In this article by Dmitry Borodin , Head of Decision Analytics at Creditinfo , we dive into how financial inclusion can enhance lives of underserved communities through alternative data solutions .

This limited access to financial products and loans can have a significant impact on an individual ’ s lives . They may find themselves unable to raise capital to finance a small business or without sufficient financial records to rent or buy a property , exacerbating existing societal inequalities that these segments of society already face .

The onus lies with financial institutions , governments , credit bureaus and regulators to collaborate and address these issues to narrow the lending gap . Collaboration can also be supported by using data-driven solutions , which are beginning to play a key role in facilitating access to finance for underserved groups . As emerging economies continue to utilise mobile banking , and alternative forms of lending such as micro and mobile loans , more and more forms of alternative data will be released which can be used to assess formal loan eligibility through the use of unbiased predictive models .

What are the barriers to financial inclusion ?

For younger people and women , systematic issues are often faced when trying to access formal loans including pre-existing bias in financial institutions ’ assessment processes and a lack of formal credit data to support loan requests . Combined with broader societal prejudices and discrimination , this phenomenon is exacerbated . While credit scores continue to be established from data derived from regular consumer bank transactions or prior payment records , the underserved will continue to face the same barriers when it comes to accessing formal loans .

We see this phenomenon occurring more in emerging economies . In Africa , for example , 57 % of citizens have difficulty obtaining the data that will form a conventional credit score . Women are also more likely to face social barriers which originate from pre-existing prejudices . So , without the right data to hand , women face an additional layer of obstacles than their male counterparts .

Harnessing alternative data

With a large increase in the use of alternative lending channels in recent years , a wealth of data is being unlocked for unbanked consumers . In countries such as Kenya , for example , mobile lending represents a very high proportion of lending data , with approximately 25 % of 20 to 24 year olds recently receiving loans of less than US $ 200 . Mobile loans are similarly popular in other markets and are beginning to incorporate data from www . intelligentfin . tech

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