# Quantifying how predictive software reduces evictions for social landlords

> A provider of arrears-management software to social landlords · Public Sector

An independent large-scale study measured how rent-arrears prediction software affects evictions and arrears across the social-housing sector, evidencing a 37.8 per cent fall in evictions.

## At a glance

- **37.8%** reduction in evictions due to arrears over three years

## What was the problem?

A provider of rent-arrears management software for social landlords needed robust, independent evidence of its product's impact. Social landlords face rising arrears and welfare-reform pressures, and the provider wanted to establish, at scale, whether its software genuinely reduced evictions, arrears and the number of tenants in debt.

## What did QuantSpark do?

QuantSpark carried out what is believed to be the most extensive quantitative study of its kind, examining more than 1.1 million social tenancies managed with the software against over 2 million tenancies managed without it. Using a multi-year comparison from 2015 to 2018, the analysis isolated the software's effect on evictions due to arrears, on total and non-Universal-Credit arrears, and on the number of tenants in debt.

## What changed?

Landlords using the software reduced evictions due to arrears by 37.8 per cent over three years, against 13.3 per cent for non-users. Non-Universal-Credit arrears fell by 1.6 percentage points over 24 months, a 29.6 per cent reduction worth about £600,000 per 10,000 properties over two years, while the number of tenants in arrears fell by roughly 11.5 per cent before stabilising. The study gave the provider independent, sector-wide evidence of its product's value.

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