The panel on "Accessories to Technology: Mobile Financial Services, Risk, and Insurance with discussant Ananya Roy of UCLA addressed how institutions must adjudicate claims and manage liability in volatile environments of new products, precarious populations, and financial experiments. "Assessing the Need and Feasibility for Using Pre-Paid Card Technology in Delivering Added Services to Micro Finance Customers in Selected Regions of Uttar Pradesh: (India) by Debashis Acharya of the University of Hyderabad and Tapas Kumar Parida of the State Bank of India led off the session with a focus on the third largest state in India, where about 22 MFIs (microfinance institutions) operate.
New 2014 regulations have been reshaping the role of IRDA, the statutory body that regulates the insurance sector in India, which is tasked with both protecting the interests of policyholders while also ensuring the growth of the insurance industry. Knowledge partners in the study included Bajaj Allianz Insurance, M2P Solutions (a prepaid card provider), and Utkarsh Micro finance, which is one of the leading 25 MFIs in India, according to a CRISIL 2014 report. They traced how a claim settlement process might evolve along three trajectories: 1) the Traditional/Conventional Model in which the MFI collects documents from clients after the death of the insured and submits materials to the insurance company, 2) the model of Electronic Transfer (NEFT) to the bank, which opens up possibilities for alternative payment mechanisms and split payment paradigms, and 3) the Open Loop Pre-Paid Card model in which the nominee gets directly benefitted by this process and in which unsettled claims can be reissued and fresh claims can processed by pre-paid card. Acharya described the costs and benefits of pre-paid cards from the perspective of users who think about mobile phones primarily as devices for communications.
"The Curious Case of Mobile Micro-insurance in South Africa: A View from Above and Below" (South Africa) by Christopher Paek of London School of Economics focused on Xhosa funerals and financial risk mitigation through insurance. To demonstrate the importance of the issue of funeral insurance, he began with the case of Godfrey, who maintains a household composed of a wife, three children and a mother in a township outside Cape Town. With a monthly income of R2000 (about $130) it would be difficult to manage costs generated by the death of his father-in-law, which would include multiple undertakers, transportation to ancestral homeland, ceremonial slaughter of one cow (and a second cow for a male head-of-household), food for guests, and the slaughter of a sheep for the funeral banquet. All tallied, such costs would be R41,780 or about 21 months of Godfrey's salary. Rather than turn to the formal sector of conventional insurance, most planning for family funerals would depend on informal mechanisms, such as burial societies, family and friends, churches, or Mashonisas (loan sharks). Funeral parlors themselves could serve as either formal and informal partners in contingency planning.
Paek explained his methodology of mixed qualitative and quantitative methods and his choices to integrate ethnographic methods in his work at the primary site in Khayelitsha, Cape Town, South Africa. His data was collected from 23 formal sector interviews, which drew on informants in insurance companies, MNOs, and TSPs, as well as regulators/legislators, administrators, and industry representatives. He also conducted 6 informal sector interviews with funeral parlors and burial societies, as well as client interviews with 76 survey respondents and 47 focus group respondents.
As inspiration Paek cited the work of Camilo Téllez and plugged his 2012 paper on "Emerging Practics in Mobile Microinsurance." Now that telecommunications companies and mobile money firms were becoming interested in the funeral insurance market, there were even possibilities for paying for funeral coverage with airtime spending. Paek described M-insurance as "fertile ground" for innovative products and presented both a "view from above" and a "view from below" that was informed by Evans' and Pirchio's 2015 research oriented around an empirical examination of why mobile money schemes may flourish in one country and flounder in another. Like other IMTFI researchers he pointed to concepts and notions of trust.
He argued that mobile money might be slower to take off in the context of high crime rates, lack of access to formal legal recourse, inundation by scams, lack of consumer advocacy, saturation with fly-by-night operations, high unemployment rates (which erodes trust in social networks), and a proliferation of scams on the phone. All of these factors undercut potential word of mouth benefits and reinscribe consumer needs for tangibility, typified by desires for a paper contract or a need to see an office. This "seeing is believing" mentality preserves the status quo, as do gatekeepers on the fence between informality and formality. Furthermore, South Africa is a country that is relatively heavily banked, so that mobile money is not something people need. Moreover, there are very heavy regulations, and e-money can only be lent by banks. In these "less than ideal payment systems," the risk of overdraft fees presents an additional deterrent to adoption. When national policies must balance between financial inclusion and consumer protection, South Africa leans toward protection.
"Sports Betting in Uganda: Causes and Consequences" by Sylvan Herskowitz of UC Berkeley encouraged those afflicted with academic snobbery to take a "multi-billion dollar global industry" seriously, which has "exploded across sub-Saharan area" and "quintupled between 2009 and 2013," thanks to a weak regulatory environment, access to international betting markets, new technology to manage bets, and the credibility of payouts With more than 1500 betting branches in a country with less than forty million people, Uganda is a vibrant area of economic experimentation. He laughed at how the signifiers of betting culture were often invisible to Westerners, however, as in the case of the location of an Ebola washing station in front of betting station in Liberia in a New York Times photograph. One of Herskowitz's photographs documented all the international football tickets he had bought. Like most betters he had lost his investment in all of them. This is not surprising, since the standard multi-match ticket requires that all of the wins need to take place. (The lure is that the winning long-shot ticket offers a large payout.
He argued that researchers need to document neglected issue, particularly one with strong behavioral biases. For Ugandan betters this meant spending more than they normally would and ignoring how betting crowds out other expenditures. The numbers are significant, because in his study group of betters, expenditures on betting represented a median 11% outlay of income and a mean of 15%. Most of his respondents (75%) were heads of household. Even though 40% of their families knew they bet, only 25% knew how much they bet. In explaining his work on communities around Kampala on financial motivations, he dropped "economic speak" for a moment to characterize incentives as "if you want to get stuff that's big and expensive" but are constrained in ability to save or access to credit. After all, betting is one way to generate liquidity, despite its bad rate of return. In studying driving factors, researchers offered betters cash or betting tickets and designed the experimental situation so that timing might be before or after they got tickets. The prime increases demand for betting tickets by 15-25%. Participants also chose higher payouts. An experiment in which he gave them a wallet for setting money aside for betting seemed to decrease betting. Rather than frame it as "overrationalizing an activity" he saw it as "encouraging people to reflect." He reported a 10% reduction in betting among those who had underestimated their expenditures. He looked forward to testing more experimental primes to sort out budgeting and failure aggregators, improving data quality by decreasing noise in the results, refining the wallet as a physical instrument, differentiating the benefits of a tangible object from simple targeting, and doing testing in relation to other expenditures such as food.