Americans are saving at historically higher rates after hitting a peak at 33.7% in April 2020, according to data from the U.S. Bureau of Economic Analysis. The household saving rate in the euro area similarly reached a historic peak at 25% in the second quarter of 2020, according to eurostat. The euro area continues to save at higher than usual rates.
However, as we emerge from this global health crisis, how many will continue to save? What savings and money management features will consumers need in uncertain times?
The pandemic has also changed what customers expect from their banks. Preferences for one bank over another is increasingly influenced by how the bank makes them feel. In a survey conducted last September, Simon-Kucher found factors such as the extent the bank had features that made saving engaging and fun, or if the bank values their loyalty, have risen in importance. These emotional factors now rank as one of the top five reasons driving decisions to switch banks (see graph below).
Banks must accelerate efforts to tap into their treasure trove of data, leverage data analytics and predictive intelligence to uncover emerging and fundamental shifts in banking behaviours and preferences in order to retain high value customers, prevent attrition, deepen relationships and increase client acquisitions.
Interactive flow of funds mapping
An interactive flow-of-funds model mapping and analyzing the movement of funds in real-time, can provide insights and intelligence into how customer banking and savings behaviours are evolving and changing. A flow-of-funds model tracks funds movements internally between various deposit, lending and investing accounts, and externally involving accounts held outside the institution.
For example, leveraging its flow-of-funds model, one leading bank was able to detect large outflows of funds from mutual funds to more liquid savings instruments within the institution at the peak of the lockdowns in 2020. The bank also saw less movement of funds out of the institution during this period indicating a flight-to-safety and not a sign of bank-switching behaviour. There were also distinct savings behaviour differences across customer-segments based on age, region, account balances and tenure during the pandemic. Younger customers were more likely to 'park' funds in checking accounts, compared to older customers who preferred savings accounts or short-term savings instruments.
The bank has been able to capitalize on these insights to personalized messages, offers and rewards to match customer segment preferences.
Accurate segmentation & analysis
Flow of funds analysis can also help banks refine customer segmentation efforts and identify changing segment characteristics early. Using a flow-of-funds analysis, one bank noticed early during the pandemic that mass market customers were parking funds in cheque accounts, while customers with assigned financial planners moved money out of mutual funds into savings accounts. Meanwhile, private banking customers were moving funds out of the bank into alternative investments during the pandemic.
Banks can also uncover geographical differences in savings preferences between urban and rural regions.
At one bank, flow-of-funds data analysis revealed customers who had been with the bank for one year or less were more likely to move funds out of the bank when long-term CDs came due during the pandemic. Noticing that some high-value customers preferred more liquid, shorter term savings products, the bank was able to respond quickly with the introduction of savings products with more flexible terms during the pandemic.
In a world constantly reshaped by emerging technologies, pandemics and demographic shifts, having a more granular and frequent view on customer banking behaviors enables a bank to detect and accurately predict shifts in customer priorities and preferences.
Instead of a knee-jerk reaction, bank promotional programmes can be more precise, targeted and informed by the most current customer behaviour patterns. Analyzing real-time, daily and weekly fund movements at the customer level can improve retention where customers exhibiting attrition behaviors can be quickly identified for targeted offers. While insights on emerging preferences can be used to improve product innovations and personalize communications to accelerate acquisitions.
According to Simon-Kucher estimates, the improvement in retention, cross-selling and engagement from flow of funds analysis can translate to an additional 10-15 basis points (bps) in average revenue per bank customer.
Most banks mistakenly think translating data into actionable intelligence involves huge financial outlays, when in fact it comes down to leveraging capabilities that the bank already possesses.
Real-time ledger capabilities from the new generation of cloud native core banking platforms are also increasingly accessible as innovative plug-in integrations to help make sure banks can analyze their customers’ evolving behaviours as it happens. Banks can respond quickly, more effectively and increase the certainty of delivering the top line benefits outlined here.