Page 17 - FIGI - Use of telecommunications data for digital financial inclusion

4�4 Fraud prevention mandatory in the banking industry and, increasing-
Analysis of location data from mobile telephones ly, also for possession of SIM cards. KYC informa-
indicate that ‘human trajectories show a high degree tion generally requires a service provider to collect,
of temporal and spatial regularity, each individual verify and maintain basic identity information about
being characterized by a time-independent charac- customers, subject to audit by or sharing with the
teristic travel distance and a significant probability to relevant regulator. The information collected and
return to a few highly frequented locations.’ Analysis maintained generally includes verification of the
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of mobile phone data of 500,000 Orange customers customer’s name, address, nationality, and an official
in Cote d’Ivoire demonstrated that ‘human mobili- government-issued identification number, such as
ty is highly dependent on historical behaviours and a passport number. Some jurisdictions also require
that the maximum predictability is […] an approach- biometric data such as a photograph or a copy of the
able target for actual prediction accuracy.’ That customer’s government-issued photo ID.
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‘humans follow simple reproducible patterns’ offers Many individuals and businesses that require
potential to identify anomalous behaviour, and so basic financial services do not have traditional bank
detect potentially fraudulent financial transactions. accounts and therefore no financial institution has
Data indicating that a person is transacting from an collected or verified their KYC information. Addi-
unusual location may be made available to third party tionally, banks have generally instituted KYC systems
financial service providers, such as digital payment appropriate to their bricks-and-mortar business
service providers and credit card companies, which model. Mobile operators, on the other hand, have
they may use to block transactions until the individu- collected and verified KYC information on a much
al’s identity is verified. broader segment of the population, including many
individuals using mobile money services that do not
4�5 Identification and AML/CFT have traditional bank accounts. The mobile opera-
Digital identity is another area where telecommu- tors have also developed KYC processes consistent
nications data has great potential to expand finan- with their mobile, digital business models. These
cial inclusion. Global efforts to fight terrorism and MNO KYC processes include appropriate sharing of
money laundering have driven “know your custom- KYC data with regulators and other third parties such
er” (KYC) obligations in several industries, but as specialized KYC verification platforms and atten-
these KYC obligations do not need to function in tion to privacy, data protection and data localization
industry silos. Internationally, KYC requirements are requirements.

5 MODELS FOR SHARING OF TELECOMMUNICATIONS DATA

Although MNOs do directly provide certain fintech appears to be the earliest form of sharing for
services, especially mobile money services, the real DFS.
value of telecommunications data for increased finan- • Under a data sharing proprietary product mod-
cial inclusion requires a “partnership” between an el, the MNO does not share any raw data or
MNO and a financial services provider (FSP) where- enter into a formal partnership with a financial
by the telecommunications data is used to improve institution. Instead, the MNO collects, processes
delivery of the FSP’s financial services. The partner- and packages subscriber data into credit scores
ship between the MNO and FSP does not need to be that can be sold to lenders and other financial
a formal legal agreement or take a particular form, services providers as a separate product. In this
but there needs to be a mechanism for data held by model, there is no sharing of raw data. The data
the MNO or insights from it to be shared in some way is shared in the form of the separate credit scor-
with the FSP. ing product.
We explore here two broad models for sharing
telecommunications data for digital financial ser-
vices: 5�1 Data sharing partnership model
The first model is a formal partnership where the
• Under a formal “partnership” model, an MNO contractual documents forming the legal arrange-
and a financial institution enter into a strategic ments set out the terms and conditions for sharing of
partnership and share data for that purpose. This telecom data for fintech purposes. One of the earliest

Use of telecommunications data for digital financial inclusion 15