‍The financial world has a great ally that provides the ability to adapt and continue growing. We are talking about alternative data. For the past ten years, financial companies have been looking for reliable data sources to provide information about consumers and their behaviours. The constant change in this digital world brings forth a great advantage for the financial sector that was not formally registered before: the analysis of people’s digital behaviour.

Alternative data is a reliable source of information on current and ever-changing consumer habits. But, what are they? They are the set of information on behaviours, habits, interests and transactions carried out by a person and obtained from non-traditional sources. All data comes from sources such as social networks, data obtained from satellites, sensors, credit card transactions, and purchase receipts stored in emails, among other sources.

The conjunction of alternative data sources and traditional sources has achieved a perfect optimisation of results that traditional data by itself could not have reached. Among the traditional sources, we find that sources like SEC filings and customer credit scores, even though they add great value to the market, cannot provide or anticipate users’ future behaviour patterns. The combination of both types of data provides companies to anticipate users and technology changes.

The growth of alternative data is exponential, and this is powered by the fact that more and more users are storing information on the network, generating new data every day. Access to this data has become easier, while machine learning devices have allowed science to advance at large scales.

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Its importance in the financial sector in 2021 & beyond

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Alternative data sources have allowed many industries to reinvent themselves, and the financial industry is one of the most benefited. However, traditional data sources do not open their doors to a big segment of the population excluded from the financial system. Thanks to this complementary information obtained from the rigorous analysis of behavioural patterns, it is possible to identify potential clients who do not yet have a formal or traditional credit record or history.

Alternative data provides the financial industry with the necessary information to detect new segments of clients and convert them into customers. This new scenario is a perfect guarantee of projection and growth. At credolab, we use the metadata and alternative data obtained from smartphones to analyse the behavioural patterns of unbanked users that could be potential clients for financial companies. How do we do this? Through alternative scoring with artificial intelligence or alternative credit scoring. Through our credit app, we evaluate the behavioural patterns of users, observing and analysing the alternative data of the unbanked to assess whether or not they are reliable.

Thanks to the analysis of this alternative data, it is possible to create a new type of credit scoring: a reliable credit history on the behaviour of users. In turn, as new patterns of behaviour are registered, new portfolios of clients arise, ready to enter the financial world. Thanks to the alternative scoring and artificial intelligence, financial companies and banks can now access all the required information to analyse potential customers reducing financial risk and helping them make safer and less risky decisions.