What came first: the chicken or the egg? The same problem is also applicable to credit. This is because if you do not have a credit history, it is almost impossible to get access to credit. Then you might ask yourself, how does one become eligible to get access to credit and financial products without a credit history? This question has challenged the world of finance for years and hindered a majority of credit products from becoming accessible to the underbanked population.
The traditional way to determine someone’s creditworthiness is often by evaluating their credit history. This method is simply not a viable option for the underbanked. Therefore, there is a need for different data sources, such as behavioural attributes, to fuel the AI-powered alternative credit scoring model. This model would rely on factors that are available for everyone and are easily traceable, with the data coming from social media, smartphone application data, monthly utility bills, etc. In time, this approach will turn the underbanked client profiles from thin to thick, and eventually converting them into becoming regular clients with financial institutions.
However, the ability to build a comprehensive portrait based on alternative data requires access to sensitive personal data. In the current dominant user-data ownership model, the data rights are transferred through the service agreements to the service provider collecting the data, which raises multiple data privacy concerns.
To address data ownership and privacy problem, we need to create a different data governance model that can protect user data rights. This is where blockchain plays a part. One use-case of blockchain is to restore control over the user’s data to the user, simultaneously empowering them to a refined data literacy knowledge. This would enable them to determine how their data is being used, the purposes of the usage, and the accessibility to their data.
In conclusion, AI-powered alternative credit scoring is fast becoming the solution for financial inclusion, with blockchain providing assistance to address data privacy and ownership concerns. When combined, these two technologies have the power to shape the future of finance and make access to credit widely accessible for not just the underbanked population, but also a wider hit on multiple groups of target audiences.
Interested to know more on how to transform your businesses using AI-powered tools? Reach out to us to know more about Juris Mindcraft and Juris Score at email@example.com.
JurisTech is a leading Malaysian-based fintech company, specialising in enterprise-class software solutions for banks, financial institutions, and telecommunications companies in Malaysia, Southeast Asia, and beyond.
Juris Mindcraft: Effortless AI for Intelligent Business Decisions
Juris Mindcraft uses advanced machine learning techniques to learn from historical data and recognise patterns to build powerful predictive and prescriptive AI models. Taking into account non-traditional data sources. Juris Mindcraft has adapted its scoring model to target the unbanked. A great solution for alternative credit scoring to assess customer’s creditworthiness more accurately.
JurisTech’s very own financial scoring software solution that can assess customers’s creditworthiness, and provide recommendations based on results. Read more here.