“Turn your financial data into competitive advantages with state-of-the-art predictive models.”

Key Benefits

Predictive Analysis

Anticipate market trends and customer behaviors with machine learning models specifically trained for your financial sector.

Intelligent Automation

Reduce operational costs by automating processes such as account reconciliation, fraud detection, and regulatory reporting.

Portfolio Optimization

Quantitative investment algorithms that analyze millions of variables in real time to maximize risk-adjusted returns.

Risk Management

Advanced models to identify credit, operational, and market risks with greater precision than traditional methods.

Customer Insights

Hyper-personalized segmentation and propensity models to improve cross-selling, retention, and financial customer experience.

RegTech Solutions

Automated regulatory compliance for AML, KYC, and regulatory reporting using natural language processing.

Our Solutions

AI Specialized in Finance

Financial Forecasting

Predictive models for cash flow, sales, credit risk, and market behavior with up to 95% accuracy.

Sentiment Analysis

NLP to extract insights from financial news, social media, and earnings reports that impact your assets.

Robo-Advisors

Automated investment platforms with asset allocation algorithms tailored to each profile.

Fraude & AML

Real-time detection of anomalous patterns in transactions with up to 70% reduction in false positives.

Financial Chatbots

Virtual assistants for 24/7 customer service with the ability to handle complex product inquiries.

Credit Scoring

Alternative scoring models that incorporate non-traditional data to expand access to credit.

Smart Contracts

Automation of financial contracts with blockchain and triggers based on market conditions.

Advanced Visualization

Interactive dashboards with drill-down to explore multidimensional financial data.

Continuous Innovation: Our AI models are updated quarterly with the latest deep learning techniques and new financial market datasets. Request a personalized demo at soluciones@iafinanzas.com

Methodology

Implementation in 4 Phases

  1. Data Audit: Evaluating the sources, quality, and structure of your financial data.
  2. Workshops: Sessions with key teams to identify pain points and opportunities.
  3. Benchmarking: Comparison with industry and competitor standards.
  4. ROI Projection: Estimate of potential economic impact by area of ​​improvement.
  • Feature Engineering: Creación de variables predictoras específicas para su negocio.
  • Model Selection: Elección de arquitecturas de IA (XGBoost, LSTM, Transformers) según necesidades.
  • Backtesting: Validación de modelos con datos históricos y escenarios de stress.
  • Integration API: Desarrollo de conectores con sus sistemas core (ERP, Core Banking, etc.).
  • Piloto Controlado: Deployment en ambiente sandbox con monitoreo continuo.
  • Training: Capacitación a equipos en interpretación y uso de outputs.
  • Change Management: Plan de adopción organizacional para nuevas workflows.
  • SLA Definition: Acuerdos de nivel de servicio para mantenimiento.
  • Performance Tracking: Dashboards con KPIs de precisión y impacto económico.
  • Continuous Learning: Re-entrenamiento automático con nuevos datos.
  • Quarterly Reviews: Sesiones estratégicas para escalar soluciones.
  • Innovation Lab: Pruebas de conceptos con tecnologías emergentes.

Success Stories

Thanks to this AI solution, we now generate accurate financial projections in minutes. Previously, this required hours of manual work. It’s a key tool for our strategic decisions AI in Finance and Data Analytics.

Ana Poma

AI allows us to detect patterns in market behavior that previously went unnoticed. It’s like having an extra team of analysts working around the clock without a break.

Lorena Lopez

By automating financial data analysis, we’ve reduced errors and accelerated report generation. Today, we make decisions faster and with greater confidence.

Yuliana Yabes

Using AI for financial statement analysis has been a game-changer. We now identify risks and opportunities early, improving service to our clients.

Sara Lara

The precision with which AI detects anomalies in transactions has allowed us to prevent fraud and improve operational risk management. It’s an essential extra layer of security.

Norka Correa

We used to need an entire team to analyze credit profiles. Today, AI does it in seconds, with better approval rates and lower delinquency rates. It’s pure efficiency.

Paola Valer

What we value most is AI’s ability to convert large volumes of data into actionable insights. It has helped us optimize budgets and anticipate deviations.

Guillermo Vergara

Incorporating AI into our audit processes reduced review time by 60%. Additionally, automatic inconsistency detection improves the quality of our service.

Luis Speed

With this AI solution, we’ve been able to automate the scenario analysis workflow, allowing us to anticipate different economic scenarios and respond more quickly.

Claudio Perales

Frequently Asked Questions about AI in Finance and Data Analytics

Answers to our clients’ most common questions about AI in Finance and Data Analytics

We implement Zero-Trust architectures, end-to-end encryption, and compliance with regulations like GDPR and SOX. Your data never leaves your controlled environment.

We work with structured data (transactions, balance sheets) and unstructured data (contracts, emails). We perform data cleansing and feature engineering to maximize predictive value.

Standard solutions: 6-8 weeks. Custom projects: 3-6 months. We offer operational MVPs within 30 days for early validation.

We define specific KPIs such as reducing delinquency, increasing cross-selling, or reducing operating costs, with pre/post implementation measurement.

AI makes it possible to automate repetitive processes, analyze large volumes of data in real time, and detect complex patterns that would be difficult to identify manually. This translates into faster decisions, fewer errors, improved risk detection, and optimized financial planning.

Yes, we develop XAI (Explainable AI) models with full decision traceability to comply with financial regulations and internal audits.

We have pre-built connectors for major ERPs (SAP, Oracle), core banking (Finacle, Temenos), and cloud platforms (AWS, Azure).

Contracts with 24/7 SLAs, proactive monitoring, and quarterly model updates. Plus: an innovation program with new features.

We have implemented solutions in retail banking, asset management, insurance, and fintech. Ask for our case studies in your industry.

Using machine learning models, AI can identify anomalous behavior, inconsistencies, or risk patterns in financial transactions. This allows for proactive action against potential fraud or losses, strengthening internal control systems and financial security.