Financial Services - Consumer Banking
Digital Banks can achieve more automation, intelligence, and personalization with AI/ ML. Numerous banking activities are becoming invisible, as journeys often begin and end on interfaces beyond the bank’s proprietary platforms. For the bank to be ubiquitous in customers’ lives banks will need to reimagine how they engage with customers and undertake several key shifts by solving latent and emerging needs. The time to think about AI-first business models in consumer banking is now.
NLP can help banks to process huge sets of structured and unstructured documents and extract key information. Machine learning models help to explore the data and find patterns in crypto-currencies and NFTs. OCR can enable banks to automatically process hand-written documents like cheques, deposit forms, and others. Vision analysis can help to identify and authenticate new/old customers.
Speech recognition enables text extraction from speech and analyzes them; personal digital assistants can help provide wealth information, retirements plans, and more customized products to customer banking needs.
AI can help banks boost revenue by uncovering new and previously unrealized opportunities. It also offers more personalized services to lower operating costs by automating complex works, improving resource utilization, reducing error rates, etc. AI systems enable banks' processes to be agile by having seamless integration with non-banking apps, facial recognition linked payment, personalized offers, personalized money management, investment recommendations, and aggregated overview of daily activities. AI can help banks move from providing financial services to their customers to facilitating their financial betterment.