Transaction Search Form: please type in any of the fields below.
Date: April 29, 2024 Mon
Time: 9:13 pm
Time: 9:13 pm
Results for consumer fraud and scams
1 results foundAuthor: Weber, Paull Title: Small Business Scams: National Survey 2012/13 Summary: This survey is the first national attempt at specifying the small business scam as a distinct category of scam worthy of focussed research endeavour. It is the first phase of a longer term proposal to understand how small business owners behave when scam risks are presented to them; it also attempts to identify which types of scams represent the most common and most serious risks of loss. The assumption implicit in this study is that there are differences in the type of scam that small businesses are exposed to and in their various responses to scam attempts, when compared to consumers. The study enlisted the assistance of many small business associations, and was conducted Australia-wide over the period May-December 2012. A total of 291 businesses responded to the survey, and the sample of small businesses surveyed represented every ANZSIC class of business. It encompassed businesses with annual turnovers that ranged from $10,000 to $20,000,000 per annum. Approximately 2/3 of respondents were male and 1/3 female, which is broadly representative of the small business population in Australia. 192 respondents provided sufficient detail for the purpose of the full analysis intended. Several predictors of scam propensity were included in the study. These potential risk factors included turnover, experience of prior loss, routine activity theory, industry type, self control, select personality traits, generalised business risk and some demographic markers. Owners reported the most prevalent scam attempts as lotteries and sweepstakes, advance fee frauds and free ‘spam’ type offers. There was evidence that social media is gaining ground as a communication medium to deliver the scam messages but email is still the dominant medium of delivery, apart from false billing and fax-back scams. Beyond the 15 common categories, another 17 types of scam were described by respondents. In response to this barrage of scam attempts business owners are developing their own rules to manage this risk. We summarize these into a list of 32 strategies being deployed by small businesses to foil the scammers. The financial loss through scams in our sample ranged from $100 to $10,000 per annum and the time spent dealing with the consequences was estimated as high as 100 hours. The dollar value of losses is somewhat lower than the norms reported by the ACCC’s Scam Watch but that is to be expected, given our data collection method we were unlikley to have self reports of major fraud communicated via an online survey. There appears to be some link between financial risk taking and increased scam propensity. General business risk taking does not seem to be related to the level of scam loss, but there is a somewhat greater quantum of loss exhibited by respondents who take higher financial risks. Respondents who took lower financial risks also demonstrated higher confidence levels in identifying a scam before a loss is incurred. A major finding of this research is that Routine Activity Theory is a useful predictor of scam propensity (scam amount lost). There was a significant relationship between the amount of money lost and the degree of online activity that the business was involved in. It seems that having a heightened online presence leads to greater risk of loss and/or more money lost. This is perhaps not a surprising finding, but none the less important to provide evidence of another hotspot. That is, businesses that transact online and indeed have a significant online presence can expect to attract the attention of scammers who will want to ‘fish where the fish are’! In addition to this, remote purchasing behaviours which had an ‘unguarded’ aspect to them (such as shopping online, speaking with an unknown telemarketer or responding to an infomercial) were shown to have a relationship with the quantum of loss. We also developed an innovative test of gullibility via a heat map based question which identified 19 respondents who selected an option that was by all measures too good to be true. These respondents would be candidates for further in-depth analysis of the thought processes that led to this choice. The 19 respondents also self-assessed as being somewhat less confident of identifying a scam, confirming that self assessment of capability may be appropriate in this case. The growing problem of scams committed against small business is shown in this report to be at such epidemic levels that the current lack of specific research attention cannot be allowed to continue. For such an entrenched problem we may not be able to find a cure, but we must begin to diagnose the ‘symptoms’ and develop effective ‘vaccines’ to take a more proactive stance. At present, the vast majority (84%) of the variance on scam prevention expenditure can be explained by the amount of prior losses incurred. Loss prevention, it seems, is far less common than dealing with the fallout after the loss has been incurred. In laymans terms - yes the horse may have already bolted, but there’s still more left to protect in the stable. Details: Bentley, AUS: Curtin University, School of Management, 2013. 46p. Source: Internet Resource: Accessed July 9, 2013 at: http://business.curtin.edu.au/local/docs/Small_Business_Scam_Survey_2012.pdf Year: 2013 Country: Australia URL: http://business.curtin.edu.au/local/docs/Small_Business_Scam_Survey_2012.pdf Shelf Number: 129281 Keywords: Consumer Fraud and ScamsCrimes Against Businesses (Australia) |