— SECTORS · BANKING
When the model is the capital.
Expected credit loss, counterparty exposure, and market risk are not reported by banks — they are modelled by them, on the strength of the data feeding those models. Under Basel and the Prudential Authority, the assumptions and analytics inside them decide how much capital a bank must hold. We build, review, and interrogate them so the number survives the committee that has to sign it off.

— THE LANDSCAPE
THE STATE OF THE SECTOR
South African banks operate under one of the more rigorously assessed implementations of the Basel framework on the continent — the country’s counterparty credit risk rules have been judged compliant with the Basel standard by the Basel Committee’s own review programme. That bar is still rising. The finalisation of the post-crisis reforms — Basel 3.1, widely called the endgame — is phasing in internationally through 2028, bringing a revised output floor that forces banks using internal models to also compute risk-weighted assets on the standardised basis, and the Fundamental Review of the Trading Book reshapes how market risk in the trading book is capitalised.
For any bank with a derivatives book, the standardised approach to counterparty credit risk (SA-CCR) now governs how exposure at default is measured — replacing the old current-exposure method with a more risk-sensitive calculation that recognises netting and margin but, on the Basel Committee’s own estimate, raises counterparty capital requirements materially under full implementation. Exposure at default is built from replacement cost and potential future exposure, aggregated across ISDA netting sets and offset by collateral. Every one of those components is both a modelling decision and a data question.
The Prudential Authority reinforces this with a hard governance line: banks using internal models must obtain prior written approval before changing them, and validation documentation must be presented to the regulator. In other words, the model in production must be demonstrably the model that was validated. For a bank’s risk and finance functions, this is the defining reality of the sector — provisions, capital ratios, and trading-book charges live or die on assumptions and analytics that must be traceable, defensible, and stable under scrutiny.
– WHERE WE WORK
WHAT WE MODEL AND ANALYSE
01
Trading book & counterparty credit risk
Exposure and capital modelling for derivatives and traded portfolios — SA-CCR exposure-at-default (replacement cost and potential future exposure), netting-set aggregation under ISDA master agreements, collateral treatment, and the CVA/XVA adjustments — built to feed regulatory capital and withstand FRTB-era, desk-level scrutiny.
02
Banking book & credit risk
Expected-credit-loss and IFRS 9 provisioning across retail and corporate lending — staging logic, forward-looking assumptions, and PD/LGD/EAD estimation — reviewed against the flaws that most often move the provision and the capital that follows from it.
03
Collections & recoveries analytics
Data-driven recovery strategy for distressed books — right-party-contact and contactability modelling, channel and treatment optimisation, roll-rate and recovery-curve analysis, and portfolio valuation — the analytics that lift recovery performance while standing up to conduct-side scrutiny.
04
Risk analytics & reporting
Turning high-volume banking data into decision-grade insight — exposure and concentration analytics, risk-metric dashboards, and reporting layers that let risk committees see what the numbers are actually saying, not just what they total to.
05
Independent model review
Second-pair-of-eyes validation of existing models — logic, structure, assumptions, and error-checking — ahead of a credit committee, an external audit, or a Prudential Authority submission, where model-change approval and validation documentation are non-negotiable.
— WHY ALETHEIA
THE DIFFERENCE
Aletheia is an analytics and modelling firm — and in banking the two are inseparable. A capital model is only as sound as the data and analytics beneath it, so the work runs from interrogating the inputs to building the model to explaining the output. This is the sector where Aletheia’s founder has worked most directly: mapping counterparty credit risk processes from trade capture through to SA-CCR and SIMM regulatory reporting, rebuilding validation workflows, building the analytics behind risk metrics, and modelling the numbers that drive capital — PFE, EAD, and XVA.
The firm’s conviction is exactly suited to a sector this heavily supervised: analytics and models exist to reveal what is true, not to produce a flattering capital number. Inputs, calculations, and outputs are kept separate, every assumption is documented, and the logic is built to be explained — because a model that cannot be defended to a credit committee or a regulator is a model that cannot be trusted.
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YOUR EXPOSURE, TRACED
Under SA-CCR and Basel 3.1, the data and assumptions inside your models decide the capital you hold. Before your next validation or submission, they deserve independent scrutiny. Tell us the problem.
ALETHEIA PARTNERS
Analytics. Modelling. Truth.
A specialist analytics and modelling consultancy, grounded in actuarial science. Based in Johannesburg, working with corporates, project sponsors and investors across Africa.
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