December 10th, 2020
At that time how to standardize the data aggregation (less controversial and less costly that web-scrapping) and pursuing the creation a legal framework where the initial focus, API from tech side and PSD2 from legal side were the solutions we have today. A myriad of vendors (Unnax
, etc.) are providing this service providing fintechs and banks the service account aggregation “as a Service”.
In the early 2000s the big data was starting, costly database licenses and expensive hardware, the cloud were just an idea then, make difficult to squeeze the most of value of the data. Before AI/ML and advanced analytics were familiar technologies the promising trend was “data mining”.
2021 is coming. Most of banks and fintechs are investing in both sides: investing in PSD2 information of its customers from AISP (account information) vendors and investing in the technology to make available the information of own customers to AISP vendors to become compliant with PSD2 framework.
The initial use cases developed with account aggregation data in the past years were:
● Providing customer a nice “account aggregation” app or website to make the bank offering it the “preferred or main one” of each customer.
● Using the information in a very “hand-made” and professional services intensive to provide competitive business intelligence.
With this to cases both, customer and banks are having a better view of the “what”, what the customers have and do with their money: the wealth position, distribution and flows).
In the other hand, CDPs (customer data platforms) are becoming a new piece in the core IT architecture of many B2C verticals with different goals/missions of CRM and Data Lakes. The ability to automatize the cross-analytics of customer interactions in digital channels, customer events known (payments, investments, divestments, money flows/transfers) will help to predict “when” the flows or wealth distribution changes between the different accounts of a given customer could occur (or customer segment trend) and “how” it occurs, the mechanisms to operate between accounts. Predicting when the customers could decrease its position in your bank to increase in others is a first step, understand how is the normal procedure as pattern is another step...but there is something missing yet.