With greater certainty over the provenance of the data, financial institutions and corporates are better able to mitigate the risks of greenwashing. Third, data for monitoring commitments. Technology solutions can help financial institutions and project owners in monitoring and meeting their commitments to ESG targets. FinTechs are providing financial institutions with good data and analytics to assess and benchmark ESG performance against peer companies. Intensel, a winner of the MAS Global FinTech Hackcelerator last year, uses artificial intelligence to analyse climate data and satellite imagery and assess the physical risks faced by assets to floods, typhoons, storm surges, and extreme heat. Fourth, data for reporting. FinTechs are offering tools to automate the reporting process, while being nimble enough to adapt to various standards, such as the Sustainable Accounting Standards Board (SASB) and the Global Reporting Initiative (GRI). Matter Analytics, another winning solution at last year’s MAS FinTech Hackcelerator, offers reporting solutions that help asset managers, asset owners and banks automatically generate customised and comprehensive impact reports for their clients. The technologies are promising, but that is not to say there are no challenges in this space. First, the ESG landscape continues to evolve. Taxonomies are still being defined and harmonised. These are important efforts that will take some time. Disclosures and reporting requirements are also being formulated by governments and regulators. But financial institutions cannot adopt a wait-and-see approach. They should not look at ESG only from the lens of regulatory requirements.

The demand for trusted data will only grow as regulators strengthen reporting and disclosure requirements. Yet, the availability of good data remains a big challenge. The process of ESG data acquisition is manual, cumbersome and costly. There is also lack of transparency in the verification and reporting process. Technology can be a game changer in addressing these data challenges. First, the problem of data acquisition. FinTechs are offering solutions that connect directly via Application Programming Interfaces (APIs) to existing systems, such as waste management systems, to retrieve relevant environmental and energy consumption data more efficiently. Financial institutions are exploring the use of IoT devices and sensors to measure directly at source, carbon emissions, energy consumption, and pollution. Satellite imagery is being used to track the progress of reforestation and carbon sequestration projects, which enables nature-based solutions and offerings. Second, the problem of data provenance. Here, distributed ledger technology is being considered as a way to maintain provenance 1/3  BIS central bankers' speeches  and traceability in the data. For example, IBM’s Food Trust uses blockchain to connect participants across the food ecosystem, such as growers, processors and retailers, with data collected along the supply chain. This allows them to ensure that food safety protocols and sustainable food practices are adopted at each stage of the food chain. It also allows them to trace any food fraud incidents or food safety breaches back to their source.