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.
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.
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.
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.
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.
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.
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.
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 firstname.lastname@example.org.