Based on over 1,200 digital financial services (DFS) agent interviews conducted between November and December 2015, the ANA Senegal report, funded by UNCDF MM4P Programme, highlights findings on the DFS agent landscape in Senegal covering agent profitability, transaction volumes, liquidity management and other important strategic considerations.
The findings illustrate that the Senegalese digital finance market is fractured between four major players who tend to share agents, thus agents serve a median of three providers. There is widespread adoption of the OTC transaction methodology with money transfers as the anchor product. High revenues and low operating expenses make agents the most profitable among all ANA research countries. The Senegalese market is facing a watershed moment, as many providers are transitioning to wallet-based products. In this transition, providers will want to maintain agent profitability as well as support its customers—not all of whom may be ready.
The cash versus in-kind subsidy transfer (e.g., food, fuel or fertiliser subsidy)[i] has generated much debate all around the globe. However, there is no clarity on which method should be adopted going forward – cash or in-kind subsidies. While both cash and in-kind transfers certainly have an important role in addressing food security, there is no consensus over whether one is better than the other. There are a number of studies that compare in-kind and cash transfers: however, the results are inconclusive. Some studies suggest that in-kind transfer is better as compared to cash transfers, while many others advocate cash transfers.
A cursory look at the issue shows that proponents of cash transfers argue that leakages/inefficiencies are reduced, procurement difficulties are avoided, as are storage and transportation costs, and targeting can be much more focused. While those advocating in-kind subsidy transfers believe that people will consume adequate amount of food grains under an in-kind transfer programme and express concerns related to cash diversion (buying alcohol or putting cash to other uses) in cash transfer programmes. Other reasons cited include inadequate rural banking infrastructure; transaction costs, which are invariably borne by recipients; two trips (at least!) – one to withdraw money and another to buy food grains; inadequate market infrastructure in rural areas; and fluctuations in prices of essential commodities, etc.
In many developing countries, governments are increasingly willing to make direct payments to poor people. Countries such as Indonesia, China, Brazil, Mexico, and South Africa have expanded their cash transfer programmes. India has also introduced cash transfers in schemes on a pilot-basis such as the Targeted Public Distribution System (TPDS), which aims at providing subsidised food grain to low-income families and aims to introduce cash transfers in many other schemes.
The Government of India, on August 21, 2015, issued the Cash Transfer of Food Subsidy Rules, 2015. These lay down the mechanisms for providing cash subsidy instead of supplying food grains through the Public Distribution System (PDS). Under the National Food Security Act (NFSA), the Union Territories (UTs) of Chandigarh and Puducherry rolled out Direct Benefit Transfer (DBT) pilots in September 2015. MicroSave conducted three rounds of assessments (baseline, mid-line and end-line) of DBT in PDS pilots in the above-mentioned UTs.
Beneficiary preference for in-kind subsidy
69 per cent and 80 per cent of the sample respondents[ii] in Chandigarh and Puducherry, respectively, do not wish to continue the ongoing cash transfers, and prefer food grain distributed through Fair Price Shops (FPS). Based on our research, we found the following reasons for such preference:
Insufficiency of subsidy amount: The current subsidy amount provided for grains does not reflect local market rates. For example, the market price of rice in Puducherry is Rs. 35 per kg while the subsidy extended under the cash transfer programme is Rs. 23 per kg. In Mahe (Puducherry), people were concerned about inflation (caused by local traders or otherwise). In Malar (Puducherry) they felt that “prices might increase after the government decides the sum of money’’. Aarti in Chandigarh said, “Prices will not be stable in the market. It will be very difficult for the government to give us the appropriate amount.’’
Transaction expenses: Current subsidy amount does not take into account the costs involved in accessing cash from banks, including transportation, particularly for the old and infirm, and the opportunity cost of wage loss due to travel times and long waits at bank branches. Our field research in Chandigarh and Puducherry showed that the average time spent commuting to the bank and waiting for a transaction is between two and three hours. This adds up to a total cost of Rs. 145 if one were to add opportunity and direct costs.[iii]
Awareness: Low awareness about the rate of subsidy (including its calculation) and the entitlement per individual/family – which causes confusion and anxiety.
‘‘I don’t know what I am getting and what should I get, I just know that I get money every month.’’– FGD respondent, Chandigarh
Self-contribution: People tend to overlook the cost incurred by them while buying subsidised grains from the Fair Price Shop. Mentally, they do not add the amount (typically Rs. 3 per kg for rice and Rs.2 per kg of wheat) to the cash subsidy they receive, as they procure grains from the open market.
Subsidy diversion: Women expressed concerns about diversion of cash subsidy by men – the issue is pertinent to Puducherry, where a majority of transfers (> 70%) were made to the bank accounts of male heads of households. With inexpensive and easily available alcohol[iv] in Puducherry, the perception is strong that men spend a significant part of the subsidy amount for buying alcohol. This is reflected in our assessment; respondents reported that only 34% of the cash subsidy was utilised for buying food grains.
“At least if the money comes to me, I will manage the budget. If he has to withdraw it, I can be sure that part of it will go to drinks since the shop is just next to the ATM” –Female FGD respondent, Karaikal, Puducherry.
In addition to these, we also identified other beneficiary behaviours associated with cash transfers:
There is always opposition to and distrust of change. In this case, beneficiaries have to navigate a significant change in the way the state provides them food subsidy – there is resistance to this. This is compounded by teething challenges in the shift from in-kind to cash transfers, and the inconvenience this has caused the beneficiaries. This reflects Status Quo Bias.[v]
Beneficiaries tend to avoid options for which they have less or no information. In case of DBT in PDS, many beneficiaries did not know the purpose and entitlements under DBT in PDS. This gap in information flow makes them apprehensive and some of the dislike for cash transfers is driven by the lack of information – highlighting the Ambiguity Effect.[vi] For instance, in Chandigarh, many of the respondents did not know their entitlements under DBT; they were unaware of even the purpose of DBT.
Beneficiaries do not consider benefits of cash transfers and tend to forget the problems (of inferior quality and delivery of less quantity than allocated; long queues; and bad behaviour of FPS owners) faced under the earlier system of food grain distribution through FPS. The issues under cash transfer seem larger even as challenges of the earlier in-kind system seem to be forgotten – a classic case of the Recency Effect.[vii]
69 per cent and 87 per cent of the sampled beneficiaries in Chandigarh and Puducherry, respectively, say that the current cash transfer is insufficient to purchase 5 kg of food grains per family member. While this points towards a subsidy calculation system that appears to be flawed, it also points towards some interesting behavioural aspects of clients. Beneficiaries tend to ignore cash contribution that they had to make in the earlier in-kind system, to buy grains. This shows Tunnelling.[viii]
Some of the above-mentioned challenges – real or just perceived, can be addressed through improvements in service quality of the DBT delivery mechanism and raising beneficiary awareness on scheme features. However, it is imperative for beneficiaries to have access to a regular market close to their residence if cash transfer for food is to be successful. Most of the concerns for cash transfers are because of lack of/less information, and poor rural banking infrastructure. These concern areas need to be worked upon effectively so as to gain wider reach and acceptance for cash transfers.
[i] Targeted Public Distribution System (TPDS) is an Indian food security system. It distributes subsidised food and non-food items to India’s poor. This scheme was launched in India in June 1997. Major commodities distributed include staple food grains, such as wheat and rice, sugar, and kerosene, through a network of fair price shops (also known as ration shops) established in several states across the country.
[ii]MicroSave undertook a study to better understand the implementation of DBT in PDS for the MoCAFPD and sampled 3,805 beneficiaries in Chandigarh and Puducherry.
[iii] Based on focus group discussions in Chandigarh (calculated off Chandigarh’s minimum wage of ~INR 340 for 8 hours of work).
[iv] Puducherry figures in the Top 5 amongst biggest beer, wine and refined/ foreign liquor drinking states and UTs nationwide, as published in 2011-12 consumption data from National Sample Survey Office, India, and quoted as “India’s biggest drinkers”, in a report published in The Hindu, August 23, 2014.
[v] Status Quo Bias: The tendency to defend the status quo. Existing social, economic, and political arrangements tend to be preferred, and alternatives disparaged sometimes even at the expense of self- or group-interest.
[vi] Ambiguity Effect: The tendency to avoid options for which missing information makes the probability seem “unknown”.
[vii] Recency Effect: The tendency to weigh recent events more than earlier events.
[viii] Tunnelling: Devoting a great deal of bandwidth to a single scarce resource, while neglecting other things to make space for the focus.
In the earlier system, payment orders were prepared manually at each panchayat from where these were forwarded to India Post for manual processing and transfer of the payment to beneficiary accounts. Beneficiary authentication, at the time of withdrawal and payment to beneficiary, were also done manually because the account details were maintained by the post office concerned in a manual ledger. This system was inefficient, as it led to monetary leakages and payment to ghost beneficiaries, in addition to the inevitable delay in payments.
To address these issues, the Ministry of Rural Development (MoRD) developed the e-FMS (Electronic Fund Management System). e-FMS serves as an MIS for MGNREGS payments and enables electronic generation of Fund Transfer Order (FTO – i.e., electronic payment order), once work details of individual beneficiaries are entered in the e-FMS at block office. It also enables online transfer of FTO from block office to either a bank or to India Post for payment processing. Further, to synchronise with e-FMS and to reduce manual steps in processing of payment order, India Post enabled electronic processing of FTO in Jharkhand. The payment processing steps are given below:
1. CEPT Mysore[2] receives FTOs from MGNREGS block office
2. CEPT sends FTOs to respective HPOs
3. HPOs credit beneficiary accounts
4. HPOs send processed list (i.e., details of credited beneficiary accounts) to CEPT Mysore
5. CEPT Mysore sends processed list to respective SPOs
6. SPOs credit beneficiary accounts (HPOs, SPOs and BPOs are not interconnected, so they manage different databases for customers. HPOs, SPOs and BPOs update their respective customer data bases separately. For this reason, FTOs are routed through all the offices.)[3]
7. SPOs send hard copies of processed list to BPOs
8. BPOs credit beneficiary accounts in a manual ledger.
Even after these changes were effected, transfer of payments to beneficiary accounts took a minimum of 7-8 days from the first step of generating an FTO and sending it from block office to India Post to the eventual credit into the beneficiary account.
Breakthrough
To address the delay in processing of FTO and crediting beneficiary accounts, India Post has rolled out “India Post AEPS” (Aadhaar-Enabled Payment System).[4] In this system, SPO and BPOs are enabled with online front-end devices (tabs, point of sale, and desktops) to carry out beneficiary transactions.
Further, Head Post Office servers remain in sync with a server installed by the state government, which maintains mirror accounts of beneficiaries of government-sponsored schemes. Front-end devices at SPOs and BPOs are connected with the server installed by the state government. Thus, beneficiary accounts can be synced and updated in front-end devices as soon as the FTO is received at the HPO. The revised FTO processing after AEPS enablement is as follows:
1. CEPT Mysore receives FTOs from MGNREGS block office
2. CEPT sends FTOs to respective HPOs
3. HPOs credit beneficiary accounts, i.e., HPO servers are updated
4. HPO servers synchronise beneficiary account data with the state government server
5. State government server synchronises beneficiary account data with front-end devices, which show updated balance in beneficiary accounts at BPOs
1. The inability of bank branches at block level to provide sufficient cash to meet the requirements of SPOs – many bank branches are not able to provide cash of more than Rs. 50,000 (USD 757) in a single day.
2. India Post’s procedures limit the amount of cash that can be transferred from SPOs to BPOs to between Rs. 10,000 (USD 151) and Rs. 20,000 (USD 303) at the discretion of the SPO.[5] One SPO typically supervises 5-6 BPOs. Moreover, SPOs are not able to meet the cash requirements of BPOs, given the limited availability of cash from block-level branches (as outlined in 1 above).
3. Cash holding of BPOs in Naxal (left wing extremist)-affected regions is limited to Rs. 5,000 (USD 75).
The Department of Information Technology, Government of Jharkhand, commissioned MicroSave to study the existing India Post-AEPS system and cash management practices of India Post for MGNREGS payments in the state and to suggest cash management measures to address the issues. Based on the study, MicroSave recommended the following cash management measures, in addition to transit insurance, to the state government:
1. Availability of Cash: Cash availability could be ensured at SPOs through one of two ways:
a. Alternative 1:
i. Once the FTO is received, the HPO can inform the SPOs under its jurisdiction and sponsor bank branch at district level about the cash requirement at SPOs and block-level branches in the next 2-3 days.
ii. On receiving the information from the HPO, the sponsor bank branch at the district level can inform the block-level branches to arrange for cash.
iii. Thus sponsor bank can ensure the availability of cash at block-level branches when SPO visits the branch to encash the Demand Draft (DD) made by HPO.
b. Alternative 2: Where multiple banks are present, HPO can prepare multiple DDs that can be drawn from more than one bank at the block level. So, if, at present, SPO can withdraw only Rs. 50,000 (USD 757) in a single day from one bank, it can withdraw Rs.100,000 (USD 1,515) from two banks, or Rs.150,000 (USD 2,273) from three banks and so on.
2. Disbursement of Prescheduled Dates: Disbursement to beneficiaries can be organised on pre-scheduled dates by communicating specific dates to beneficiaries. This would help BPOs that have limited cash available with them for disbursement. This would also reduce rush at BPOs, reduce waiting time for beneficiaries and ensure payment on the same day. However, there is security risk of money being looted while in transit from SPO to BPO, if disbursement dates are communicated in advance. If this is managed well, this approach can be very helpful in areas where security risk is low.
Conclusion
With these initiatives, turnaround time (TAT) to credit beneficiary accounts has come down from over 20 days to 3-4 days. India Post has also started CBS implantation in the country to cover all HPOs and SPOs. India Post will provide front-end devices to BPOs, which will remain connected with the CBS. These initiatives will bring all the offices of India Post on the same platform to further enhance delivery of G2P and other payments. But, even after such initiatives, cash management will remain a concern. With these initiatives, better cash management practices, recent approval to function as Payment Bank, and the push for Direct Benefit Transfer (DBT), India Post has the potential to become one of the key success stories in India’s drive for financial inclusion.
[1] India Post has three administrative layers at district level, i.e. Head Post Office (HPO) at district, Sub Post Office (SPO) mostly at block, and Branch Post Office (BPO) at panchayat/village level.
[2] Centre for Excellence in Postal Technology (CEPT) Mysore manages back end technology aspects of India Post.
[3] Since the time of this study, India Post has adopted a Core Banking Software (CBS) and will be able to update accounts at all levels simultaneously.
[4] State/India Post utilises SRDH (State Resident Data Hub) database, which is a state-specific copy of Aadhaar database. Payment to beneficiaries is done through Aadhaar-based biometric authentication.
[5] The standard operating procedure permits Rs. 5,000 as cash holding per BPO. But the limit given does not suffice for the volume of business at the BPOs. Hence, SPO, at its discretion, provides the BPOs with cash over and above to the stipulated limit.
It’s a common belief that agents in rural regions need more cash than e-float to meet the demand of their customers, while in urban areas cash-in and cash-out transactions balance themselves out. The 2013 Agent Network Accelerator (ANA) Uganda Country Report revealed that more than half of agents in Northern Uganda (57%) require more e-float than cash. As Northern Uganda is predominantly rural, this finding is extremely intriguing.
High demand for e-float implies that customers are conducting more deposits than withdrawals at agent outlets. In Northern Uganda, 43% of households live below the poverty line—two times the national average—therefore one would expect this region to be a net recipient of domestic remittances. What makes Northern Uganda unique in the unconventional demand for e-float from other rural regions?
Research conducted in Northern Uganda revealed that investments in and proceeds from agriculture activities has increased the amount of money in circulation within the ecosystem which has, in turn, created opportunities for mobile money transactions—such as smallholder farmers engaged by large, commercial farms. In fact, mobile money agents in Northern Uganda report that they experience high demand for e-float during the months of the two harvest seasons (July to August and November to December) when traders and farmers earn high revenues.
Traders and farmers in Northern Uganda seem to be moving closer to digitizing the agricultural value chain. Unlike other agricultural regions in the country, Northern Uganda has dedicated value chain players (such as the Sorghum Value Chain supported by Nile Breweries). Traders, who play a key role in this value chain, make most of their purchases to their suppliers in the region and even across the border in Congo and South Sudan using mobile money.
Traders choose to digitise their payments because digital payments are a faster, convenient and cheaper means of purchasing supplies than physically travelling to Kampala or outside the Northern Region. They also choose to employ digital payments to increase safety against theft, robbery or fake currencies. It seems that for traders mobile money is a trusted medium for bulk merchandise payments which has resulted in the high level of deposits into their mobile money accounts, and thus agents’ need for more e-float than cash.
Further, paying suppliers is not the only reason agents experience a high demand for e-float. As a result of the income earned from the harvest, traders and farmers deposit money to their mobile wallet accounts. With an estimated 0.2 formal bank branches per 10,000 persons, most of which are located within urban centres (Lira, Gulu, Arua), Northern Uganda has the lowest bank penetration rate in the country. Mobile money agents are accessible and mostly at their doorstep. As a consequence, people store money on their e-wallets as the best option available. Agents note that customers make payments for school fees and send pocket money to their children, as well as remittances to relatives and friends outside the Northern Region.
How Do Agents Cope?
An illiquid agent impacts his/her ability to meet customers’ demands and can hurt an agent’s business. In discussion with agents in Northern Uganda, while they understand the cyclical swings in e-float demand associated with the agricultural/harvest seasons, maintaining a sufficient amount of e-float remains a challenge to rural agents. This is because they lack the appropriate capital, resources, management techniques and at times willingness to invest in their mobile money operations during the planting season.
We interviewed agents who frequently borrow e-float from other agents; an innovative coping mechanism which we also witness in Tanzania. Whilst this is encouraging, these informal management systems can put pressure on the lender, and would benefit from making this arrangement more formalized.
We found that agents carry a small amount of capital for their mobile money operations and thus run out of e-float more often, resulting in the need to rebalance before the next transaction. In fact, in some cases non-dedicated agents often have to choose between their mobile money and parallel businesses when it comes to cash management, mostly during the planting season (when farmers tend to their land). During this time period, agents choose to keep more cash than e-float as they would rather speculate in their parallel business. An illiquid agent can lead to poor customer service such as denying a customer’s transaction or forcing a customer to split their transaction—which increases both their transaction fee and the time a customer spends to transact.
What Can Providers Do To Help?
The need for e-float in Northern Uganda highlights the importance of digital financial service providers to understand both the needs of their rural customers as well as the liquidity management challenges and coping mechanisms of rural agents. While we understand that liquidity management in rural areas is complex, based on our research with agents, we recommend offering the following services to help agents overcome e-float shortages.
Provide float on credit: Some master agents in Northern Uganda provide e-float on credit. One master agent interviewed provides a 30-minute e-float credit to his agents by sending a float runner to collect the cash. If within 30 minutes the cash isn’t received, the line for the agent is blocked. This indicates an opportunity for structuring an e-float loan product. Access to a sustained flow of e-float through credit financing will enable agents to serve their customers better and build their loyalty.
Develop a reward structure for agents who are inclined to save money than having at disposal: Agents in Northern Uganda use their till as a safe way of banking their business earnings and during the low agricultural season they invest in their parallel business as they weigh between the mobile money commissions and this other business. Providers can reward agents who increase their e-float held during the harvest period, so as to ensure that they can serve customers and thus grow their business.
In Northern Uganda, agents’ and customers’ float requirements indicate that P2B and B2B payments are growing and are linked to their agricultural livelihoods. The mobile money use case in rural Uganda seems to be slowly evolving from domestic remittances to payments and deposits. This implies that practitioners will need to understand triggers for such payments, such as economic seasonality and design practices that suit customers’ and agents’ liquidity needs.
Typhoons are great engines of destruction. When a typhoon makes landfall it often produces a devastating storm surge that destroys everything in its path without mercy. The best defence against a typhoon is an accurate forecast that gives people time and means to get out of its way. It is therefore prudent to watch, watch again, and then watch out if you happen to be in a typhoon-prone area.
Since its inception, the digital financial services (DFS) industry has been subject to a wide range of frauds, across different markets and players of the ecosystems. The diverse nature and scale of these fraud cases has been evolving across markets. As a result, most digital financial services operators are now deploying in-house, dedicated fraud teams. Supply-side research by The Helix Institute of Digital Finance in Bangladesh and Kenya identified fraud as the biggest concern amongst agents, in 2013 and 2014. Our recent surveys in both Tanzania and Uganda highlighted how prevalent it has now become—42% of agents and a little more than half of agents, respectively, indicate that either they personally, or one of their employees, have experienced fraud in the last year. In other markets, such as Zambia and India, it has been cited as one of the top challenges to an agent’s business in 2014. In response, The Helix Institute collaborated with leading specialists to build a Risk and Fraud Management in DFS course. The course highlights key risks as well as mitigation/management strategies.
Emerging trends involve both internal employee fraud and fraud by external parties. DFS provider employees can use their position to gain access to confidential customer information, especially in cases where there are no tight checks, and then use this to target customers, gain account access, or otherwise obtain client funds. In one mobile network operator (MNO), employees colluded and stole about US$ 3.4 million through accessing the company’s suspense account which temporarily holds unclassified or disputed transactions. The staff members were then able to generate e-value and redirected the funds for withdrawal through some colluding agents. This was due to lack of appropriate reconciliation procedures and mismanagement of the user access rights for the mobile money system, where staff members were using multiple active system user log-in credentials. In Rwanda, an MNO found one of its staff members orchestrating fraud by redirecting funds amounting to US$ 673,943 for withdrawal through conniving agents over a 12-month period. In South Africa, the collusion between a few employees of a major MNO and a bank resulted in a major SIM swap fraud. This resulted in the loss of thousands of Rand.
Third parties, such as employees of institutions providing outsourced services or unaffiliated fraudsters, generally contact agents or customers indirectly through social engineering (typically spoofing/phishing) scams to fraudulently obtain account information and rob them. Others have been able to hack into accounts or wallets, to ultimately obtain funds illegally. Recently, in India, 5 engineering students robbed a private sector bank of tens of millions of Rupees using fake mobile wallet transactions over a period of four months, since December 2015. The students managed to hack into the bank’s newly-introduced wallet so that if a customer tried to send funds to another wallet holder, and the recipient was offline, the initiator of the transaction did not end up losing any funds. Instead, funds were pulled from the bank and directed to the fraudster’s wallet. This fraud case was uncovered when about US$ 1.2 million had been siphoned off. In Kenya, fraudsters who are typically prison inmates, with illegal access to mobile phones through syndicates, continue to perpetrate fraud through social engineering. The latest methods used are through calling or sending text messages to random numbers, either in pretence of being relatives requesting for funds or as representatives of different companies: for example, banks or supermarkets, communicating about winners of special promotions. In the latter cases, they request that the subscriber sends funds to a specific mobile wallet to ‘activate’ their winnings, in order to receive their large cash prizes.
The latest random messages being pushed around Kenya target anyone who is about to send funds. These text messages are as “Please nitumie ile pesa kwa hii number, simu yangu imezima”, which translates to “My phone has gone off, so kindly send those funds to this number instead”. Since sending money is a common activity, when some people receive this text message, they are duped into believing it has been sent by the intended recipient. They are misled into thinking that the intended recipient is having trouble accessing their normal wallet/phone, and so are providing an alternative number so that funds can be transferred. The sender then send funds to the new number. Many innocent customers have lost money by responding to these calls or text messages, with those living in the rural areas most commonly hit.
These are just a few examples of a multitude of alarmingly creative approaches to defrauding agents and end-users. Among customers, there are also perceptions of fraud vulnerability as identified by Consumer Protection and Emerging Risks in Digital Financial Services report by CGAP, MicroSave and BFA, which also reaffirms the prevalence of these occurrences. The general trend is that frauds that circumvent back-office systems result in large-scale losses to the providers, while smaller frauds from third parties often target lower amounts from agents or customers.
But how should providers heed evolving fraud?
Typhoon-prone countries have increasingly sophisticated early-warning systems. Similarly, DFS providers need sophisticated risk/fraud management systems. Providers need to understand fraud and track its evolution over time in order to manage it effectively. This understanding is derived from robust monitoring of the ecosystem and fundamental monitoring questions are asked on an on-going basis: What new fraudulent activities are happening? Is there a trend? Are all controls adequately designed and executed? Are employees aware and do they understand their roles and responsibilities?
Fraud Management Systems
DFS providers need sophisticated risk/fraud management systems (FMS). The FMS help service providers to understand the nature of frauds. A lot of data is generated from different systems in any DFS provider. FMSs enable fraud managers to use this data and design rules and algorithms to track the pattern of frauds. They enable them to set fraud rules which help in identifying collusion checks, velocity checks, threshold checks, black-list checks, new subscriber checks, profile checks, SIM swap checks, etc. These systems help providers to understand fraud and track its evolution over time ― thereby helping to manage them effectively and reducing revenue losses. Velocity and pattern detection tools, which are real-time, dynamic, efficient, and effective in finding patterns that point to fraud, add powerful capabilities for next generation fraud management.
Reliable and relevant data and dashboards
Data is critical for monitoring and managing DFS fraud. Reliable data is generated through working with technology providers to build robust systems or tools that determine and track normal and abnormal behaviour. Providers need to ensure robust prevention measures on the first line of defence – registration or account opening processes. Combining this with data-driven alerts can provide real-time, multi-channel defences to address a wide spectrum of fraud threats. At the same time, more traditional “maker-checker” approaches to ensure segregation of duties, together with back-office monitoring and reconciliation teams, are key to maintaining the integrity of digital finance systems.
Internal control
Providers need to ensure robust internal controls. They can be of two types: preventive controls and detective controls. Some examples of preventive controls can be measures like limiting number of transactions per day (value or volume), authentication of transactions, having passwords at different levels, providing limited access to employees, etc. These are generally low-cost solutions to the providers. Detective controls, on the other hand, are post facto. Typical detective controls are: understanding the patterns of transaction activity, reviewing high-value /high-volume transactions, monitoring log-in activity of employees, etc. These tend to be expensive, since DFS providers need to build systems for this. When any fraud happens, preventive measures offer the first line of defence.
Clear reporting and communicating channels between stakeholders, including customers
Different providers have different organisational structures, which determine the number of stakeholders involved. Internally, managers, back-office support, customer service, and finance and revenue assurance teams must all be aware of fraud risk and encouraged to communicate any anomalies or suspicious activity to relevant internal parties. External communication to agents and customers is equally important for effective preventive control. Awareness creation among customers on how to avoid the risk of fraud is a critical preventive measure to reduce customer spoofing/phishing scams. Lastly, in the event of the detection of suspicious activity, clear internal procedures defining both how to escalate awareness and ensure immediate action, need to be in place. Whistle-blowing within institutions should also be encouraged.
DFS ecosystems continue to evolve; however, with this the scope for fraud is also growing. For DFS to realise its full potential, all stakeholders inclusive of regulators, donors, providers and their partners, as well as customers, have a role to play in combating fraud – and minimising the risks of DFS being swept away by burgeoning typhoons of fraud. The first HelixRisk and Fraud Management in DFS, is ongoing – click here to check it out!
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Insufficiency of subsidy amount: The current subsidy amount provided for grains does not reflect local market rates. For example, the market price of rice in Puducherry is Rs. 35 per kg while the subsidy extended under the cash transfer programme is Rs. 23 per kg. In Mahe (Puducherry), people were concerned about inflation (caused by local traders or otherwise). In Malar (Puducherry) they felt that “prices might increase after the government decides the sum of money’’. Aarti in Chandigarh said, “Prices will not be stable in the market. It will be very difficult for the government to give us the appropriate amount.’’
Source: Compiled from