If you want to build personalized financial experiences for your customers using AI and machine learning, MX is a good candidate. MX Technologies offers a broad platform that aggregates financial accounts, discovers insights and builds personalized money experiences. It securely aggregates and verifies financial data, adds context to it, and lets businesses build experiences that can increase engagement and growth. With broad connectivity, data augmentation tools and a security and compliance focus, MX is designed to help businesses get more value out of financial data.
Another good option is Flybits, a data-driven personalization platform that lets banking companies offer contextually and personally relevant experiences at scale. Flybits offers an interface for rapid experience creation, secure data orchestration, and features like trust-based data sharing and hyper-personalization. It can be used for a variety of use cases like onboarding, spend stimulation and cross-sell and up-sell, which can result in substantial improvements in marketing ROI and engagement rates.
For a more AI-infused approach, Dynamic Yield is a good platform for generating unique, algorithmically matched content and products for each customer across multiple digital touchpoints. It includes features like audience discovery, content and offer personalization, product recommendations and experience optimization. With features like A/B testing and AdaptML deep learning for personalization, Dynamic Yield is a good fit for companies that want to offer customers a unified, personalized experience.
Last, Kniru is an AI-powered financial advisor platform that offers hyper-personalized financial management through chat. It covers a wide range of financial planning topics, including investment advice, expense management and retirement planning. With features like personalized savings recommendations and anomaly detection, Kniru helps users stay on top of their financial activity and make the most of their financial planning.