Connect to all banks through a single standardised API
Categorising transactional banking data in an accurate and automated manner lies at the heart of extracting value from Open Banking data. Our artificial intelligence engine classifies banking transactional data based on our proprietary taxonomy and NLP machine learning models, and delivers consumers and SMEs behavioural insights to improve credit risk assessment, debt advice and collections operations, customer experience and fraud detection decisions.
Our adaptive and self-learning artificial intelligence engine continuously optimises its transaction classification accuracy to respond to the dynamic nature of consumers and SMEs behavioural spending patterns.
Ducit.ai’s transaction categorisation API provides a scalable and cost-effective solution for organisations looking to improve decisions based on consumer and SME consented financial behavioural data.
Affordability checks are a fundamental requirement in consumer credit, and are quite often confused with conventional credit checks. This is a dangerous misconception, and one that Ducit.ai is committed to resolve.
Our Open Banking affordability score is based on the most up to date financial transactional data to estimate the forward-looking ability of consumers and SMEs to afford the credit product in question and ensure their financial wellbeing is preserved.
Traditional credit checks are backward looking and fail to take into account the changing circumstances of individuals.
Our API driven affordability score product addresses this long-standing industry challenge, and puts consumers and SMEs in control of their finances.
Fraud activity is constantly evolving, and our dual framework utilises unsupervised machine learning to detect anomalies from previously unseen data where there is no historical fraud flag, and supervised machine learning to identify fraud from existing labelled data.
The over-reliance of the banking and payments industries in legacy business-rules based fraud detection platforms combined with over simplistic analytical approaches has resulted in record levels of fraud.
Our approach combines the power of transactional data from Open Banking and confirmed fraud data from across the industry with the latest artificial intelligence techniques to enable financial institutions to make better fraud detection decisions.