Everyday customer interactions with ATMs or ASSTs to withdraw cash or check their account means these touchpoints emit hundreds of thousands of data points per day. This data holds the answers to how customers interact with those end points and how they are performing. However, currently this data is not being fully analysed or harnessed at all.
Data Analytics
This is surprising when you consider how better data analytics is widely understood to be crucial to enable banks to stay ahead of the competition. Indeed, one major study found that nearly half (48 percent) of banking executives globally agreed on this. However, many do little with it. The data which is harvested from the self-service banking network, including ATMs and ASSTs, is a critical way for banks to lower their operational costs. At the same time it can improve their offerings and increase their bottom line.
Real-time data collection and analysis is more than just critical for managing operational costs. It also plays a significant role in how banks realise their omnichannel ambitions to improve customer engagement and experience. For this to be successful, banks must leverage tools which provide actionable insights into performance across a number of channels including in-person services, ATMs, online and apps. The insights which are collected on these channels provide a complete and integrated picture of banking performance across all touchpoints.
Actionable Insights from Data
No matter how a customer interacts with the bank, every touchpoint provides large amounts of data which can be collected, sorted, and analysed for actionable insights. However, taking this information from raw data and transforming it into valuable insights is a challenge for many financial services organisations.
To do this, it involves strong data management and analytics processes and end-to-end mapping of all self-service banking channels, in-person and online. Real-time insights are also key to understanding how the network is performing and how customers are interacting with the endpoints. Importantly, this information must be easily accessed throughout the organisation. Doing this will enable the bank to identify if there are any inefficiencies or issues throughout the network which can be fixed swiftly, with minimal disruption to services.
Significantly, with real-time monitoring, banks can see any attacks on their services or endpoints from threat actors. The sensors are not only on the ATM. Those around the machines will be able to collect any interactions with the endpoints and in the surrounding area. For the most part, the sensors will pick up harmless interactions, but other times this may be an indicator that a threat actor was trying to take money out of the machine. As such, collecting, sorting, and analysing real-time data from the sensors can protect the bank and their customers and mitigate any harmful threats.
Furthermore, predictive analytics and continuous monitoring will enable banks to forecast the future performance of each touchpoint. Banks are able to apply specific parameters. Depending on their current business objectives they can better understand how each service channel is forecasted to perform in a specific situation.
How advanced analytics is transforming banking
As budgets tighten with rising costs, banks need to approach their ATM networks in a smarter way to optimise cash management and data forecasting. Real-time data tracking gives banks a greater understanding into customer behaviour. This is key to service performance improvements, including knowing in real time whether the ATM self-service interface is working or not. However, banks must get their data right, before they lean on the insights.
From real-time monitoring of customer interactions, financial services institutions can collect data based on the transaction flow, which can indicate if there is a better way for customers to complete their transaction. This will allow banks to see where network inefficiencies lie and then drive a culture of continuous improvement. The ATM is a vital touchpoint for a full omnichannel service, so banks leveraging data in the right way will ensure that the endpoint and the network are more user friendly.
Moreover, real-time tracking will also enable banks to predict when cash cartridges need to be replenished. As such, this will ensure there is enough cash in the machines for customers, and be able to better forecast how much cash the endpoint will need. This creates efficiencies around how banks deliver cash to the machines that need it. It reduces their Cash-In-Transit (CIT), security, interest and insurance costs.
Digital Transformation
To make sure that banks are making the most out of the data, they should leverage a dynamic, industry-specific banking business analytics platform. This should be available to all in the business and be able to seamlessly integrate into their current systems. The platform must collect and analyse the data in real-time from all key touchpoints in a bank’s network. Importantly, this data should be converted into usable insights for customer behaviour and performance metrics for the ATM. This will enable banks to adapt their offerings to changes in customer needs and market conditions. This will place banks on the front foot so they can focus investment in the up-and-coming areas.
The banking industry shows no signs of slowing down when it comes to digital transformation and development. The key here is to understand how all service channels, in-person and online, are performing to ensure customer demands are met. The way to do this is through leveraging real-time insights and data analytics. Financial services organisations must transform their approach to self-service banking strategies as data analytics is not only a driver of competitiveness, but also of long-term success.
Learn more at https://www.aurigaspa.com/en/
- Neobanking
