No credit? No problem.

Dollarito expands credit access for low-score communities with a solution built on IBM Cloud

Two businesspeople looking at computer tablet
Pushing back on exclusionary credit scoring models

Dollarito is a digital lending platform focused on helping individuals with no credit history or low credit scores access transparent, responsible and reasonably priced loans—empowering them to build credit and improve their financial future.

In the United States, millions of people with low or no credit are excluded from the exact financial opportunities that allow them to improve their credit. Dollarito sought to help their clients circumvent this paradox by addressing the limitations of traditional credit scoring models. The company wanted to facilitate a more accurate evaluation of a person’s repayment capabilities based on their banking transactions, behavioral data and economic factors. However, Dollarito lacked a scalable, secure and compliant technology foundation, which was fundamental to achieving their objective.

Enter the IBM Cloud® platform.

60% Increase in speed for loan approvals and passing regulator audits 40% Cost reduction due to automation in loan disbursement and collection process In just a few minutes Loan approval and money distribution for clients
We discovered that IBM has the best technology to speed up our development process. We decided to deploy all our operations with the help of IBM and leverage the infrastructure for the IBM Cloud for Financial Services.
Carmen Roman Co-founder and CEO Dollarito
Scaling inclusive lending with AI and IBM Cloud

After evaluating their business needs and technology options, Dollarito reached out to IBM to create a web solution with a secured, compliant and scalable infrastructure. This solution needed to be fully tailored to their mission of serving communities with limited access to credit.

IBM’s web solution combined infrastructure optimization and regulatory compliance, powered by IBM Cloud for Financial Services®, with advanced AI capabilities from the IBM watsonx® portfolio of products. This combination enabled smarter strategy and operations through generative AI and foundation models.

With fully containerized operations and a data mesh strategy, featuring strict audit trails and access controls, the solution also enabled Dollarito to focus on innovation while maintaining trust and transparency.

IBM has helped Dollarito kick off its cloud and machine learning operations. Dollarito uses IBM Cloud for Financial Services technologies to optimize infrastructure and demonstrate compliance, enabling us to focus on our mission of providing financial services to communities with limited access to credit due to low scores.
Eduardo Perez Co-Founder and CTO Dollarito
Redefining what fair and affordable credit means

Through their new AI-powered credit evaluation model, Dollarito has achieved results, such as:

  • 60% faster loan approvals and regulatory audits
  • 40% lower costs through automation in loan disbursement and collection
  • Fund distribution times reduced to just a few minutes

By moving beyond traditional credit scoring, Dollarito empowers clients to resolve urgent financial needs quickly and safely. The partnership with IBM has strengthened Dollarito’s position as a leader in inclusive fintech innovation. As they continue to grow, they intend to continue collaborating with IBM teams to develop new use cases and adopt advanced technologies that build on their existing infrastructure.

About Dollarito

Dollarito is a digital lending platform that helps communities with no credit history or low FICO scores to access transparent, responsible and reasonably priced loans. Dollarito applies AI to banking, transactional and behavioral data to evaluate the repayment capability more accurately than FICO scores.

Solution components IBM Cloud® IBM Cloud for Financial Services® IBM watsonx®
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Examples presented as illustrative only. Actual results will vary based on client configurations and conditions and, therefore, generally expected results cannot be provided.