If you take the example of personalised banking, from having a personal manager, today, the scenario is more about having a personalised view on the app. However, the core banking system has been the same for the past two decades, which includes the centralisation of all the branches of a bank.
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This has helped create more services and also reduced incidents of fraud. There are several aspects of the way processes are being done and how that has transformed. Citing an example, Sharad says that generally, when you have to open a bank or mutual fund account, the officer who is opening the account would need to identify you in person.
The Aadhar card allows you to replace IPV in-person verification , with a unique identification number that helps you prove that you exist as a human being without having to go to a bank to open your account.
Various aspects like document verification, credit score checking, document submission have all gone paperless. This is fundamentally because, their companies invested in technology in the 80s and 90s. The regulators in India are proactive.
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Aditya believes that most banks in India moved to core banking after regulatory demands, and NEFT transfers here are unique to the Indian landscape as well. This even holds true to cross compatibility of the ATMs. Today, individuals have better access to their financial information; they can transfer and borrow money online and make investments, which, until a few years ago, was a distant dream.
The corporate banking segment has gone completely paperless. When the RBI came out with its draft regulations in , telecom operators, supermarkets chains, electronic wallets, and prepaid instruments players could open payment banks to accept deposits, for basic savings, and to provide remittance service for millions who were excluded from the digital financial system. These payment banks can issue ATM-cum-debit cards to access funds, but are restricted to holding a maximum balance of Rs.
The payment banks platform can also be leveraged to distribute simple financial products like mutual funds and insurances, but such entities are prohibited from providing loans. The transactions volume via m-wallet had seen close to 3x growth, clocking over Rs.
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Additional Cash Received. The most significant benefits for financial inclusion probably arise from digital platforms making transactional data digital and standardized. Digital platforms are changing how informal merchants and workers trade.
In doing so, platforms are reinventing informality ; whether workers and merchants operated in the informal sector out of necessity or choice, governments or other formal institutions can now access transactional and non-traditional financial data about their activities even if what they do work from home or on the street is the same. Platforms are tackling the burden of standardizing and making visible large volumes of commercial activity because they believe in the value of this data.
As previously informal income streams become standardized and accessible through worker and merchant participation on digital platforms, the business case for serving small businesses or self-employed individuals should become more straightforward.
Already, historical sales data is being analyzed to offer loans to merchants in many e-commerce platform examples. Jumia uses sales volumes history, seller performance, and seller ratings to prequalify merchants for lending offers underwritten by Branch , Baobab, and Invoice Pay.
Jumia has also already captured most of the KYC know-your-customer information, which it also shares with its FinTech Partners. Paytm wants to grow the number of SMEs and sellers on its platform and sees the loans as a way to bring ease of financial assistance to SMEs and merchants in semi-urban and tier-II cities across the country. Additionally, transactional data related to ordering is just as informative for lending decisions as sales. The procurement platform Sokowatch tracks store ordering data across all of its informal merchants.
This has enabled the platform to offer revolving credit to shopkeepers whereby shops can order and receive merchandise on netday payment terms.
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In another example, Twiga Foods applies machine learning algorithms to its purchase order records, enabling the procurement platform to predict creditworthiness. Lenders have noted that this gives them the confidence they need to provide microloans to small businesses.
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Instances of platforms using standardized data streams, alone or via a partner, to offer financial services are becoming more prevalent, but many Global South use cases are still early stage. The devil may be in the details around how easily an activity or transaction can be standardized and how ready financial institutions are to plug into these kinds of partnerships. Opportunities for lending may depend on how much variety there is in the type of work performed on the platform —simpler data streams may be easier to interpret. Platforms with low variety e.
Frequency of transactions may also matter since this has implications for how engaged a worker or merchant is on a platform and whether they are loyal to a given platform. Services business models may offer the greatest opportunity to offer insurance in order to protect workers against on-the-job risks since the imperative exists from a business perspective.
Ride-hailing platforms, like Bolt and Uber, demand that drivers have insurance. To this end, Bolt has sourced, negotiated, and facilitated an insurance scheme for its drivers Taxify Cover. Lynk is exploring per-job insurance so that if a Pro i. In both scenarios, there is an advantage for platforms to source and offer straightforward insurance plans for workers.