It was announced earlier this week that the Hong Kong Monetary Authority (HKMA) is looking to bring lending into the digital age - banks will be allowed to forgo traditional credit checks on some personal loans in favour of big data analysis.

It makes sense that risk assessment should make a move in this direction. We don’t shop, travel, listen to music, or even date, based on the same information that we used to, so why should banks rely on impersonal credit checks when deciding whether or not to approve a customer for a loan? Of course, a bank’s decision to lend is a commercial one, but in a world where our digital footprints extend far beyond our number of steps per day, there must be a smarter way to assess this risk.

Enter algorithmic credit scoring. Behind a scientific sounding name, lies the potential for greater financial inclusion, and – FinTech’s headline act -  serving the needs of consumers who have largely gone unnoticed or ignored by mainstream financial providers. 

The power of financial technology doesn’t lie in digitising and streamlining the existing process, but the creativity to style new frameworks, unlock new norms, and re-imagine how we approach whole concepts and audiences.

Through this lense, big data scoring has big potential.