From Data to Decisions: Alternative Data Sources supporting SME Lending
From Data to Decisions: Alternative Data Sources supporting SME Lending Small and medium enterprises (SMEs) and microbusinesses are the backbone of many emerging and developing
Credit scores are changing, considering more diverse data than ever before. But while more data can be considered, not all of it should be. Personal information does not need to be shared for an alternative data credit assessment.
Today, financial businesses are incorporating new data sources, such as behavioural analytics or open banking, to build a more complete picture of whom they lend to, WITHOUT the need for personal data.
Alternative data means lenders and financial businesses can say ‘yes’ to more people without needing any personally identifiable information.
At Begini, we can assess anyone, and we are very selective about the data we use. Here are some of the things we won’t use in our assessment.
When we speak about Personal Information in terms of data, we are talking about any information that could be used to identify you directly or indirectly. That might be your name, address, phone number, date of birth, bank account, license, or social security number. It might be your medical information or any type of video or audio recording.
Regulations often refer to this as PII or Personally Identifiable Information. Personal information, or PII, is never considered in our credit assessment.
At Begini, we aim to only take the smallest amount of data necessary to perform the function required. Under the GDPR, there are certain types of data that are classed as “sensitive”.
These include any type of personal data that could indicate a person’s racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or a natural person’s sex life and/or sexual orientation.
Begini will never use sensitive data, as classified by GDPR.
We follow the Equal Credit Opportunity Act. This is a US-based law, established in 1974 which disallowed credit-score systems from using information like sex, race, marital status, national origin and religion within the credit scoring models.
At the heart of our mission is the belief that access to credit is access to opportunity. We are driven by our goal to help build a fairer more inclusive world when it comes to credit. We support the Equal Credit Opportunity Act.
At Begini, we follow the EU’s General Data Protection Regulation (GDPR). The GDPR is the most comprehensive data protection law ever introduced, fundamentally changing the way companies can use the personal data of their customers and prospects.
At present, the GDPR is only legally required by companies that are collecting the personal data of EU citizens or residents. Begini, however, follows GDPR principles in all our countries of operation, and we can meet any specific requirements in other regions as they arise.
We minimise the extent of the data extraction. An important part of GDPR is that companies should only store and process as much data as is required to accomplish a given task.
As a result, when Begini is evaluating a scoring project, we work with clients to minimise the amount of data requested with our Device Data SDK to only the permissions required for building our models and to define retention periods to ensure we comply with GDPR. For our psychometric assessment, we only collect indicators of behaviour, skills and character. We never ask for personal information.
We work at all times with anonymised information to ensure an unrelenting commitment to data privacy.
People are diverse and credit assessment should consider a diversity of data. We consider non-personal, non-traditional data that is predictive of risk.
Character-based scoring leverages behavioural and digital data to better understand people and enable better decisions.
This data can be turned into valuable insights allowing lenders to not only ‘see’ more people but to understand their customers better, providing the foundations to offer better financial outcomes for everyone involved.
Through a psychometric assessment, we can capture multiple personality traits. The most relevant are locus of control, fluid intelligence, impulsiveness, confidence, delayed gratification and conscientiousness. These traits let us identify applicants who are likely to repay their loans.
Not only are these insights predictive of risk, but they have also been shown to be very stable. While an individual’s financial situation might change, their personalities tend to remain stable. —
Another option is to consider device metadata. We can collect privacy-consented metadata from the applicant’s device (iOS or Android). We have built a low-friction, embedded user experience which can be completed in under a minute and results returned in seconds. With a device data assessment, we are not considering personal information on the phone, but the ways in which people use their device, which is predictive of their behaviour and character.
It is not in the best interest of either the lender or the borrower to increase the amount of personal information required in a credit assessment.
Non-personal alternative data allows more people to be considered for credit products that suit them, without increasing the personal data risk for either party.
The democratisation of data means that individuals should be in control of how and when they want to use their data to access the services that are important to them. Non-personal alternative data gives them another option to create or share data that can be useful to access credit, without risking their identity.
There is power in data. And there is more data available than ever before. For both lenders and borrowers, it has never been more important to consider if you are using the best data for the task at hand.
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