BTRC to award licence for alternative credit scoring

The Bangladesh Telecom Regulatory Commission (BTRC) is planning to create a new licence category for alternative credit scoring -- the process of assessing someone's creditworthiness using non-traditional data, such as payment history for utilities or mobile phone bills.
BTRC thinks introducing the new category will allow companies to assess the creditworthiness of people who are not well-represented in the formal financial system.
The telecom regulator initiated the move when telecommunication value-added service (TVAS) provider Pioneer People Limited (PPL) applied for licence renewal.
Pioneer People was awarded a licence for assessing alternative credit scoring in 2018 but has not yet begun full-fledged operations.
According to Pioneer People's official document, alternative credit scoring aims to assess credit risk using machine learning and data from various digital platforms and applications, such as airtime usage, mobile banking usage, geolocation, bill payment history and social media usage.
At three commission meetings, BTRC discussed the issue of licence renewal for Pioneer People as a telecom value-added service (TVAS) provider.
The regulator then decided not to renew the TVAS licence, but to create a new licence category for the service.
In the telecom industry, value-added services (VAS) refer to services offered by telecom service providers beyond the core services of SMS, voice and data.
BTRC is not awarding Pioneer People a VAS licence because the service is not intended for individual telecom users, but rather for organisations that provide non-formal financial services.
The regulator has recently sent a letter to the company for submitting a no-objection certificate from the Bangladesh Bank and the Finance Division of the Ministry of Finance.
Pioneer People CEO Mujtaba Sattar Anonto said they are now working to get the approval from the two authorities.
He expressed hope that they would get the licence and that it would be "something revolutionary in the country's alternative credit scoring system which would cover a huge number of the unbanked population".
Mujtaba Sattar said they have long been working on alternative credit scoring using telecom and other mobile financial services.
He said they will use Tiaxa for machine learning and data analysis on certain mobile users to score them.
He also said the service is secure and that user privacy will be cent per cent protected.
Alternative credit scoring is the process of determining a person's creditworthiness using data from non-traditional sources, such as telecom payments and digital footprints, rather than traditional sources like debt repayment history or credit files.
For example, an agency might look at a farmer's recent mobile financial services, mobile recharge amount and frequency and bank account messages on his phone to assess his creditworthiness.
Credit scoring agencies then run this non-traditional data through AI or machine learning algorithms. This produces a score that a bank can use to assess the farmer's creditworthiness.
If the farmer is from the underbanked segment, he may not have any previous credit files to reflect his financial discipline. This can make it difficult for him to enter the credit system.
However, alternative credit scoring could resolve this issue, as non-traditional data is available even for first-time credit applicants.

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