Analysis of customer data enabled the not-for-profit organisation Moneyline to offer loans to low-income customers, by providing more comprehensive risk assessments than traditional banks.


  • As a result of the Knowledge Transfer Partnership between Moneyline and Salford University, more people than ever before have been able to access affordable loans. These customers would otherwise either not have had access to finance, or would have been forced to borrow from payday lending companies at high cost.
  • Lending by East Lancashire Moneyline IPS Ltd is set to increase by 50 per cent from 2011 to 2012, and their total lending topped £10 million in 2012.
  • Moneyline have also expanded their business geographically, and the collaboration has made it more likely that the company will spread nationally.

"The KTP has helped us gain the confidence to move our business into more geographical areas and, as a result, more people now have access to affordable finance than would previously have been possible." (Diane Burridge, Chief Financial Officer, Moneyline)

About the research

People who claim benefits or live on low incomes often find it hard to get a loan because they are deemed too risky to lend to, do not have a sufficient credit score, and fall outside the lending criteria of high street banks and building societies.

However this has changed after researchers from the University of Salford teamed up with the not-for-profit organisation Moneyline, which provides access to credit, savings and advice for low-income customers.

Moneyline was set up to help people in the area of East Lancashire access small loans without having to use expensive payday loan companies. The company used a relatively simple and informal means of assessing loan applications, operating on a small scale. They realised they could use customer data to learn more about what might predict the risk of lending to certain types of customers.

The company entered an ESRC-funded Knowledge Transfer Partnership (KTP) with researchers from the School of Computing and Science at Salford University, who used a process called data mining to detect patterns in the data. Through this process, the researchers could see that there were certain social and economic factors which wouldn't show up in banks' traditional credit scoring, but which minimized the risk of lending to an individual.

Data mining showed that the risks of lending were actually lower than banks would perceive. This has given Moneyline the confidence to lend in a sensible, ethical way to people who would never otherwise have been given credit. It has also allowed the company to move from an informal means of assessing loan applications to a consistent framework for risk management.