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Financial service providers depend on informa- can be useful to understand customers better. As a
tion to market services to the needs of customers, to result, it can reduce risk and improve availability and
assess customers’ ability to take on the responsibili- accessibility to a range of financial services, particu-
ty of a financial service, to guard against fraudulent larly credit and insurance.
transactions, as well as to comply with anti-money
laundering (AML) and counter financing of terrorism
(CFT) rules. The lack of accounts means a lack of CDR DATA
transaction history, and thus often little or no infor- Consumption features
mation about a person useful for such purposes. By time window and direction
Widespread adoption of mobile technologies has • Daily call (SMS) events
seen rapid rise in the use of mobile money, especially • Daily duration of call events
• Daily time between consecutive call (SMS)
in sub-Saharan Africa. Mobile money provides many events
of the functions a deposit account has traditional- • Daily time between consecutive events (either
ly provided – and more in terms of easy transfers call or SMS)
among peers. Peer-to-peer transfers can provide Global
access to capital for small investments or funding in • Communications time entropy
emergencies such as loss of a job, sickness or death • Communications entropy
Social network features
of a family earner. However, mobile money does not • Number of unique call (SMS) correspondents
provide the same access to credit-based financial • Call (SMS) delta degrees
services that traditional banking provides. • Number of reciprocated call (SMS) events
Individuals and businesses without access to tra- • Fraction of reciprocated call (SMS) events
ditional financial services present substantially high- • Median of time between reciprocated call (SMS)
events
er risk for financial services firms than customers Mobility features
that do have such access. They have not established • Radius of gyration
a credit or other financial history with such providers • Distance traveled
or a credit reference bureau and therefore present • Popular antennas
• Popular antennas entropy
greater credit risk and higher underwriting costs.
Mobile telephone penetration is universally higher, Source: Pedro, J. S., Proserpio, D., & Oliver, N. (2015).
and often multiple times higher, than the penetration MobiScore: Towards Universal Credit Scoring from
Mobile Phone Data. In User Modeling, Adaptation
of bank accounts. Many individuals can thus access a and Personalization (pp. 195–207). Springer, Cham.
broad range of digital services, including traditional https:// doi org/ 10 1007/ 978 -3 -319 -20267 -9 _16
.
.
telecommunications services such as voice and data,
over-the-top (OTT) services and mobile money ser-
vices. The data generated by this digital footprint
3 TELECOMMUNICATIONS DATA
Telecommunications data includes data held by Modern telephone CDRs also collect additional data
telecommunications operators about their custom- generated by mobile services, including mobile
ers, their accounts, and use of telecommunications station international subscriber directory number
services. As illustrated below, telecommunications (MSISDN) and location registers, which show roam-
operators hold a wide variety of types of data. ing locations of mobile users.
CDR data are used not only for billing purposes,
3�1 Telecommunications usage related data but also for telephone accounting and analysis, net-
work management, and fraud detection. For exam-
3.1.1 Service usage data ple, CDRs showing call attempts can be used to
Telecommunications companies have used call detail analyse quality of service and unusual CDR records
records (CDR) since before the digital revolution to can be used to detect fraud and plan future capacity
manage interconnection and roaming domestical- requirements. CDR data are kept based on standard-
ly and internationally. CDRs track voice call time, ized requirements established by the ITU and other
date, duration, and initiating and receiving numbers. regional standards bodies.
Use of telecommunications data for digital financial inclusion 9