If ever there were a business model that needed effective data analytics and risk management, it’s mobile money. With target users located primarily in areas of the world where there are little to no official financial services, limited infrastructure, and often shady governing bodies who offer varying levels of protection to their citizens, and tentative commitment to overseas investors, mobile money operators open themselves up to a multitude of hazard and uncertainty.
Yet despite the potential impact of those obstacles above, one challenge to the progress of mobile money efforts could be largely attributed to the user.
An article by CGAP in 2013 details how some customer behaviour can coerce findings to provide false data. The problem of “direct deposits”; the act of depositing money directly into a recipient’s mobile account as opposed to transferring from another, was well documented as an example of this.
With loss of revenue resulting from direct deposits estimated to be more than 20% of net P2P transfers, the need to address this issue remains paramount to future growth. And yet that’s not all. In addition to this figure, the predicted stunt in registration rates, missed opportunities for promoting new use cases, and take up of an operator’s SIM card in the first instance, should also be factored in to create an even greater deficit.
The case as to whether the problem is more effectively resolved through system or policy changes is an ongoing debate.
The GSMA suggests a three-step system process for effective resolution. It begins with set policies which discourage the client from such behaviour from the outset, adding clauses to contractual agreements for example; with mention of disciplinary procedures should they ever be broken. The next step is to identify transgression of suspected offenders through data analytics, and then finally to action disciplinary procedures having established either repeat or isolated offenders.
However, those in favour of system changes argue that agents should be seen as enablers instead of enforcers. The solution must not risk the reputation of those who represent the mobile money industry. It has been suggested in this instance that by implementing an extra stage at the transaction point it could be possible for direct deposits to be prevented altogether, thus eliminating the need to take action further down the line.
With data analytics that understand real user behaviour at the core of a sustainable mobile money economy, what do you think can be done to improve their accuracy?
To find out more about the solutions currently being discussed to minimise the occurence of direct deposits, please click on the following link.
For further reading sources and useful tools to implement risk management in mobile money, please click on the following links.
Image : Mobile Affair. Photo by Miranda Harple for Yenkassa.com