AI/ML based Customer Intelligence should be at the core of banks technology strategy!

New technology advances have given banks access to exponentially more data about what customers do and want. It is an amazing opportunity for banks to use analytics to unlock the goldmine of information to cater to their customers. Banks have been struggling to give customers an engaging experience with them. There is a misconception that just developing digital channels to access their account is enough to get customer loyalty. In order to provide an engaging experience, it is essential what contextual information should be given to their customers to make their journey fruitful. For that banks must invest in technology stack which will help them to understand what customers want. Artificial Intelligence and Machine learning will play a crucial role if not the crucial role to get customer intelligence.

In this era of mass customization, customers have become more connected more demanding and less loyal. Easy availability of banking services from non-traditional banks mean easier comparison and faster switching between banks. The relationships become brief and largely transactional. We are already experiencing the concept of one click transactions in fund transfers, brokerage & trading and other services to the new provider with very little effort. The demographic trends have scary implications for conventional financial services firms as the millennials & younger generations become the least loyal. According to NGDATA, in 2016 33% said they will switch banks due to poor customer service and in 2017 the number was 41%.

What & why Customer Intelligence:

Banks adopting customer intelligence strategy keeps the customer at centre of all operations. They have a deeper understanding of customer through their banking relationships and transactions. Customer intelligence investments gives insights about the customer to understand their persona.

It helps in building the customer persona through which banks can segment customers to improve CX and to have a targeted messaging. It helps banks to engage at an emotional level and strengthens the relationship with the customers. Customer Intelligence is the path to true KYC.

Its important banks to become an indispensable partner for consumers throughout their life. Which means becoming truly omnichannel, offer ultra-personalised care, provide a compelling product & financial eco-system. How can cutting edge technology contribute to the above goals?

How to create a Customer Intelligence Strategy with technology:

For starters banks need to create customer centric hub. Create a unique customer profile depicting all relationship maps. Record customer references, customer Assets/transactions etc. Use Master Data Management (MDM) to get one version of true customer data. Once the customer centric hub is ready, connect it to the digital experience center to get the 360 & 720-degree view of the customer. Once this happens, the relationship manager can have access to the individual customer journeys by creating behavioral and emotional customer personas. Using AI/ML models create the ideal customer profile and have the relationship manager prepare for the “Next Best Action” for the customer. This can help in providing ultra-personalization for the customer.

Banks can adopt big data architecture like Hadoop to store client data from various touch points both online & offline. Use a Master Data Management tool to store the single version of truth of the customer. Tools like Kafka can give real time streaming data of the customer actions. Along with this utilize some ETL and analytics tools to create the customer 360/720 view. Banks can use RFM analysis and Machine Learning extract real time data for each customer segment. Automate the process of personalization and provide insights with the help of customer intelligence.

Banks are already using artificial intelligence (AI) to experiment with service that is ultra-personalised.  According to PwC many banks in the United States are piloting AI-based client advisors. Here the AI engine is primed with all kinds of data on banking products and data on customer transaction & interaction history, policy and procedures guidelines, and more, to provide contextual service to their customers.  We are just scratching the surface how AI can disrupt banking operations.  AI, machine learning, and customer analytics will become the key player from a client engagement perspective in the coming years. These new cutting-edge technologies will find a way to integrate themselves in customer’s lives. The chances of this becoming a reality is high as it will be ultra-personal with accurate intelligence gathered from data about consumer behaviours, choices, and preferences.