Banks and financial companies have always collected large amounts of data, primarily concerning customers, deposits, investments, loans, transactions, financial market data, and recently, logs of website clicks and app usage. While some data is highly regulated, it’s still possible to tap into a wide range of analytical use cases for marketing, risk management, and operations.
Financial Institutions are increasingly relying on machine learning and data science to collect a wide range of data. In particular, this data can be used to pinpoint customers at risk of churning in the near future; personalize product and service recommendations; and automatically analyze sentiment in customer reviews.
Optiwisdom has a unique product for the banking industry solving their customer credit card transactions for protecting them if it is a real purchase or not. This is OptiFraud. This is a professional services firm specializing in applying Machine Learning special algorithms to solve banking business model.
Our team of data scientists, management consultants and statisticians are on a mission to help banking fraud organizations operations in a new era defined by big data analytics, learning algorithms, and predictive intelligence.
We use Machine Learning to unravel the intrinsic relationships in complex multi-dimensional data and explain them as simple math. Our team develops purpose-built learning algorithms that sift through complex data to identify statistically significant variables and explain the mathematical relationships shared between them.