Skip to content

AI for credit cooperatives in Ecuador

Grow across channels while staying close to members.

In short

What can artificial intelligence do for a credit cooperative?

A cooperative competes on closeness to its members. Certia helps it grow without losing that: fast origination at branches and on digital channels, collections that protect the relationship, identity controls and dashboards the board understands, with processes aligned to SEPS supervision.

What weighs most

  • Portfolio in rural and urban areas
  • Small teams with a heavy load
  • Early delinquency that grows quietly
  • Digital channels still in progress

Terms worth knowing

Alternative credit scoring
Alternative credit scoring is a model that estimates credit risk with data beyond the credit bureau history, such as utility payments, phone top-ups, account activity or the use of digital channels. It helps assess people with a thin credit file. In Ecuador, each data source needs a valid legal basis under the LOPDP.
Credit origination
Credit origination is the process that runs from a loan application to its approval and disbursement. It covers data capture, identity validation, repayment capacity analysis, the decision and the signing. When every step is recorded, the institution can answer the applicant faster without losing control over risk.
Credit pre-assessment
Credit pre-assessment is the first review of an application: it organizes the information, checks documents and flags inconsistencies before an analyst decides. With AI support, the system assembles the file and proposes a reading of the case, while approval stays with a person in the risk area or on the credit committee.
Early delinquency
Early delinquency is the delay in the first days after a due date, when the installment can still be settled with a reminder or a simple arrangement. Handling it in time keeps the obligation from aging until it becomes past-due portfolio, and it usually costs less than recovering it later.
Portfolio segmentation
Portfolio segmentation is the grouping of loans or customers by days past due, amount, product, payment history and preferred contact channel. It lets you give each group its own collection strategy, with messages, timing and escalation levels that fit its risk and its relationship with the institution.
Probability of payment
Probability of payment is an estimate, based on historical and behavioral data, that a customer will meet an obligation within a given period. In collections it helps decide whom to contact first, through which channel and with what offer. Like any model, it is recalibrated with the actual results of each period.
KYC (know your customer)
KYC (know your customer) is the set of controls a financial institution uses to verify who its customer is and where their funds come from. It covers identity validation, the transaction profile, the declared economic activity and periodic updates of that information. It is the foundation of anti-money laundering work.
KYB (know your business)
KYB (know your business) is the verification of a business customer: legal existence, representatives, shareholders, ultimate beneficial owners and economic activity. Before opening an account or approving a business loan, the institution confirms that the person signing has authority to do so and that the ownership structure does not hide money laundering or fraud risk.
AML (anti-money laundering)
AML (anti-money laundering) is the prevention of money laundering and the financing of crimes: policies, transaction monitoring and reports that surface unusual operations. In Ecuador, financial institutions, including savings and credit cooperatives, are obligated entities that must report suspicious operations to the Financial and Economic Analysis Unit (UAFE).
Identity impersonation
Identity impersonation is fraud in which someone uses another person's data or documents to open an account, apply for a loan or move money in that person's name. It is addressed at onboarding and before disbursement, with document validation, liveness detection and device and behavior signals.
Synthetic identity
A synthetic identity is a fake identity built from real and invented data, for example a valid national ID number combined with a different name, another date of birth and an email created for the occasion. It is hard to detect because no victim complains; it usually surfaces when you cross-check sources and review the inconsistencies between them.
Liveness detection
Liveness detection is the check that a real, present person is in front of the camera, rather than a photo, a recorded video, a mask or an AI-generated face. It is used together with face matching against the ID document. In Ecuador, biometric data is sensitive data under the LOPDP.
Voice biometrics
Voice biometrics is the verification of a person through the characteristics of their voice. In a contact center it authenticates customers while they talk, without a long list of security questions. Because AI can imitate a voice, it is wise to combine it with other signals and to treat it as sensitive data under the LOPDP.
Open finance
Open finance is the model in which customers authorize their financial institution to share their data with third parties, through secure APIs, so they can receive other services, such as consolidating accounts or getting credit based on better information. In Ecuador, that exchange must comply with the LOPDP, especially its consent and purpose rules.
Embedded finance
Embedded finance means financial services, such as credit or insurance, offered inside a non-financial company's platform at the moment the customer needs them. One example is the financing offer that appears at checkout in an online store. The financial institution behind the product remains responsible for risk, identity and compliance.

Let's talk about what your institution needs to solve.

A first conversation to understand your operation and tell you plainly where we can help, and where we can't.