Financiera Efectiva increases credit access by 8% with AI — resulting in millions of dollars in new loans
A new era: finance AI for decision making
In 15 years at Financiera Efectiva, Juan Cotrina has helped bring analytics to the forefront of the company’s strategy, influencing sales, collections, lending, risk, and operational efficiency.
Now, he’s more energized than ever as they embark on the next phase: AI-driven decision-making.
“We reduced model lifecycle time by 4x. DataRobot can build a model in a single day.”
In 15 years at Financiera Efectiva, Juan Cotrina has helped bring analytics to the forefront of the company’s strategy, influencing sales, collections, lending, risk, and operational efficiency.
“We’re transforming into an AI department,” said Cotrina, Analytics and Artificial Intelligence Manager at the leading Peruvian financial institution. “I’m excited to use AI to improve efficiency, cut costs, increase credit access, and elevate experiences — with more automation, better customer support, and productivity tools for our store reps nationwide.”
Financiera Efectiva offers financing for appliances, motorcycles, cash loans, mortgages, and small businesses across 200 offices, plus retail banking services such as savings accounts and digital debit cards. Cotrina sees AI as integral to scaling smartly.
“Everything goes back to the customer experience,” he said. “AI will help us better compete in the industry.”
Faster models with AI automation
The team recognized, however, that their existing predictive analytics software lacked the advanced algorithms needed to meet their goals at scale. Nor did it provide essential governance, model control, and documentation for the regulated industry.
“AI is a productivity copilot. Now everyone uses it daily — not just to build models, but to detect risk patterns, create strategies, and run campaigns.”
DataRobot hit all those marks in an easy-to-use platform. Plus, a quick demo on one of the company’s top use cases sealed the decision.
“DataRobot was very different from other companies. They surprised us by saying, ‘Let’s build the use case – live,’” Cotrina said. “That experience gave me confidence not just in the technology but also in the people at DataRobot.”
As the company on-ramped with DataRobot, they linked the platform with their cloud provider, Amazon Web Services. They easily import large datasets with hundreds of millions of records and thousands of columns. DataRobot enhances data quality by detecting nulls, missing values, and outliers and automatically treating them according to best practices.
The DataRobot team also helped overcome a hurdle in implementation: adding an Active Directory to enable user access in a way that met Peru’s legal requirements.
While the Financiera Efectiva data science team was initially concerned about AI automation, they soon saw DataRobot as a way to increase throughput and deliver more valuable AI projects to the business.
“AI is a force multiplier,” Cotrina said. “Now everyone uses it daily — not just to build models, but to detect risk patterns, create strategies, and run campaigns.”
AI automation = 4x faster modeling
The initial move to DataRobot went smoothly — bringing peace of mind.
“We switched our models to DataRobot with a big bang and it was a very successful transition,” Cotrina said. “It was a risky change, but it’s gone well. Loan delinquency and sales are in good shape.”
Since then, DataRobot has become the company’s primary platform for building advanced finance AI models. Every day, it handles tens of thousands of transactions, assigning credit scores and running pre-approved loan campaigns. The results have exceeded expectations:
“With our old platform, we wouldn’t have made regulatory deadlines. Thanks to DataRobot, we were able to adjust all our models within a year — instead of four to five years.”
Improved Field Engineer Efficiency: The Noritz Diagnostics AI Assistant application allows engineers of all experience levels to perform optimally, fostering a more confident and capable workforce.
- 8% increase in credit access – Representing millions of dollars in new loans, expanding into higher-ticket segments.
- 18 models in one year – With its previous platform, it would have taken four to five years to deploy that volume. The winners emerged after comparing hundreds of champion-challenger models.
- 3,000 features – They train models on more than 3,000 features, up from 800 before.
- Documentation 4-5 months faster – To meet banking industry regulations, they generated 3,000 report pages with DataRobot automating 50% of it.
- A 10-point performance gain – They improved model performance by an average of 10 points based on GINI scoring (a way of evaluating performance in predictive models).
AI governance in finance
The company also sharpens its ongoing compliance and governance efforts. They standardize technical documentation, enabling consistency and speed.
Such speed was critical when the Peruvian Superintendent of Banking issued a new regulation on model risk management for the entire financial and insurance industry. DataRobot automated many of the steps for the team, empowering them to finish faster and without significant additions to the team.
“With our old platform, we wouldn’t have made regulatory deadlines,” Cotrina said. “Thanks to DataRobot, we were able to adjust all our models within a year — instead of four to five years.”
Additionally, they gain explainability and transparency, enabling them to answer why clients were scored a certain way and help prevent bias.
“With DataRobot, you can zoom in and see the parameters and logic used. It even links to documentation,” Cotrina said. “It’s not a black box generating a score.”
AI for competitive advantage
Next up, Financiera Efectiva is creating a new access model for unbanked clients that uses alternative data and an AI credit evaluator that assigns a score and recommends loan conditions.
“DataRobot will be our core intelligence engine. It’s like having dozens of analysts building models at the same time.”
Cotrina couldn’t be more optimistic about the team’s ability to support companywide decisions through the next phase. AI has become an indispensable part of their predictive analytics, and increasingly, they’re exploring generative AI and agentic AI to personalize and elevate customer experiences.
“DataRobot will be our core intelligence engine,” Cotrina added. “It’s like having dozens of analysts building models at the same time. It helps us position ourselves better in the market when issuing debt or seeking capital. It also gives shareholders and the board confidence that we have a world-class platform.”
