Climate physical risk is now sitting in African agri loan books

The 2022 drought across the Horn of Africa drove non-performing loans in agricultural portfolios up by 200 to 400 basis points across multiple Tier 2 lenders we have worked with. The 2024 East African floods did similar damage, in different counties, to different crops, in the same loan books. This is not a once-a-decade tail event any more. It is the new climatology.

Physical climate risk is now sitting inside African agricultural loan books as a measurable, recurring driver of expected credit loss. Few banks have measured it. Most still treat agri losses as idiosyncratic borrower events rather than climate-driven portfolio events.

Climate physical risk as a recurring driver of expected credit loss in African agri portfolios — The losses are recurring, the exposure is concentrated, and the data to see it is free.

Three moves that close the gap

Three concrete moves close the gap, and none of them is glamorous.

Three moves that close the agricultural climate-risk gap — Georeference the book, overlay public hazard data, then translate the result into basis points.

Georeference the agri loan book. If you do not know what coordinates your borrowers' farms or processing facilities sit on, you cannot overlay drought, flood, or temperature-anomaly data on them. The first deliverable on every agri-portfolio climate engagement is a georeferenced borrower map. Many banks resist this on data-privacy grounds; the regulatory pressure in 2026 is moving sharply in favour of doing it anyway.
Build a hazard overlay using public climate data. ECMWF, NASA POWER, and CHIRPS rainfall datasets are free, well-documented, and have historical depth going back decades. Sub-county-level drought and flood return periods can be built from them. The output is a hazard score per borrower location that you can join to LGD assumptions in your ECL model.
Stress test, do not narrate. A 1-in-10-year drought scenario applied to the georeferenced book should produce a portfolio-level impact you can report to the credit committee in basis points of LGD increase. If your scenario output is a narrative paragraph rather than a number, you do not have a stress test. You have a memo.

The diagnostic typically reveals that 15 to 25 percent of an agri portfolio sits in hazard hot-zones that the bank's standard credit model does not see. That is the provisioning conversation worth having.

Where ARMA comes in

ARMA's agri climate stress engagement is a 10 to 14 week build that delivers a georeferenced loan book, a public-data hazard overlay, and a credit-committee-ready scenario output. It is built for Tier 2 and Tier 3 African banks with material agricultural exposure, typically 15 to 35 percent of the book. Visit client.africarisk.net to scope the engagement.

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