Credit Scoring Engine
Real-time underwriting model combining bureau data and behavioral signals.
BNPL Fintech Development
Addi built its name on letting Colombian shoppers split purchases into instalments at checkout, both online and in-store. Cloning that model means engineering a credit decision engine, not just a payment button.
Algosoft structures Addi-style builds around four pillars: the consumer instalment app, the merchant checkout SDK, the underwriting/risk engine, and a collections and repayment management system.
Real-time underwriting decisions using bureau and behavioral data.
Drop-in checkout widget for e-commerce and point-of-sale partners.
Reporting, disclosures, and audit trails aligned to Colombian financial regulation.
DataCrédito and TransUnion Colombia connected for credit checks.
Automated repayment reminders, retry logic, and delinquency management.
Why Algosoft for Colombia
We've built scoring models that combine bureau data with behavioral signals for faster, safer underwriting decisions.
Our architecture builds in audit logging, disclosures, and reporting structures from day one.
We design SDKs that are simple for merchants to embed without compromising on risk controls.
Colombia Pricing Tiers
All prices in COP at 1 USD = 4,100 COP. USD equivalents shown for reference.
| Tier | Cost (COP) | Cost (USD) | Timeline | Best For |
|---|---|---|---|---|
| Basic | COP 82,000,000 – 205,000,000 | $20,000 – $50,000 | 14 – 18 weeks | Single-merchant pilot with basic credit checks |
| Standard | COP 205,000,000 – 533,000,000 | $50,000 – $130,000 | 18 – 26 weeks | Multi-merchant rollout with bureau-based scoring |
| Advanced | COP 533,000,000 – 1,312,000,000 | $130,000 – $320,000 | 26 – 34 weeks | Full platform with fraud detection and collections automation |
| Enterprise | COP 1,312,000,000 – 3,280,000,000+ | $320,000 – $800,000+ | 34 – 40 weeks | National-scale platform with advanced ML underwriting |
By Feature Set
Each module below can be scoped independently as part of a phased fintech rollout.
Real-time underwriting model combining bureau data and behavioral signals.
Embeddable instalment-payment widget for e-commerce and POS integrations.
Disclosures, audit logging, and reporting structures aligned to Colombian financial regulation.
Pattern-based fraud screening layered on top of credit decisioning.
DataCrédito and TransUnion Colombia connections for real-time credit checks.
Automated reminders, retry logic, and delinquency workflows for instalment repayment.
Where Your Budget Goes
Representative allocation across the Standard-to-Advanced tier range.
Colombia-Specific Cost Drivers
Regulatory and market factors unique to Colombian consumer lending.
Rule-based scoring is cheaper than a trained machine-learning risk model.
Connecting both DataCrédito and TransUnion Colombia adds redundancy but increases integration cost.
Full regulatory reporting and audit infrastructure requires more engineering than a minimal disclosure flow.
Supporting many merchant platforms (Shopify, custom POS, WooCommerce) multiplies SDK testing effort.
Real-time anomaly detection costs more to build than static rule-based fraud checks.
Multi-channel repayment reminders (SMS, push, WhatsApp) add scope beyond basic email reminders.
Project Timeline
A phased delivery plan for a regulated instalment-credit platform.
SFC requirement gathering and credit policy definition.
Bureau integration and underwriting model development.
Checkout widget development and merchant sandbox testing.
Instalment selection, repayment tracking, and account dashboard.
Fraud detection rules and SFC-aligned audit logging.
Penetration testing, compliance review, and merchant pilot rollout.
Technology Stack
A stack chosen for financial-grade security, auditability, and bureau connectivity.
Optimise Your Budget
Practical ways to manage fintech development spend without compromising compliance.
A simpler rule-based underwriting model can validate the business before investing in ML scoring.
Launching with a handful of merchant partners reduces SDK testing and support overhead initially.
Start with DataCrédito alone and add TransUnion Colombia once volume justifies dual-bureau checks.
Leverage existing SFC reporting templates rather than building bespoke compliance dashboards from scratch.
Start with email/SMS reminders before investing in a full omnichannel collections system.
Avoid costly compliance rework by working with developers who understand SFC requirements upfront.
Our Delivery Process
A structured six-stage process tailored to regulated lending platforms.
We map SFC requirements and define your initial credit policy and risk appetite.
Bureau integration design and data flow architecture for underwriting decisions.
Two-week sprints covering scoring engine, merchant SDK, and consumer app in parallel.
DataCrédito, TransUnion Colombia, PSE, and Nequi wired and validated against sandboxes.
Penetration testing and SFC-alignment review before any merchant goes live.
Controlled merchant pilot followed by scaling to additional partners and cities.
Frequently Asked Questions
Costs range from COP 82,000,000 for a single-merchant pilot to COP 3,280,000,000+ for a national-scale platform with advanced ML underwriting.
Depending on your lending structure, you may need to register with or report to the Superintendencia Financiera de Colombia — we recommend involving local legal counsel early.
We integrate with both DataCrédito and TransUnion Colombia, the two primary credit bureaus used for consumer lending decisions.
Yes, many clients launch with rule-based underwriting and migrate to a trained ML model once sufficient repayment data is collected.
A single-merchant pilot with basic credit checks typically takes 14 to 18 weeks.
The credit scoring engine and compliance/reporting infrastructure together typically account for around half the budget.
We offer ongoing retainer support for model retraining and compliance updates as your repayment data and regulatory landscape evolve.
Speak with our fintech team about scoping a compliant instalment-credit platform for the Colombian market.
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