 million (an 8 percent increase) using the same amount of collection resources.…”