How it Works_ Telco Data Credit Score (1)
How it Works_ Telco Data Credit Score (1)

Telco Data Credit Score in The Philippines: How Does It Work?

Let’s Discuss Traditional Credit Scoring 

To start, it’s only fitting to quickly discuss Traditional Credit Scoring so that readers can have a clear picture of how financial institutions perform credit risk assessment.

Credit scoring bureaus were the main hub of credit information. They investigate the traditional data such as age, homeownership, outstanding loans, repayments of utility bills, source of income, work tenure, work location, and residential address, etc. Credit risk analysts use these pieces of information and historical data to design and train credit scoring models.

Traditional Data Credit Scoring


However, banks and financial institutions can only assess those who have these set of traditional data, which is basically 30% of the adult population in the Philippines. For the remaining 70% unchartered population, we need to leverage other data sources that are as powerful and insightful as traditional data.

This is where we tap into a data source wherein almost each and everyone in the adult population owns: mobile data. This is not an unchartered source though. For FinScore, we have been in the business of predictive data analytics for credit risk management for more than eight (8) years.

Telco Data is the shortened word for Telecommunication data. Also known as mobile network data (MNO), this data category is comprised of texting usage, data usage, voice usage, top-up patterns, SIM age, among others.

Here at FinScore, we use over 400 telco data variables that we are utilizing a highly predictive credit score. Our proprietary, Artificial Intelligence (AI) and machine learning technology developed by our data scientists is the engine that provides the firepower in making these happen. Each credit score pull is being delivered in less than a second.

Telecom Data Credit Scoring

Alternative data credit scoring, specifically Telco Data, has the ability to verify, analyze, and assess the creditworthiness of the credit-invisible customers. The credit-invisible market, also called the unbanked market, is a chunk of the population who does not have any financial history, can leverage if they need to apply for a loan.

In the Philippines, in which our company is headquartered, 70% of the population remains unbanked. Telco data credit scoring can be the solution for banks and financial institutions in the Philippines to finally make the invisible market, visible. Not only visible but also reachable and possibly become viable for future financially inclusive loan products.

Telecom Data Credit Scoring


Before we proceed, please note that the process varies for each financial institution. The scenario that we are sharing is an example.

Telecom Data Credit Score Process

A borrower applies for a loan in a consumer lending company. Then, he provides his consent to allow a third-party credit scoring company to collect and analyze his data for assessment. The lending company then shares the mobile number with the credit scoring company. In FinScore’s case, we ensure that the terms and conditions of our partner financial institutions are amended with a specific consent statement in a way that adheres the Data Privacy Legal Framework in the country.

The lending company makes an “inquiry” to the credit scoring system. With FinScore, a client can access the system via API integration or the FinScore ACE (Alternative Credit Evaluation) web-based Scoring Portal, depending on their requirement. Using the declared mobile number of the borrower, the credit scoring company then pulls Telco data from a partner Telecommunications company. The Telco data will be used for analysis via a scoring system that runs on AI and machine learning algorithms, establishing a profile of the borrower such as willingness and capacity to pay.

Alternative Data Credit Score

To check if the borrower shows an ability and willingness to pay, the system scans through patterns and its consistency over time.  Examples of good behaviors show very stable patterns of the number of SMS sent and calls made per day, and the amount of data usage. As for the borrower’s capacity to pay, the system can look at the top-up patterns such as frequency and amount of top-up.

Each inquiry returns a credit score based on the profile that will be used to help credit risk analysts and loan underwriters to make a well-guided decision.

The entire process happens securely and safely. We have an article on how to comply with data privacy laws in the Philippines for you to check out.

That is how Telco Data Credit Scoring works. Do let us know if you are interested to know more about this topic by sending a question to us. Our team will respond as soon as we can. We would love to answer your questions. Otherwise, you can follow our social media channels such as LinkedInFacebook, and Twitter

For more information and inquiries about alternative data scoring, contact us today.

Download the high-resolution infographic here:

Christo Georgiev, FinScore

Christo Georgiev

Country Manager and Chief Strategic Officer, FinScore

Christo is an experienced digital entrepreneur and operations executive. He has a special affinity towards digital payments, assets and currencies. Prior to joining FinScore, Christo was in charge of operations across several verticals in the i-Gaming industry both in Philippines and internationally.

FinScore is a financial technology company in the Philippines that offers a powerful credit scoring platform and fraud detection tools based on alternative data, including telco-based data. 

As the pioneer in lending and scoring of the unbanked, we continuously provide fintech services that empower financial institutions, banks, and credit bureaus with flexible platforms to help them make insightful and reliable credit decisions. Contact us today to learn more about our products and solutions for financial institutions.