Page 126 - Special Topic Session (STS) - Volume 1

STS419 Liza M. et al.
The outcome of the analysis is expected to point IFIs to segments that
would require additional financial assistance. The cornerstone of Islamic belief
is to ensure that "no one is left behind". Through a study of customers' account
standing 7 days post end of the month, the analysis aims to theorise that the
movement after month end (typically post salary disbursement) would
indicate for those in need a reducing balance. The analysis could be repeated
for another two 7 days cycle in which accounts that do not recover in balances
highlight that the group is indeed the target segment of customers that
require cash waqf assistance.
From Figure 1, we have illustrated what the results could look like. In the
depicted example, the process begins with the basis of analysis being based
on education profile, where the pool of beneficiary could be those that did not
complete Tertiary education. From there, the analysis could establish those
who are in white collar jobs and then determine the segment based on a limit
of below RM 2,000 a month income level. Concurrently, it conducts an analysis
of the different genders that make up the segment. Finally, the depicted
analysis carries out the process to determine the income level that is
associated with observation criteria of interest.

4. Challenges in Implementation
It is worth noting the identified challenges of operationalising this
framework. Most pertinently would be the issue of data privacy of customers
and the “stereotyping” nature of the algorithm. Currently, consumer behaviour
towards sharing personal data is still in its nascence. Enhancement of data
security is becoming ever more relevant in order to protect consumer data.
Moreover, the computing power required to store and process the data in the
initial phase of building the Decision Tree model still poses a challenge on its
own. Both of the challenges would incur high cost due to the required
technological upgrade and upskilling of staff.

5. Conclusion
This paper built a theoretical framework for Islamic financial intermediaries
to leverage off Big Data using a decision tree model to enhance social
financing via improved identification of the beneficiaries. This framework
postulates that Islamic Financial intermediaries should qualitatively analyse the
data available to arrive to a descriptive output. The output can be used to build
a model that uses Big Data to allow a deeper insight into the financial
behaviour of potential social finance beneficiaries. This allows for better
planning of social finance policies and programmes that are able to improve
their standard of living. The contribution of this study provides a clear
perspective on the potential uses of Big Data usage by Islamic Financial
intermediaries. The development of this framework was limited by the

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