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The new era of data intelligence in credit scoring

Credit scoring solutions have dominated retail banking decision models for decades. In the 1990s and early 2000s when financing was rapidly growing, these credit decision process tools started as basic models with limited data, mainly demographics. Now, credit scoring has become the core decision tools used in the banking industry. However, in an age of data abundance, this is set to change. 

Credit scoring serves two main purposes: fast processing and accuracy.

The last five years has seen an explosion of big data that has provided ground for data scientists to start exploring alternative, non-traditional data to gather insights about peoples’ credit worthiness. This is essential for those with no credit history or even those with limited credit data. This has led to the inception of financial technology firms (fintechs) revolutionising the decision process tools for lenders and banks in their respective countries.

For a bank or a lender, limited, traditional credit data and information on potential borrowers imposes risks on their decision process. To mitigate these risks, a bank or lender can manually collect and assess the available information; however, this is costly. This is where social scoring comes into play.

Social scoring insights through statistically predictive models mitigate both risk and high costs. Social scoring provides comprehensive consumer insights from the plethora of daily data that people leave behind through their digital footprint. This can be used to pre-screen borrowers’ applications or even fast-forward the approval process and thereby create more cost-effective and efficient processes. 

We are seeing more and more lenders, banks and even credit bureaus overseas — such as FICO, CRIF and Experian — adopt or experiment with the use of the social scoring solutions insights to help millions of people enter the mainstream financing ecosystem.

For several lenders that have already adopted social scoring, they have seen their portfolio quality improve by 55 per cent in terms of default rates (bad loans), while simultaneously increasing the number of loans approved by 12 per cent. Social scoring promotes financial inclusion and, consequently, the growth of an economy.

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Social scoring models give great insights on characteristics that are related to the willingness to pay back a loan, such as loyalty, consistency of behaviour, ethical standards and so on. These are important attributes that lenders and banks previously collected and assessed through manual procedures. Nowadays, with millions of metadata that we leave on our daily digital footprint, it takes only minutes for a robust statistical model to come up with insights on someone’s credit worthiness. 

We believe that social scoring, although not adopted yet in Australia by lenders and banks, could in the future support banks and lenders in optimising their credit decision processes. This is why we have bought social scores to Australia. Social scoring can help Australian students or immigrants, with no or limited credit history, to access finance. Social scoring could improve financial inclusion as well as offer more opportunities for growth in Australia.

Bill Kalpouzanis is the co-founder and director of Lodex.

Bill’s career in banking started 20 years ago in Greece and has seen him move through various sectors designing and leading credit risk management systems and digital transformations for global banks.

Something of a finance polymath, he’s absorbed all that he’s learnt in his various executive roles along the way, and it is from this fantastic wealth of knowledge that his brainchild, Lodex, was born. He has a Master’s Degree in European and International Economic Studies, a Bachelor of International Economics and Political Studies (Honours), is a Certified Project Management Professional, Certified Financial Risk Manager (FRM) and Certified Market Maker/Trader by ADEX.

He emigrated to Australia in early 2015 with his wife and two young sons.

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