Personalization: Role for Trustworthy AI
Digital Trust
Jayanth Krishnan
8/11/20251 min read
Context
Personalization, across sectors, including banking and FinTech is said to contribute to Digital Trust.
For firms building our their products and services AI will provide significant capabilities in delivering Personalization features
Knowledge Takeaways:
Trust in the FinTech context can be equated as Trust = Fairness+ EQ+ Reliability+ Security
Personalization efforts targeted at Reliability and Security will yield the highest Trust ROI
Personalization requires a massive data warehouse of past customer behavior
Such large data warehouses either come from large banks or a long history of serving customers with multiple choices
Several ensemble models utilizing Machine Learning, Deep Learning, Neural Nets, GANNs have been employed by banks to learn customer preferences (through a sophisticated trial and error)
Action Steps
Invest in a JTBD or grounded methodology based research to understand how personalization leads to trust and eventually value. Every product-market fit is unique to the customer's decision making environment
The use of synthetic data is gaining popularity to construct customer personas where there are large gaps in data used to train models
Personalization Model
Personalization Use cases in FinTech
Plenty of consultant literature (like this) out there on how personalization drives value to customers. Personalization has been the holy grail of customer satisfaction for decades. However, the lower cost of data storage, computation power, ubiquity of mobile devices and network speeds has resulted in a low cost personalization using data warehouses.
Most technology architectures optimized for personalization will not be optimized for digital trust. Hence personalization and security will need to be designed from the ground up.