Page 234 - Contributed Paper Session (CPS) - Volume 7

CPS2069 Pamela Kaye A. T.
The members of the Philippine Statistical System (PSS) must remain
closely coordinated in researching and compiling best practices in the
statistical techniques and methodologies to address Big Data’s inherent
veracity and volatility issues.
3. Data Governance: The Philippine central bank must be able to establish
a single Data Governance framework which will serve as guidelines to
direct work flow, processes and data management with regard to how
data should be accessed, used, and protected. Without a single
framework, incoherent practices on Big Data management may pose risks
to data quality and security. The path towards a wider and more inclusive
data-sharing and collaboration in accessing information-rich data sets
must be clearly linked with data security. The extent and coverage of the
legalities involved in Big Data is not limited to consumer rights and
protection, intellectual property rights, copyrights, and licensing
arrangements with partner providers. Liabilities for Big Data breaches
must be discussed and clearly defined.
4. Data Confidentiality: Big Data usually consist of highly personal and
private information that the BSP must safeguard against cyber security
threats and confidentiality risks. Although the Philippine central bank
adheres to the guidelines set by the National Privacy Commission (NPC),
specifically the Data Privacy Act of 2012 and its Implementing Rules and
Regulations (IRR), the BSP must still enhance its data security layers (i.e.
cryptography, user access) to mitigate reputational risks and loss of trust
from its key data providers.
5. Cyber Security: Given the high volume and high velocity nature of Big
Data, cyber security measures must be stringent and reliable. Preventing
cyber-attacks must be real time, swift, efficient, and effective. Threats,
therefore, must be countered proactively rather than reactively given the
wide variety of data sources and the data’s high level of sensitivity.
6. Capital Resources: Organizational readiness in terms of BSP’s capital
resources is vital in keeping up with Big Data developments and
opportunities. Human and technological resources must be compatible
and/or up to speed with the demands of Big Data to ensure operational
efficiency and effectiveness in data collection, management, analysis, and
timely dissemination to BSP management for policy-making.
a. Technological Capacity: One of the pressing cost implications of Big
Data is the expenditure related to the acquisition, installation, and
maintenance of digital infrastructures (e.g., hardware and software
compatible with Big Data). The BSP’s current IT infrastructure may
need to be upgraded to keep pace with the developments in
collecting, processing, storing, and managing Big Data.

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