The municipal valuation of residential properties has become increasingly important to ratepayers as it forms the basis of rates and taxes and if valued too high, ratepayers will pay more than they need to – for at least five years before the next valuation comes around.
The issue has been topical in recent weeks as residents in both Johannesburg and Cape Town have been reviewing newly tabled valuation rolls.
Hayley Ivins-Downes, Head of Digital at Lightstone Property, said several existing Lightstone products, using technology, data and artificial intelligence, will help eliminate valuation variances and inaccuracies, and so provide ratepayers with the certainty and comfort that the rates they pay are appropriate.
“Three of our valuation products help clients effectively capitalise on the opportunities hidden in trends. AI Valuation Model (AiAVM), Estate Agent Valuation Model (EVM) and AI Powered RCV combine the power of Artificial Intelligence with our traditional products and processes to help identify new opportunities or cut significant operational costs for our users”.
The AiAVM has been running in parallel with Lightstone’s existing AiVM product for six months, and delivers increased coverage, accuracy and usability in property valuations.
“We have seen an increase in the proportion of our AVMs predicting within range from just over 70% to close to 85%, and more importantly, we’re setting a new standard for ourselves and the rest of the industry with pinpoint accuracy within 10%”, she said.
On this measure within 10% accuracy, there is a massive 17 percentage points improvement, and Lightstone is able to provide usable estimates for an additional 690k properties.
Ivins-Downes said the increased coverage and accuracy will have a direct effect on the average cost of granting loans as well as the speed of turnaround in a highly competitive environment where consumers expect instant responses.
In consultation with Estate Agents on the ground, Lightstone recognised a need for a product that might not be fully self-driving like the AiVM, but that can simplify the price counselling process with the buyer and seller during complex and often emotionally loaded negotiations.
“Our new EVM will give the Estate Agent a more scientific and realistic trading range in the suburb, as well as an accurate range of the upper and lower bounds the property could trade in.”
This will help secure mandates from sellers while ensuring that realistic offers are made by buyers in line with the value lenders and other industry players will place on the property.
EVMTM
The AI Powered RCV has been developed for insurers and re-insurers to use during underwriting and portfolio risk assessments “because we recognised that the construction and replacement costs of homes our insurance clients carry on their books have significantly drifted from market values in most parts of South Africa,” Ivins-Downes said.
For this reason, Lightstone developed an AI powered RCV with similar confidence scores attached to the predictions for insurers and re-insurers to use. When comparing the confidence scores to actual results through Physical Valuations, the majority sit in the 71% to 80% accuracy band, while a smaller portion are in the 81% to 90% confidence score accuracy band.
Lightstone only compares results against physical valuations which in themselves might be inaccurate – but even with that limitation, the distribution of confidence for this model shows pleasing results. It is in different stages of testing and adoption with Lightstone’s insurance clients and available on API.
Accurate property valuations for ratepayers
Lightstone’s EzRates assists ratepayers in easily accessing a Lightstone Property Value Buyer Report so they can check if the municipal value on the General Valuation Roll is in line with the property’s estimated market value.
This report gives property owners the peace of mind that they have reliable data about their property value and it can also be used as supporting documentation for any objection to information recorded on the Roll, as it includes all the property information registered at the Deeds Office, such as the owner’s details, the size of the property, intel on recent sales in in the area – and much more!
Other experimental work using AI techniques
Lightstone is running other experiments in the AI sphere, including building out their AUR algorithms to provide more intel and insights about buildings, swimming pools and solar investments. This will ultimately create more data for its AiVM to consume or be really useful on its own.
Poorer people dominate Non-Urban areas... other upmarket estates on the upper end
Mining and agriculture underpin Mpumalanga’s economy
Mpumalanga’s economy is built around:
Mining and energy – the province is rich in coal reserves and produces about 80% of the country’s coal, contributes more than 20% to the provincial GDP and employs 7% of working people. 11 of Eskom’s 13 coalfired power stations are in Mpumalanga.
Agriculture and agro-processing – Mpumalanga is a productive agricultural region, with the Lowveld being the second largest producer of citrus fruit and the Highveld producing more than half of South Africa’s bean crop. Around 14% of the area is grazing land used in beef, button, poultry, dairy and wool production.
Forestry – a key economic driver, particularly in rural areas.
Manufacturing and beneficiation – accounts for 15% of the province’s GDP.
Manufacturing and beneficiation – accounts for 15% of the province’s GDP.
Highest volume of formally registered properties in Emalahleni, greater value (and most sales) in Mbombela
The 10 biggest towns in terms of formally registered properties (see graph to right) account for 50% of the province’s properties, and on average towns have less than 5 000 formally registered properties.
In terms of formally registered homes, Emalahleni (a Nguni name meaning place of coal, formerly Witbank), is the largest with 52 000, followed by Middelburg (34 000) and Mbombela (formerly Nelspruit) (19 000). Mbombela, however, has the highest average property values, followed by Secunda, built amongst the province’s coal fields.
Towns with the most formally registered properties
Average property value
More than a quarter (5 000) of Mbombela’s 19 000 properties are valued at more than R2 million, and there are smaller towns which compare favourably – in Hazyview, for example, (see graph Small towns with highest average property values) one out of five properties exceeds R2 million in value.
Small towns with highest average property values
Property sales and mall activity
Mbombela recorded the most sales of properties above R500 000 in value in 2022 – in fact, 6% of stock in Nelspruit, Secunda and White River transacted in 2022, compared to just 2% in Emalahleni, Middelburg and Ermelo.
However, only 7% of the formal deeds-registered properties within Mbombela’s town boundaries are in townships, compared to more than a third in Emahahleni, Middleburg and Ermelo. Bushbuckridge, Nkomazi and City of Mbombela in the north-east of the province account for 44% of all “unhoused households”.
Mbombela’s busy property sales levels are mirrored in shopping mall activity, with an estimated 740 000 customer visits in April 2022, with Nelspruit Crossing attracting 4 700 a day or 141 000 in total.
Emalahleni was next at 540 000 (the Highveld Mall in Emalahleni was the busiest with an estimated 4 800 visitors a day during April, accounting for 144 000 or 37% of mall visitors in the town), followed by Middelburg with 300 000 (Middelburg Mall at 4 400 a day) and Secunda with 260 000 (Secunda Regional Mall at 4 700 a day).
Egoli trumps coal in household income table
As might be expected, Mpumalanga is poorer than western neighbour Gauteng, with 77% of households living on an income of less than R12 000 (compared to 55% in Gauteng).
Mpumalanga has a larger percentage than Gauteng with household income under R12k
Mpumalanga metro municipalities and population numbers
