What is Mobile Money?
Mobile money is the basic form of sophisticated MFS in emerging markets, comprised of a variety of financial services, delivered via mobile handsets. It is useful in emerging markets due to the lack of robust institutional and/or legal infrastructure supporting access to finance of the unbanked segments of populations.
Within the context of mobile money, key technologies enable more sophisticated MFS through secure consumer onboarding and reliable risk decisioning. The former largely involves digital identity formation and verification to carry out KYC/AML/CFT checks and safeguard consumers’ money, whereas the latter is concerned about utilisation of fragmented and dynamic data to build credible profiles for mobile money users for FIs and/or alternative credit providers to base lending decisions on.
IDaaS
Strong customer authentication, identity-related security measures, and assessing creditworthiness accurately, are must-haves for digital financial provision. In the context of emerging markets, the concept of digital identity is more complicated due to patterns of economic engagement of the unbanked/underbanked population segments and overreliance on cash transactions, leading to a lack of financial records.
To overcome challenges associated with information gaps, the IDaaS model ‘leverages the customer relationships held by mobile operators to create a unique financial identity and credit score for mobile phone users.’ A unique identity, in such cases, is mainly a functional identity. Customers’ relationships in a functional identity context can be simple transactions, such as airtime top-ups and purchases and tariff/account plans.
Moreover, for other ecosystem actors such as FIs and merchants, such data is an invaluable resource to serve the unbanked/underbanked segments while widening their customer base and developing business models (ie, for FIs, by reducing the cost of delivery and for merchants, by differentiating customer services/products according to credit worthiness).
IDaaS providers are sought-after actors who, through incorporation of biometrics and AI/ML-based technology such as facial recognition, fingerprint, and iris scanning, as well as additional verifiers like device data and customer behaviour analysis, are able to identify, verify, and authenticate users. Similar methods are employed to authenticate transactions; enabling customers to use standard financial services digitally. By tracking customer spending patterns and behaviour, potentially fraudulent activities can be foreseen and mitigated, increasing the trust in MNOs and merchants operating on mobile platforms provided by them.
IDaaS is, therefore, an enabler for offering more sophisticated MFS by providing a first step for identity verification.
However, these technologies are not without their challenges. MNOs and other providers face increased risks stemming from identity theft/fraud which can take the forms of SIM swapping, fraudulent account opening (ie, through forged identity documents), and fraud during online transactions. Therefore, IDaaS providers will need to continue developing their verification and consumer onboarding methods by leveraging more assistance from telcos, MNOs, and other fintech solution providers to achieve robust identity formation and verification without compromising user experience and impeding use of basic financial services.
A successful IDaaS model is a collaborative one between all industry actors, including global identity coalitions (ie, Kantara Initiative) and broader initiatives (ie, the United Nations’ Legal Identity Agenda-ID4All). The use of MNO data can further the use cases based on identity formation and subsequent risk decisioning activities, for instance, personalisation of products/services, as currently employed by many embedded finance providers. As mobile handset/smartphone proliferation continues and mobile finance models and MFS use cases develop, identity provision and verification needs will accelerate.
Alternative Credit Scoring
Stemming from the advancement in digital identity services’ leveraging of data, alternative credit scoring solutions have been growing in popularity for the past couple of years. As opposed to traditional credit scoring, alternative credit scoring vendors employ dynamic and incremental data relating to customer transaction patterns and transaction information to assess creditworthiness of unbanked/underbanked population segments. This data can include frequency, recency, and the value of monetary transactions.
Alternative data provided by MNOs and solutions in collaboration with TPPs (Third-party Providers) for credit scoring also open possibilities for enhancement of various other lending, as well as payments use cases, such as microinsurance and BNPL. These pave the way for transitioning MFS into more sophisticated services. One of these spinoff services would be rewards linked to transaction frequency and utilisation patterns.
For instance, mobile microinsurance and health services provider BIMA launched a health wallet and app where users can manage their health subscriptions, earn, and use health points (collected by subscriptions) which, in turn, are utilised to purchase medical products, treatments or wearables. Rewards data can assist in building and enhancing credit scores and profiles of users.
Related Reading
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