“This way, it is possible to prepare simplified and accurate credit analyses, reduce risks and costs…”
Aline Oliveira Pezente is a co-founder and the CPO of Traive, a financial infrastructure company for agriculture, which operates with proprietary Artificial Intelligence.
Pezente has a M.Sc. in technology and certifications and in data analysis from MIT.
Aline Pezente, co-founder and CPO of Traive
AgriBrasilis – How can AI contribute to agribusiness?
Aline Pezente – Artificial Intelligence (AI) can significantly transform agribusiness. From AI-equipped satellite and drone solutions that allow real-time monitoring of crops to much more accurate and faster credit risk analysis. Traive does this while fully connecting the flow of credit and receivables from the reseller/dealer or distributor of inputs, which generates governance, agility, and security for businesses.
We have identified a need for data refinement and analysis of variables during the agricultural credit approval process. With this in mind, we have developed a proprietary AI that connects on the same platform the two ends of the agricultural credit granting process: the capital market and the agricultural supply chain. This makes it possible to prepare simplified and accurate credit analyses, reduce risks and costs, and leverage financial returns.
“Agribusiness is, undoubtedly, one of the most complex segments to model and assess risk”
AgriBrasilis – The term “artificial intelligence” is often used incorrectly. What actually defines an AI?
Aline Pezente – It refers to the scientific area of Computer Science dedicated to creating systems that can perform tasks that would normally require human intelligence, such as writing and calculating, for example. AI can range from simple systems capable of performing specific tasks to complex systems capable of making autonomous decisions.
AgriBrasilis – How is it possible to associate rural credit analysis and artificial intelligence?
Aline Pezente – Rural credit analysis is enhanced by AI through the reading and segmentation of various data sources, which generate more complete and accurate assessments of credit risk.
Traive’s technology stands out by combining human knowledge – from credit analysts – with a powerful AI. This AI considers a complex probabilistic model, being able to deal with uncertainties and incomplete information, precisely the main challenges faced by the agricultural sector and its extensive data diversity.
AgriBrasilis – What factors are evaluated during credit risk analysis?
Aline Pezente – Agribusiness is, undoubtedly, one of the most complex segments to model and to assess risk. Therefore, our methodology efficiently analyzes a range of data, including climate information, soil types and cultivation practices, as well as economic variables such as commodity prices, logistics, supply and demand, and interest rates, etc.
AgriBrasilis – Is credit analysis more efficient when carried out with AI support?
Aline Pezente – Yes. In fact, when tested, reports generated by Traive’s AI were considered, in 90.2% of cases, as good as or better than those produced by credit analysts, and both the materials created by AI and those written by human credit analysts were evaluated by a group of decision-makers who did not know which had produced each content. The results obtained were endorsed by the global scientific community (ACM).
AgriBrasilis – The company is starting an internationalization process. To which countries? What investments will it make in the short and medium term?
Aline Pezente – Just like in Brazil, there are many opportunities to transform agribusiness in Mexico through technology, which is why we are beginning our internationalization through a strategic partnership with Verqor, the largest agfintech in the country. The collaboration will allow Verqor to use Artificial Intelligence to support Mexican farmers, offering faster credit approvals and data-driven decisions. The deal seals the commitment to innovate and revolutionize agribusiness, providing solutions that increasingly drive business.
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