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From reactive to proactive banking header image

From reactive to proactive banking - 6 tips to better serve your customers

6 December 2021

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  3. From reactive to proactive banking to better serve your customers
AI-AR-ML
Customer Experience
Customer Insights
Digital Transformation

What is proactive customer service and how to implement it?

Customer service is a critical component of any successful financial institution. It’s a way to differentiate your business and stamp a brand on the minds of customers. It’s the backbone of your business and it’s what keeps your customers happy and coming back for more. Without the right customer service, even the most well-made product can be unsuccessful. Luckily, there is a way to keep your clients happy and on board with your brand: going from reactive to proactive customer service.

What makes a financial institution proactive?

Put in the simplest of terms, being proactive means taking timely actions to solve a problem even before it occurs. To take proactive actions, banks need to catch events as and when they happen, process them in real-time and perform or recommend actions accordingly. So, there is a need for real-time actionable data and minimizing latency in decision making. To attain this, financial institutions need to move away from manual processes which are time-consuming and prone to human error.

Automating business processes and decisions with AI-powered banking and CRM solutions can help converting customer relationship management from reactive to proactive. Here are some ways for financial institutions to provide better customer service by going from reactive to proactive.

#1 Turn data into actionable intelligence

Data is all over the place. But merely collecting data about customers and their product or service utilization is not sufficient. Rather than being meaningless in its raw form, data needs to be transformed into actionable intelligence to provide value to the organization. Now, cloud technologies are providing us immense opportunities to ingest and process data and generate insights out of them. This, in turn, can be used to generate immediate actions or recommendations. Additionally, the resulting intelligence must fit the particular needs of the persons receiving them and be timely, accurate and relevant. Only in this way can financial institutions provide unified and streamlined journeys, both for the customer and for their staff.

#2 Defeat latency and interaction delays 

Very often, the delay between an action and the data or information that triggered that action is too long, and that can have a huge impact on user experience. It prevents organizations from identifying and resolving critical issues proactively even before they occur.  Any delay in processing data can result in lost opportunities. With an intelligent solution, banks can handle data in real time rather than processing data of past events.

#3 Monitor data continuously

Having the ability to take actions proactively requires real-time analytics and continuous monitoring. Real-time data monitoring can seem a nearly impossible task with an average number of 20 interactions per customer per month, all digital and assisted channels combined. If we can monitor and combine all data from these 20 interactions in one platform, then every interaction would be an opportunity to improve data quality, cross sell, and client satisfaction, with CRM orchestrating them all at the backend. This is only doable with automated and systematic monitoring of data. CRM systems work round the clock to consume data, build systematic processes and provide insights. Banks should leverage these intelligent solutions to provide visibility into processes and allow real-time monitoring so good and timely decisions can be made.

#4 Provide value for your audience

There is no question that we are overwhelmed by information. Yes, data must be transformed into actionable information, but it must not overwhelm us with unnecessary noise and decrease our processing or decision quality. Instead, it must eliminate noise by drawing special attention to exceptions or distinctive features. Data must be analyzed and broken down into contexts and views that provide value for their audience. For example, dashboards should be role-based such as Relationship Manager Dashboards, Branch Manager Dashboards and Contact Center Agent Dashboards and provide insight into data that’s relevant to different profiles using the system.

#5 Break down silo mentality

To take proactive actions, the full picture should be known, whether it’s about customers or internal processes. Having siloed systems and different processes in each system does not provide the full picture. In fact, silos are a stumbling block to filling the gaps in situational knowledge needed to take proactive actions and decisions. As a result, connecting across silos and monitoring activities from end to end is critical to gain an accurate picture of emerging risks.

Rather than having different systems in place, banks can leverage an integrated software tool to provide unified and streamlined journeys, both for the customer and for the staff. And, the staff can benefit from unified views of customers and standardized processes, and can work more efficiently if they have all the information they need in one place.

# 6 Apply machine learning to customer analytics

Today, it’s no more about which product the bank wants to promote and sell. It’s rather about what the customers need and want. Customers drive the business, and banks need to offer products and services that their customers need and seek. Capitalizing on machine learning (ML) and artificial intelligence (AI), VeriTouch enables banks to transform from reacting to customer’s inquiries or requests to proactively performing and suggesting actions. And it is designed to create “wow” moments to drive happy customers and engaged employees.

This brings another opportunity for banks to continuously listen to customers and transform from a “product-centric” to a “customer-centric” organization. Because it’s high time that banks and other financial institutions adopt and leverage real-time customer experience analytics and treat their customers as customers, not numbers in their systems.

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6 December 2021
AI-AR-ML
Customer Experience
Customer Insights
Digital Transformation

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