Crunching numbers securely: the role of fully homomorphic encryption in credit scoring

• Credit scoring has not traditionally been a very data-secure process.
• Increasingly, regulators are demanding data privacy.
• Fully Homomorphic Encryption could deliver data privacy to credit scoring.

Credit scoring is a process most people and businesses think they understand. It’s the assessment of financial risk we place on individuals and enterprises, based on which financial institutions will lend or not lend. Credit scoring determines what flexibility you’re given to raise funds, and so it can be the make-or-break factor in business success.

Add to that the fact that in the modern world, financial data, which is vital for companies and whole economies around the world, has to be treated sensitively and kept securely, and you have a technological and ethical dilemma, with banks and institutions facing growing demands and regulations in relation to credit management. That adds a fresh level of responsibility that financial organisations have to meet.

The European Central Bank ECB recently conducted an in-depth analysis of the credit risk landscape. It discovered that nearly 20% of identified deficiencies or problems in the banking sector were related to credit risks, while 44% of these deficiencies were connected to flaws in the credit risk management frameworks of banks.

That translates into one crucial fact: banks have not been effectively managing the risks associated with their lending.

Fully homomorphic encryption and credit scoring

The analysis also found that another 10% of the issues were related to how banks classified loans and the provisions they made for potential losses. One-third of the deficiencies were linked to non-performing exposures (NPEs), suggesting that a significant portion of loans were not performing as expected.

This is where fully homomorphic encryption (FHE) comes in.

The technology, which is based in cryptography, is a potential game changer in the field of credit scoring. It can be implemented to develop platforms, allowing secure communication. It can perform computations on encrypted data without needing to decrypt anything. That means it can underpin secure messaging, secure emails, secure file sharing, and secure, accurate data encryption. As such, it’s a fundamental privacy enhancing technology (PET).

This crypto-technology can be hugely beneficial for lenders as it can allow them to establish credit scores from an applicant’s data without having any actual access to decrypt the data. That means it can deliver insights on the data without ever exposing sensitive personal information to privacy risks during the credit scoring process.

Privacy considerations and regulatory changes

Regulators are placing greater and greater emphasis on safeguarding the privacy of consumers. Currently, the credit scoring method is not ideal from a privacy perspective, as it often involves sharing personal data with lenders. Nevertheless, this has become an accepted and necessary approach to facilitate access to credit – a kind of ‘known issue’ that had to be swallowed if the traditional credit scoring system was to work at all.

That may be about to change, though. As technologies like FHE become more mature, regulators are indicating that they may strengthen privacy rules, resulting in stricter regulations that protect the privacy of an individuals’ financial data.

FHE shows promise in significantly improving privacy in the everyday business of credit scoring. Especially when credit scoring can largely be done by machine-to-machine interaction without overt human scrutiny of the data (including its private elements), FHE can enhance both privacy and security.

That can make the credit assessment process more effective, reducing the risk of data breaches, mitigating insider threats, and enhancing consumer trust.