Leverage structured and unstructured data to improve the predictive power of models
Use of statistics, machine learning, predictive modeling, and other analytical techniques to uncover insights about customers, products, and other areas of research
Creating automated reports based on IFRS for internal or external (investor, auditor, regulator) requirements
From gathering user requirements, writing specifications to product testing and deployment ,and applying ECB regulations
Adding new data sources achieves additional model accuracy for both pricing and reserving
Full scope risk management - from customer analysis, to segmenting defaults, to tool usage for processes, and strategy for customer engagement
Finding the biggest drop-offs of clients for your services, and ways to improve.
From automated reporting to measuring effectivity, to devising strategies and methods for improved collections
By automating the customer onboarding process, business reduced the time it takes to bring new customers on board. This lead to improved customer satisfaction and increased revenue as customers start using the product or service sooner.
By analyzing companies practices, identified areas what caused frustration or dissatisfaction among customers. By improving these processes, we achieved a more positive experience for our customers, which can lead to better relationships and increased loyalty.
Automating the customer onboarding process free up staff time, allowing them to focus on other important tasks, such as customer service or product development and in long run this reduced the need of increasing our stuff.