GUEST BLOG

Despite the gradual recovery of society from the COVID-19 pandemic thanks to vaccinations, the digital means to make lending transactions are here to stay.  It is safe, efficient, and convenient for both your customers and your lending business. The pandemic has acted as a catalyst for lenders to rapidly adopt digital technologies and stay competitive in this changing environment. Upgrading digital infrastructure introduces fundamental changes that can create more economic opportunities.

However, more digital technologies not only reel in more opportunities but also disadvantages. When it comes to future-proofing your financial services company, aim to grow by expanding your market reach while ensuring profitability by detecting fraudulent individuals who are more likely to default on their loans.

To achieve both, you can rely on alternative data credit scoring.

Alternative data credit scoring is the umbrella term for credit scoring using non-traditional data sources and methods.

In traditional credit scoring, lenders manage their risk and reduction of bad loans by relying on credit bureaus that provide credit information on the consumers. They can learn if the loan applicant has been paying off loans on time, has ongoing loans, or has been blacklisted for not paying at all. But this only works for those who have a loan history. Besides this, they assess the socio-demographic profile of the borrower which can be found on the loan application form either in pen-and-paper or digital form. The lender may also use a credit scorecard, a type of credit model, that outputs a score predicting the probability that the borrower can repay the loan on time. With Alternative Credit Scoring, alternative data sources such as mobile usage, digital wallet usage, bill payment history, social media behavior, geolocation, and more can be aggregated to produce a credit score.

The mobile phone has become a physical extension of a 21st-century human. Whatever model, size, or function it may have, each mobile phone owner has a SIM card so he or she can connect with the rest of the world. They use it to make phone calls, send messages, access a wide array of mobile applications — from social media to digital banking. As time passes, a user creates his or her mobile footprint such as, but not limited to, texting usage, data usage, voice usage, top-up patterns, SIM age, and more. These are telco data that is unique to each user. 

Alternative data credit scoring, specifically telco data, can help verify, analyze, and assess the creditworthiness of the credit-invisible applicant. The credit-invisible market, also called the unbanked market, is a portion of the population who does not have any financial history they 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 viable for future financially inclusive loan products.

Now that you have the confidence to serve larger volumes of customers, it is also important to add a fast and powerful way to extend credit to real customers. Fraudulent activities do not sleep. In fact, synthetic identities, bot attacks, and fraud attacks are more present in digital channels.

This is where Social Media Presence Data, which is another type of alternative data analytics, comes in.

Social media presence data is derived from public databases, which are near-real-time data. You can confirm an applicant’s identity with an e-mail address and/or mobile number. FindSocial, a fraud prevention tool, for example, can check more than 20 social media platforms, showing a user avatar and profile information in a simple interface. FindSocial also produces a Social Presence Score that can help you determine whether the customer’s social presence can be trusted or not.

Banks and financial institutions of any size are increasingly having positive perceptions towards Alternative Data Credit Scoring because not only can it increase their profitability but also reduce costs due to its speed and efficiency.

The COVID-19 pandemic has further pushed such businesses to transform the way they assess borrowers’ creditworthiness. Besides making their digital banking and/or lending mobile application available to the masses, the lending process, especially loan underwriting and disbursement needs to be fast, easy, and secure to keep up with the demand of the market and to stay ahead of their competitors.

Alternative data scoring provides borrowers with better, easier access to credit. If they apply for a loan from a lender that uses this particular type of credit scoring method, there is a higher probability they will qualify for credit applying for a loan with an establishment relying on traditional methods alone.

• Going digital can help financial institutions reach larger markets to serve. However, it can also attract fraudulent individuals.
• By leveraging alternative data in your analytics efforts, you can reach the large group of unbanked and underbanked individuals and prevent fake accounts from exploiting digital loopholes.
• Telco data is a type of alternative data that can determine the financial power and creditworthiness of a borrower using data variables such as SMS and call usage, top-up amounts and patterns, SIM age, and more.
• Social media presence data is a type of alternative data that enables fraud prevention and faster identity reviews.
• By using an advanced analytics platform, you can instantly confirm if an applicant’s declared e-mail address and mobile number are registered on more than 20 social media platforms.

Learn more on the Marketplace.

BLOG

As a digital transformation evangelist with years of experience in the financial and banking industry, I have helped many Fortune 500 clients future-proof their lending programs by providing intelligent solutions, especially in the decision risk management area. Through these engagements, I’ve observed that many lenders compromise their agility in rolling out a decisioning solution due to delays and challenges in the initial steps of evaluating and onboarding the right data sources. Customer needs and expectations are changing in real-time so lenders must eliminate barriers to their own agility to stay in the game. 

Below are few activities I’ve observed that compromise lenders’ agility: 

• Choosing the Right Data Provider: Considering there are thousands of data providers across many lines of businesses, lenders always have to spend a lot of time choosing the right data provider for their decision strategy. Lenders must evaluate each data provider in each region by the line of business, review their doc specs, figure out ways to test their API in their decision solution, and then, based on the outcome, initiate the onboarding discussion. These activities often significantly delay the implementation of a risk decision solution and ultimately, delay better outcomes for the end customer. 
• Onboarding Data Providers: Onboarding a data provider involves a series of discussions around pricing, legal contracts, support, etc., and again becomes a bottleneck in the lender’s agility to roll out products to end customers.
• Switching Data Providers: Considering the effort required to onboard a data provider, lenders often default to their existing data provider and keep using the same data for their new risk decision solution or product. It’s like building a new car with an old engine designed for a different model.  They should put a mechanism in place to easily choose and switch to the data providers that best augment the overall risk decision solution.
• Keeping Pace Data Sources: As data types are exponentially growing, data providers are offering new data sources, and it is hard for lenders to keep pace with who has what data. Most of the time, lenders default to using the same data type even if there are alternative data products in the market that offer new, more relevant, and deeper insights.

These activities are repeated for each data source and, on average, add a week to a month to making the data available for building a risk decision strategy around it.

To create true agility in launching a risk decisioning platform, lenders need a one-stop hub that offers easy access to a variety of data types so they can evaluate, integrate and easily build decision models around it instead of waiting for months. And having the right data source is as important as having a robust, agile risk decisioning platform.

The Provenir Data Cloud + Provenir Marketplace provides a wide variety of data sources in the lending ecosystem, along with advanced search capability to discover and detect trusted data sources based on geographic location, data type, product type, etc. It’s out of the box, prebuilt API provides seamless integration with available data sources such as credit bureaus, identification and fraud, collateral, alterative credit data, etc. 

The combination of discovering the right data sources and using an out of box prebuilt API allows the lender to quickly switch between different data providers. With a simple click of the button, they can integrate new data sources into their decision strategy seamlessly without having direct contact with the data provider. The lender can test the respective data and enable it for the end customer on the fly once satisfied with the desired test outcome.

Provenir Data Cloud + Marketplace helps lenders be more agile, responding quickly to changing data needs and focusing their time and energy on innovating their financial product.