Impact of digitalisation on inflation needs close monitoring: DG Patra

The impact of digitalisation on key economic variables relevant to monetary policy demands close monitoring, especially its effect on inflation, as the price disparities between online and offline goods could potentially steepen the Phillips curve, necessitating a reassessment of traditional inflation models, said Michael Debabrata Patra, deputy governor of the Reserve Bank of India (RBI).

 

Speaking at the Maldives Monetary Authority (MMA) Research Conference, Patra said, “Research interest is being drawn to examine how financial innovations like digital payments, FinTech, central bank digital currencies (CBDCs), and AI can reshape monetary policy transmission and affect financial stability,” adding that dynamic methods and big data analytics like web scraping, text mining, large language techniques, and machine learning frameworks are becoming vital for macro-financial analysis and monetary policy tech.

 

 

Patra highlighted that digitalisation can be regarded as a long-term technology shock impacting economic growth, productivity, labour markets, older technologies, and inflation. The global digital economy is estimated to already account for more than 15 per cent of global GDP, and generative artificial intelligence (Gen-AI) alone is projected to boost global GDP by $7-10 trillion over the next three years.

 

Additionally, he said the proliferation of digital consumption has been accompanied by a shift in saving and investment decisions, such as online brokerage accounts, robo-advisors, investment apps, and the like, as they are easier, faster, and more informed. Digitalisation has also influenced borrowing patterns of households, providing greater and easier access to FinTech companies for digital loans, and reducing information asymmetries through a wide range of sources, including tax returns, electronic toll collection, and bill payments.

 

Having said that, Patra cautioned that these newer technologies pose challenges for monetary and regulatory policy formulation. “The shift from traditional modes of savings can affect the transmission of monetary policy impulses to the real economy. Second, central banks need to be vigilant about the possibilities of debt escalation and risk build-up at the household level,” he said.

 

“…Shifts in consumer behaviour may require central banks and policymakers to transition from traditional macroeconomic models to agent-based modelling, integration of behavioural economics, nowcasting, policy simulations, and advanced liquidity stress tests,” Patra said, adding that central banks also need to equip themselves with cutting-edge computational tools like machine learning and big data analytics to examine real-time, high-frequency data received from digital platforms.