Due to the high data volume, large historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence as banking, capital markets and insurance. AI enhances efficiency, reduces costs, offers data insights and manages risks.


Next, we list our solutions for Banking, Capital Markets and Insurance enterprises.


  • Loss Reduction between 60%-90%.
  • More security for your customers.

Fraud Detection

Fraud detection is one of the top priorities for banks and financial institutions, losing tens of billions of dollars every year. Fraud detection problems are known for being extremely imbalanced, a typical workflow will have only have 1% of fraudulent transactions. Certain kinds of algorithms that we have at Prometeo are specially designed for this scenario.


  • 24/7 customer service.
  • Opex reduction.
  • Sales increase between 10%-25%.

Bots & Personal Assistants

A chatbot is a computer program capable of understanding textual or spoken information and respond to the customer in certain simple tasks. In the finance industry, they can be used to improve customer service, help customer to make better decisions, automatize claim management and they can be combined with other AI services, to improve fraud detection and increase sales.


  • Increase revenue between 10%-35%.
  • Enhanced cross-selling by +50%.
  • Improve customer experience.

Personalized Recommendations

A recommendation system uses machine learning to understand the customers preferences with the objective of recommending them products. With real-time personalization, enterprises can surface relevant content to each individual person, display the right calls-to-action to guide visitors through the decision-making phase, cross-sell products based on customer intent, and provide a enhanced customer experience.


  • Human bias reduction in financial models.
  • Planning improvement.
  • Cost reduction.

Financial Forecasting

Currently, many financial forecasting and planning processes are manually intensive and suffer from inherent human biases. Machine Learning and Deep Learning are used to improve predictive (what will happen) and prescriptive (the best course of action) financial forecasting processes. Cash-flow forecasting, revenue forecasting, cost and expense planning, and balance-sheet planning are all areas of predictive financial analytics that will benefit from AI technologies.


  • Maximize business opportunities.
  • Avoid financial catastrophes.
  • Ensure sustainable growth.

Risk Assessment

Financial risk management is an essential element of any successful finance institution. With the massive amount of data created every day, Big Data systems are a helpful tool that finance professionals can benefit from to simplify information, guide a company through the murky waters of the financial market and create strategies to avoid losses and maximize profits as much as possible.


  • Reduce errors.
  • Improve employee satisfaction.
  • Cost reduction.

Automatic Document Processing

Optical Character Recognition (OCR) technologies allow reading and processing of text from different sources. It can be used to manage invoices, process forms and scan documents. Other technologies within the Natural Language Processing (NLP) spectrum can help classify legal documents and control regulatory compliance.


  • Reduce losses.
  • Improve customer retention.

Churn Detection

Customer churn detection is a top priority for many financial firms. Since getting new customers is much more more expensive than retaining existing ones, understanding why customers churn and estimating the risks are powerful components of a data-driven retention strategy.

Do you have a use case for your industry that is not listed here? Send us an email to hello@prometeo.ai.