AgenticInvestor

Saudi Arabia Loans To Banks

Saudi Arabia · Monthly series · EC-SA-LB

Latest, September 2026

72.96B SAR

+27.5% from August 2026

Open interactive chartSaudi Arabia Loans To Banks in the app

78.54B45.17B11.8BAugust 2016September 2027
History through September 2026, the forecast path to September 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for September 2027: 61.16B SAR, with an 80% interval of 43.52B SAR to 78.54B SAR.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
October 202659.47B SAR47.25B SAR71.46B SAR
November 202659.06B SAR46.43B SAR71.28B SAR
December 202659.15B SAR46.06B SAR72.04B SAR
January 202759.54B SAR45.90B SAR72.96B SAR
February 202759.61B SAR45.41B SAR73.20B SAR
March 202759.76B SAR45.11B SAR74.22B SAR
April 202759.99B SAR44.84B SAR74.82B SAR
May 202760.21B SAR44.58B SAR75.93B SAR
June 202760.41B SAR44.04B SAR76.45B SAR
July 202760.59B SAR43.85B SAR76.99B SAR
August 202760.86B SAR43.78B SAR77.60B SAR
September 202761.16B SAR43.52B SAR78.54B SAR

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-15.

AI confidence

Limited evidence

At least 6 complete tests are required; 2 are available.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
n/aToo few tests (2 tests, 6 needed) (2 tests, 1 won)
Direction
n/aToo few tests (2 tests, 6 needed) (20 of 24 calls right in 2 tests)
Turning points
n/aToo few tests (2 tests, 6 needed) (14 turns in 2 tests, 0 without a turn)
Error vs baseline
4% lowerError ratio 0.96; 1.00 is a tie.
Tests won
1 / 2Complete rolling backtests; ties count as no win.
Test period
2024-10-01 to 2026-09-0112 observations ahead per test.
80% band coverage
83%Observed outcomes inside the band across all stored test windows.
How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Replay past tests

Model comparison

Comparison pendingA new ticker first receives its serving model's forecast and evaluation. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Reading

That is the highest of the 118 readings since October 2016.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)
The 24 most recent observations, newest first.
PeriodValue
September 202672.96B SAR
August 202657.23B SAR
July 202645.93B SAR
June 202655.84B SAR
May 202656.45B SAR
April 202634.43B SAR
March 202648.48B SAR
February 202652.91B SAR
January 202645.18B SAR
December 202555.53B SAR
November 202549.28B SAR
October 202549.61B SAR
September 202545.11B SAR
August 202561.67B SAR
July 202554.63B SAR
June 202549.41B SAR
May 202548.55B SAR
April 202546.79B SAR
March 202548.45B SAR
February 202542.75B SAR
January 202540.51B SAR
December 202439.96B SAR
November 202456.05B SAR
October 202441.32B SAR

Source

Data: public market data feeds.

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