Jul 14, 2022
Banking services have fully adopted digital technology for transfers, payments, and deposits. However, despite the fact that innovation contributes to financial inclusion and allows lenders to discover new opportunities, the credit industry still lags behind.
Loans are a form of financing that allows people to access goods or services that would otherwise be inaccessible to them. Accessing loans through traditional systems often can be tedious, arduous and almost impossible, especially for people outside the financial system.
The traditional credit granting process relies mainly on credit history, that is, information on a person's use of the financial system (like credit card limits, number of credit requests at once, debt repayment history, among others). The problem is that these models are built on data that provides a partial view of an applicant's risk profile, often limited to checking the affordability of a loan amount. As a result, many creditworthy people miss the opportunity to get a loan.
Different global events, such as the pandemic or the current war in Ukraine, have caused a recession in some economies. According to an Investor Guide article, Brazil in 2021 experienced a scenario of inflation and unemployment with household indebtedness reaching record levels in the last 11 years. Likewise, in global terms, the World Bank forecasts that world growth will decrease from 5.7% in 2021 to 2.9 in 2022.
In this context, economies worldwide need to keep credit flowing, especially when inflation is high and money becomes scarce. To ensure that people feel financially secure and included to progress in spite of hardships, it is essential to support and encourage them to do so. However, traditional lenders and banks often lack the technology to onboard new customers quickly and efficiently, leaving many people behind when they need it most.
It is very common to see some people without a credit history (such as informal workers, immigrants or millennials), in a desperate attempt to obtain liquidity, fall into the trap of informal lenders charging very high interest rates and getting disproportionately into debt. In recent years, however, new credit granting processes utilising alternative data, artificial intelligence, and other mechanisms have enabled more and more people to receive credit safely and fairly despite being outside the financial system.
New credit origination systems based on alternative data allow lenders to have a holistic view of their prospects and, therefore, make better decisions in real-time and offer them products and services according to their needs.
Alternative data comes from multiple sources (not just the financial system), such as:
Artificial intelligence algorithms collect and interpret this information, which creates non-linear models that predict human behaviour in different contexts.
According to “The State of Digital Lending”, an ABA (American Bankers Association) and Accenture report, lending is inevitably going digital. Also, the handbook affirms that traditional banks risk losing their competitive advantage if they cannot meet customers with the services they expect wherever they are — and that is everywhere. In this way, alternative credit scoring has become a must for the banking industry, bringing new benefits, such as:
Credolab’s solutions are offered as complementary to other alternative and traditional data scoring solutions that may use other forms of alternative data such as:
However, when it comes to delivering alternative data scoring solutions based on 1st party, non-PII mobile device data, credolab is considered a leader in the field. Credolab AI-based proprietary algorithm analyses over 70,000 data points from smartphone metadata to better credit decisions. Credolab is the only alternative credit scoring company that uses only privacy-consented, permissioned, and anonymised mobile device metadata.
One type of alternative information that credolab collects is behavioural data via a single API. Each user’s behavioural data is unique and does not change significantly over time. This kind of data is the information obtained from mobile apps. For instance, a number of gambling apps installed may indicate the customer is associated with high-risk behaviour and more likely to default.
Lenders could also use behavioural data for marketing insights into how prospects feel about their onboarding process (and find its pain points) or to develop more accurate buyer persona profiles. Therefore, by having a deeper knowledge of their prospects, lenders can improve the customer journey and provide their clients with more attractive offers, improving conversion and loyalty rates.
New alternative scoring loan originations have come to stay. With access to new data sources and technology, lenders can better trust their customers while combating financial exclusion across the globe.
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