ABSTRACT
The arrival of “FinTech” – non-bank companies offering financial services through new technology – has changed the regulatory landscape of the financial markets. This is especially the case in the funds transfer market. While terrorist finance might have once been more at risk of detection in some jurisdictions than others, FinTech threatens to bring about a levelling of risk across jurisdictions. To what extent, though, do we expect decision-makers engaged in transferring funds for terrorism to switch seamlessly in response to changes in risk? Because terrorist finance requires choice under risk and uncertainty, it may be characterized by systematic patterns of error deriving from human decision-making processes. These errors cause delays, or “stickiness” in adaptation to new conditions and may provide openings for counter-terrorist finance (CTF).
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. This could be an ordinary grass-roots supporter transferring funds to an overseas (or domestic) terrorist organization or it could involve the terrorist organization itself transferring funds to a local (or overseas) operative. Our notion of fund transfers includes but is not limited to remittances knowingly transferred for terrorism purposes (see Mascarenhas & Sandler, Citation2014).
2. Bures (Citation2012, Citation2015) has a somewhat more pessimistic assessment.
3. These are “mechanisms” in the sense that a watch listed individual, although not actually being watched, might trigger law enforcement interventions by taking a particular action (e.g., purchasing an airline ticket or attempting to travel outside of a particular jurisdiction).
4. According to Jeff Kauflin (Citation2019) at Forbes, the 11 biggest FinTech firms in America in 2019 are Stripe, Coinbase, Robinhood, Ripple, Sofi, Credit Karma, Circle, Plaid, Avant, Gusto and Zenefits. Each has billions of dollars of capital. The FinTech firm with the highest market value in the world is Ant Financial, based in China. Ant Financial operates Alipay, a mobile and online payments platform. Its market value is approximately $150 billion (CNBC, Citation2018). Also based in China is the peer-to-peer (P2P) lending platform, Lufax, whose product matches investors with borrowers. The company collects a “finder’s fee” for each completed transaction. To date, the company has arranged P2P loans of almost $3 billion and is currently valued at more than $10 billion (Carew & Demos, Citation2015).
5. Mobile operating systems use “sandboxing architecture” that isolates apps from malicious malware, making mobile phone-based payments through e-wallets potentially more secure than online payments from a computer (Dickler & Epperson, Citation2018).
6. Cryptocurrency is a virtual or digital currency using strong encryption technology such as Blockchain to secure both transactions and the creation of additional units of the cryptocurrency.
7. The formal details are explained by Phillips (Citation2009).
8. It is important to note that the new opportunities do not have to be low risk for this to happen. It is the imperfect correlation of new products with existing products that allows benefits from diversification to be expanded in this direction.
9. Also see Tversky and Kahneman (Citation1992).
10. See Phillips and Pohl (Citation2014, Citation2017) for a more formal discussion of prospect theory, stochastic dominance and terrorist choice.
11. All of these behaviours are systematic patterns of human decision-making and have often been observed in animal decision-making (e.g., MacDonald, Kagel, & Battalio, Citation1985, Citation1991).
12. The indication that he is looking for might include some delay in processing in a manner not dissimilar to the old intelligence tradecraft technique of testing for postal delays as a signal that mail may be being intercepted and read before being forwarded.
13. The symbol “” is the negate symbol.
means not
.
14. An investment with a so-called paper loss isn’t realized (sold), and so the loss hasn’t truly occurred yet.
15. Exploring this line of reasoning, Shefrin and Statman (Citation1985) hypothesized that loss averse investors would sell their winning investments too soon and hold their losing investments too long. When they studied the relevant financial data, they found that about 40% of investments that were sold were “losers”, while 60% of investments that were sold were “winners”, a result supported by Ferris, Haugen, and Makhija (Citation1988) and Odean (Citation1998).
16. The endowment effect is due to loss aversion, resulting in a discrepancy between what a person is willing to pay and what the same person is willing to accept for a good. People to tend to place a higher value on what they have, just because they have it. They will pay, say, $10 for something. But when they are asked to state a selling price it might be, say, $15 (Kahneman, Knetch, & Thaler, Citation1990; Knutson et al., Citation2008).
17. There might be more to be inferred from such fund flows, if they could be detected. That is, they might be weak signals (see Phillips & Pohl, Citation2020) of the scale of future planned terrorist activity.
18. One potential marker is individuals holding multiple FinTech (or traditional) accounts but who have one account that directs payments to a single receiver. There are other “separation” possibilities that could be investigated.
19. For more examples of overconfidence see Daniel, Hirshleifer, & Subrahmanyam (Citation1998).
Additional information
Notes on contributors
Peter J. Phillips
Peter Phillips is an associate professor in finance at the University of Southern Queensland. His work applies orthodox and behavioral economics to decision-making in terrorism, law enforcement and intelligence contexts. He shows how economics can enhance decision-making by providing frameworks within which to ‘think about thinking’.
Benjamin McDermid
Benjamin McDermid is a graduate student in finance and economics at the University of Southern Queensland. He is interested in exploring the ways in which prospect theory can be used to highlight the essential features of decision-making problems as well as its use as an interpretative framework for understanding human behaviour (past and present).