BSP Seek AI Applications to Improve Functions
BSP Seek AI Applications to Improve Functions

BSP Eyes Artificial Intelligence Applications to Enhance Functions in the Philippines

The Bangko Sentral ng Pilipinas (BSP) seeks to dive into machine learning (ML) techniques, especially in natural language processing, nowcasting, and banking supervision in order to better understand the financial system and economy of the country.

BSP Governor Benjamin Diokno expressed, “Central banks’ interest in ML has been increasing over the years, mainly due to its potential to enhance the existing tools used for regular monitoring as well as its ability to uncover underlying relationships between data to better understand the economy and the financial system.”

Machine learning is one of the subfield of Artificial Technology (AI) that involves algorithms that provides output based on patterns learned from data.

Natural language processing at BSP converts text into data to produce a quantitative summary, including the news sentiment index and economic policy uncertainty index that is currently being enhanced.

BSP also uses ML techniques to generate nowcasts of regional inflation and domestic liquidity. These models are an addition to the BSP’s existing suite of models for macroeconomic forecasting.

In banking supervision, the BSP’s goal is to use ML techniques to enhance its data validation processes and better identify atypical data.

Diokno noted that ML gives various opportunities in central banking, mostly when combined with techniques from other disciplines, such as econometrics and network science.

Diokno also emphasized the challenges that come with ML processes. The most often-cited limitation is the black-box approach to ML, which could result in inconveniences in interpreting the causal relationships in ML models.

Just like the traditional econometric system, ML algorithms may also encounter some challenges in correctly forecasting tail risk or low likelihood events.

The adoption of ML models would also require investments in information technology (IT) infrastructure and capacity building, together with a change in the organizational mindset.

As the Philippines builds a more robust and more technologically advanced economy. BSP will continue to develop ML applications that can be useful in conducting its key functions while they consider its associated risks.

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