Sharpen decisions in Financial Services with explainable Deep Learning
Financial Services can use, trust and control DreamQuark’s AI to solve their day-to-day challenges regarding marketing, risk and compliance.
Nicolas founded DreamQuark in 2014 with the unique vision of democratizing IA and bringing Deep Learning to financial institutions. To achieve this, Nicolas surrounded himself with the best data scientists and computer engineers to develop class leading algorithms embedded in Brain, the most advanced predictive platform accessible to everyone.
Today DreamQuark offers to banks and insurance companies a unique IA solution based on Deep Learning that enables the creation of smart applications within few clicks. Brain covers all their main activities such as segmentation, targeting, underwriting, credit scoring, asset management, compliance, anti-money laundering, fraud, dunning, satisfaction and customer retention.
DreamQuark stands out from the competition by providing ease of use, outstanding prediction performance and unique decisions interpretability within a single platform.
- EASE OF USE
Deploying a Deep Learning solution is highly complex and usually requires a data scientist team not necessarily in phase with operational team expectations. To solve this, DreamQuark automates all data pre-processing tasks including data formatting, identification of variables transformation and models training. Without any Data Science skills and within few clicks, business experts can now create powerful AI business application which can be easily integrated in any existing IT system through APIs.
Brain leverages breakthrough proprietary Deep Learning which benefits from years of in-house research and development. In addition of being outperforming and providing fast prediction, DreamQuark algorithms can identify hidden relations within the data which remain invisible to other solutions. On top of that, Brain can handle structured data as well as unstructured data from images and audio.
DreamQuark’s Brain solution avoids the “black box” effect by providing users with transparent explanations for every single decision the platform makes: users can easily understand what was important to create the model and identify any bias. Brain tracks any changes in models & data and empowers business experts to comply with existing and future regulations (such as GPDR).