Financial institutions in Africa must develop strong climate finance capabilities, given the challenges ahead, to ensure they are more relevant to their environment, while also building good climate-risk resilient portfolios. Technology and artificial intelligence (AI) will play a critical role in making these happen. Climate risk evaluation and financing would need to get really smart to process a wide array of information, which are broader than data in traditional risk models.
With Africa’s participation in COP30 in Brazil, its financial institutions must not be left behind. Climate finance and resilience in Africa is critical now, given climate challenges in agriculture that makes more climate-resilient practices imperative. We also have the challenge of energy poverty and inclusive energy access that climate-smart technologies could solve within a broader energy mix and options. There is also the challenge of managing climate risks, including intertwining and cascading effects of climate change, migration and security, especially in West Africa. Agriculture and food security is inherently linked to security issues, banditry and the challenge of creating a conducive and peaceful environment for commercial and small holder farming.
Escalating climate challenge issues that cascades into security problems, food insecurity, hunger, poverty and migration issues, all mutually reinforcing and fuelling each other multidimensionally, are real challenges for West Africa today. These climate related problems are no longer abstract and academic issues, but real living challenges on the ground for citizens of West Africa. Yet, there are potentials for us to turn these challenges around into opportunities that deliver broader inclusive prosperity. We can do this if we are more proactive with integrated climate resilient initiatives that build stronger climate resilient economies.
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There are also climate risks that affect your business and finance, even if you are not in the climate business. What are the risks that your business or financed assets could get stranded as the world transit to more climate smart technologies? These transition risks and evaluations are not typically embedded in financial institutions’ risk assessments, with the potentials to create long term blindside risks to banks and financial institutions. The same transition risk issues would apply to the invested assets of companies.
How do we collaborate to ensure that critical ecosystem information from diverse players are available for smart AI-aided climate financing decisions? Africa is particularly more challenged in this context, given the siloed nature of its digital public infrastructure, in which a diverse array of critical public good information sits unintegrated and unconnected, implying an additional layer of heavy lifting for smart artificial intelligent innovations.
One of Africa’s leading businessmen recently narrated an experience in Italy, where he had to take an Uber taxi, after waiting a while for his pick-up that did not show up. He revealed that he was picked up by an electric taxi car and the taxi driver told him that he charges his car at €20, which will power his taxi for 500 kilometres. That is the perfect illustration of a transition risk and the potential for long term stranded assets that the investments and financing decisions of companies must be conscious of. In essence, climate resilience, finance and risk issues need to be everyone’s business.
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Financial institutions in Africa must develop strong climate finance capabilities, given the challenges ahead, to ensure they are more relevant to their environment, while also building good climate-risk resilient portfolios. Technology and artificial intelligence (AI) will play a critical role in making these happen. Climate risk evaluation and financing would need to get really smart to process a wide array of information, which are broader than data in traditional risk models. These will include structured and unstructured ecosystem information (from climate/ meteorological, agriculture, telecoms, financial transactions, identity, geolocation, including traditional practices and behavioural data that may be non-quantitative). These wide arrays of information will sometimes need to be processed smartly in real time to support financing decisions.
Smart risk-pricing will make climate-financing sustainable. It will ensure commercial resilience, while maximising social impact. It will create the most optimal balance of the exploitation of opportunities and risk resilience that ensure financial institutions play key impactful roles in our climate economies. Financial institutions typically optimally price well the risk they know (their known-knowns) and overprice their uncertainties (their known -unknowns) or even abandon play in such uncertain markets. Yet, those potentially abandoned plays may represent opportunities unexploited and social impact undelivered. Smart AI-driven, intelligent climate risk-decisions can help banks and financial institutions solve such problems, enabling them to build smart, sustainable commercial and high social impact climate-financing portfolios.
There are two Big Cs that must be addressed to realise the promise of artificial intelligence (#AI) in Climate Finance:
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1) The first C: COLLABORATION: How do we collaborate to ensure that critical ecosystem information from diverse players are available for smart AI-aided climate financing decisions? Africa is particularly more challenged in this context, given the siloed nature of its digital public infrastructure, in which a diverse array of critical public good information sits unintegrated and unconnected, implying an additional layer of heavy lifting for smart artificial intelligent innovations.
Only smart banks with smart technological capabilities, which have solved the problems of their legacy technology ‘path-dependencies‘ would be able to realise the full promise and potential of AI in climate financing. A chain is, ultimately, only as strong as its weakest link.
What are our known-knowns, known-unknowns, unknown-knowns and unknown-unknowns in Africa’s context for smarter, intelligent predictive capability, and risk decisions, including building resilience for unknown shocks that AI predictive capabilities may not model? Financial institutions will need to be very proactive to build partnerships, collaborations and alliances, to have a dynamic feed of critical, structured and unstructured ecosystem information into their climate risk-models for smart financing decisions. This would have to be enabled by technology.
2) Second C: CAPABILITY: How would banks and financial institutions develop the real technology capability for AI aided climate financing decisions? For the past decade or so, we have seen banks struggle with digital transformation and struggle to realise the full potential of digital technology. The promise and the realities of digital transformation have not matched. Banks and financial institutions should never underestimate what it would take (them) to develop the technological capability to realise the full promise of AI (a more advanced technology) in their climate financing business, and learning from their current struggles with digital transformation.
Only smart banks with smart technological capabilities, which have solved the problems of their legacy technology ‘path-dependencies‘ would be able to realise the full promise and potential of AI in climate financing. A chain is, ultimately, only as strong as its weakest link.
Olu Akanmu is academic director of Lagos Business School’s Tech-Leap Initiative.
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