Last August, U.S. Congressman Duncan Hunter was indicted for misuse of campaign funds for personal benefit. The Justice Department alleges that Hunter conspired with his wife, whom he appointed campaign manager, to steal from his campaign to support their lavish lifestyle: the campaign spent $15,000 on airline tickets and hotel rooms for Hunter’s children and relatives, a $14,000 Thanksgiving trip to Italy, and for other expenses like $700 for seven adult and five children’s tickets to see “How the Grinch Stole Christmas.”
Though Representative Hunter’s conduct is only now being investigated, the allegations of improper spending go back to 2009, and many of the expenses now under scrutiny were detailed in his campaign’s filings with the Federal Election Commission (FEC). FEC filings are public records, readily available and searchable (via simple keyword searches on the FEC’s webpage) to anyone interested in looking. For example, Representative Hunter is a “vaping” enthusiast (even smoking his e-cigarette in Congress). Using the FEC’s webpage and a simple search for the words “cigar,” “smoke,” and “tobacco,” I found that Representative Hunter’s 2015-16 campaign expenditures include hundreds of dollars of spending at a cigar lounge, smoke shop, and tobacco company in his home district. Similar search results through the FEC website show all sorts of eyebrow-raising transactions.
So why weren’t the problems detected earlier? The problem, in cases like this, is not that the FEC doesn’t have enough information to identify suspicious activity—it’s that it has too much information. The FEC has massive amounts of data, making the detection of fraud a needle-in-the-haystack problem. The FEC relies largely on complaints and referrals to guide its enforcement process, with the result that enforcement remains anemic. In 2017, for example, the FEC levied administrative fines in 215 matters totaling under $2 million, despite having data on 23.4 million line-item disbursements and 34.5 million individual contributions, not even counting electioneering communication transactions and the massive data on political action committees (PACs).
Waiting for referrals, or screening data by hand, is not an effective way for the FEC’s roughly 300 employees to detect corruption or fraud in campaign finance. There are no silver-bullet solutions; fraud detection is a fundamentally difficult, especially when fraudsters take steps to cover their tracks. But there are some steps the FEC can take to better monitor fraudulent expenditures to identify suspicious cases early on:
- Automated flagging of suspicious transactions. The FEC can employ a blacklist or automatic flagging system for certain types of vendors and/or transactions. When a campaign filing reports that a candidate like Representative Hunter is spending up to $1,000 at a time at a cigar lounge, this should trigger an audit. The creation of something as simple as a keyword flag could vastly expedite the narrowing process for which candidates need additional monitoring. However, the FEC should keep its screening algorithms confidential, as the public disclosure of the keywords that trigger additional scrutiny could make it easier to circumvent the system through false reporting.
- Comparison between candidates. Many corrupt or fraudulent transactions can’t be identified simply through the identity of the vendor. For example, candidates regularly spend money on food and drinks for donor events, so the same reported transaction (a large expenditure for catering) might be a legitimate campaign expense, but could also be an illegitimate use of campaign funds for personal benefit. The FEC could, however, use comparisons between candidates to more accurately identify potentially aberrant behavior. By matching on geography, party, incumbency, and amounts of spending, a simple algorithm could pick out circumstances when certain candidates behave very differently from the norm. Unusual spending does not necessarily imply illegal spending, but it does suggest the need for additional scrutiny, so an algorithm that incorporates comparisons among similar candidates could be very effective in targeting audits and maximizing the effectiveness of the FEC’s limited oversight capacity.
- Bounty program. Government agencies are notorious for their limited computational expertise. But as FEC data are already public, the FEC could implement a bounty program, paying individuals or companies for finding fraud among candidates, individual contributors, or PACs, when their information leads to an administrative fine. Bounty programs work well because they only pay out in circumstances where bad behavior is uncovered. This type of data monitoring is already being undertaken for Medicare, where data privacy is a much greater concern. It is unclear what techniques private companies would use on the FEC data, but fraud detection has become a well-developed field in the era of e-commerce, and a paid program would reward those with the best ability to detect fraud. To avoid over-enforcement or random enforcement, private entities participating in the bounty program should be required to provide specific information, for example by identifying specific suspicious transactions or patterns. Furthermore, to avoid either random or politically-targeted reporting, participants would have to prove that they perform sufficiently well (perhaps by debarring reporting entities with too many false positives in their track record). The FEC already has the capacity to levy administrative fines, and a privatized bounty program would vastly expand its capacity for screening, while the administrative process such as fines and appeals can stay firmly within the bureau’s control.
The case of Duncan Hunter is not just a case of brazen corruption by one congressman. Rather, it underlines the failings of the FEC to make use of the data it demands and collects, even when a cursory examination would have raised red flags. By applying simple computational techniques, or outsourcing the problem to those capable of using more complicated ones, the FEC can detect and deter corruption among candidates.