Widespread digital transformation and continuously changing customer behaviour and demands are driving financial institutions towards adoption of cognitive systems to meet customer expectation and reduce operational cost. Customer growth is crucial for the new age financial institution. These institutions are finding actionable insights to make faster decisions associated with these objectives with a single customer view by using visual as well as real-time analytics. Furthermore, analytics platforms can feed a variety of multisource datasets without volume limitations, thereby offering financial services a complete understanding and helps in identifying new sales opportunities in real-time.
AI technology can be categorised into four major segments including machine learning, deep learning, natural language processing, and image and video processing. Machine learning and natural language processing are the prominent and most preferred technologies in the BFSI. These technologies are widely used in fraud detection, process automation, underwriting, claims processing, risk and compliance, investment management, credit lending, customer faced chatbots, personal financial assisting robots, and others. Machine learning helps in analysing large datasets from multiple sources and provides actionable insights. Some of the use cases of machine learning are as follows:
- Personalized services – Financial institutions are delivering personalized services based on customer profiles by analysing data on customer satisfaction, preferences, buying history, demographics, and behaviour to better understand their needs. These insights can help you delivering personalized offers that improve customer satisfaction and retention.
- Personal finance management – these institutions are automating personal finance management using machine learning to give customers a 360-degree view of their finances and provides forward-looking advice based on customer risk profiles and available funds
- Product offerings – Financial institutions are using machine learning to recommend products using insights to precisely gather customers and prospects according to their profiles and probable needs. It provides cross-sell and up-sell opportunities.
Conclusively, financial sector is adopting AI technology to better understand consumer behaviour and expectation. Additionally, due to huge volumes of data being generated from several sources such as customer data, processes and others, is providing an opportunity to analyse them and gain actionable insights that can improve decision making.
ICT – Research Analyst,