By Joe Bowerbank, Senior Business Development Manager, Creditinfo
Over 2 billion people have limited or no access to financial services. Though this figure is slowly decreasing year on year, the barrier to entry is kept high by the fact that most financial institutions around the world will only take into account data from ‘traditional’ data sources – such as utility bills or credit card statements – when considering applicants. Yet many people have no bank accounts and so little or no credit history to their name, especially those living and working in less economically developed or emerging markets.
Without the relevant data, financial institutions cannot perform the necessary due diligence on potential customers. This leaves many – even responsible, creditworthy people – severely restricted.
Financial inclusion is goal number seven of the United Nation’s sustainable development goals. It is crucial to improving quality of life, helps to create a more stable and sustainable financial system and supports the alleviation of poverty. Nevertheless, the global potential banked population is still being underserved.
Tapping into the banking insights of the unbanked
How do financial institutions calculate risk among the billions of people who have never had a bank account or opened a credit line? It’s a tricky question to answer.
The good news is that there is an abundance of alternative data than can be leveraged to assess the creditworthiness of individuals and organisations. For example, although only 34.5% of the population of the Philippines have a bank account, there are 1.59 mobile phones for every person in the country. The majority of those will be on a prepaid plan.
Data around people’s payments for mobile phone plans, other fintech apps, and even social media use, can be used to develop market level credit risk scores to offer companies and individuals who don’t have bank accounts a route in. Additionally, bringing alternative data into the process can funnel liquidity into emerging markets and encourage a healthier financial ecosystem.
However, the problem is that it’s not just a question of there being too little data on hand. Banks know this information is out there, but often lack the capability to collect and interpret the data. They need the tools to make an informed lending decision and extend financial services to the unbanked.
The abundance of alternative data that we know is out there needs to be shared with the right parties, along with the tools to analyse it, otherwise the data becomes all but redundant.
A real-world example: facilitating housing finance loans in Pakistan
In Pakistan, the number of housing finance loans that have been granted is insignificant compared to the size of the country’s population. While 10 million citizens have access to formal credit, around 105 million over the age of eighteen do not. With little credit history data to go off, banks are left unable to increase the number of loans they’re offering.
The traditional system just doesn’t work for Pakistan’s citizens right now, leaving them without means to access housing loans, while at the same time stifling the country’s economic growth.
As we inch towards a global recession, financial issues that are having such a significant impact on the economy are rightfully top of mind for the government in Pakistan. As a result, it has backed an initiative to bring more liquidity into the market.
Set up in 2021 by Pakistan Banks’ Association (PBA), the initiative works to combine traditional data sources such as credit bureau data and internal banking data with alternative sources such as mobile phone metadata in order to widen the pool of potential applicants for housing financial loans.
Importance of data accessibility for Pakistan’s financial institutions
The success of the initiative hinges not just on the data itself, but on having two things: a bridge between the alternative data and all the different financial institutions – from credit bureaus to banks –, and the tools to leverage this data, allowing them to overlay best lending practice on top of the data to make correct decisions.
This is where Creditinfo stepped in. The PBA looked to the credit bureau and financial data expert to lead the consortium of parties – including credit bureaus and ratings agencies – in Pakistan towards this goal. Creditinfo acted as the bridge between organisations and the data, helping them to access and analyse it. The co-operation has led to the development of a market-level application scorecard and income estimation model, which have acted to increase the percentage of the population that has a data footprint capable of informing robust credit risk decisions.
The first project of its kind in the country, it has therefore enabled financial services to provide loans to more of the population, especially those in low-income segments previously excluded from traditional housing finance.
The project will go on to support the Naya Pakistan Housing Programme (NPHP), a government-backed initiative providing low-cost, affordable housing to deserving individuals in Pakistan that is expected to be a catalyst to accelerated economic activity and increased job opportunities in the region following the negative impact of Covid-19.
