How data unlocks new levels of customer value in financial services
By InterSystems
Demand for personalised banking experiences has exploded due to recent advancements in technology that have created a shift in customer preferences and expectations. Today, customers want you to do more than call them by their first name. They want you to proactively offer the right services that progress beyond transactions, and they expect this type of personalisation at every touchpoint. This is particularly crucial as banking customers are turning to mortgage lenders and wealth managers to help them navigate financial challenges that have emerged as a result of global events.
Financial organisations now have an unprecedented opportunity to use data they already hold that can provide in-depth insights into customer behaviours and needs. From there, applications for many financial products and services can be streamlined, saving time and resources while delivering greater levels of value to your customers. This leads to stronger personalisation in customer engagements that correlates with better customer relationships, which is critical to retaining loyal customers and acquiring new ones.
Unlocking the value of data to become more customer-centric is the key to sustaining faith in financial services. However, many financial organisations, perhaps even you, struggle to create value from data, especially when you have staggering amounts of it. In fact, with so much data to sift through, 38% of Australian financial service organisations are using data that is between one and three days old, and a further 13% are using even older data from four days to one week old.[1] The good news is that there are some simple ways you can use your business data to improve your customer experience strategy:
- Personalised products and services: the amount of data generated from credit card transactions, ATM withdrawals, and credit scores is enormous. You can use this trove of information to gain deeper insight into your customers’ needs to personalise targeted offers. For example, you could design cheaper and better services such as targeted insurance products for irregular-income, gig-economy workers.
- Customer behaviour patterns: predictive analytics extracts information from data and uses it to predict future trends and customer behaviour patterns. You can use data to predict what products or services your customers want now, what they want next, and how loyal they are based on their current customer behaviour. When you can predict how your customers behave, you’ll be able to reduce customer churn, encourage loyalty, and meet evolving customer demand.
- Cross-selling opportunities: you can use data to identify what your customers need, and tailor offers based on the activities in their accounts. This provides cross-selling opportunities that nudge customers to experiment with different product combinations with attractive rewards, such as cross-selling instant loans to credit card holders.
- Fraud detection and prevention: leveraging data to keep pace with changing consumer behaviour is key to identifying your customers’ steps in their banking journey. It can also help prevent fraud attempts in personal and business banking. For example, you could recognise an unusual transaction and, due to instant data insights and analysis, take even faster actions to stop it. This will go a long way in retaining customer loyalty and reducing regulatory risks and financial losses for the bank.
- Insight into internal processes: data-driven decisions don’t just improve the customer experience. You can view data regarding your firm’s internal process efficiency and use it to optimise existing processes or develop new ones. Data insights can also be used to better comply with regulations and help reduce the risk of fines due to regulatory breaches.
Customers have big expectations about financial organisations and banks understanding their needs. But, unless you have a crystal ball, it’s often hard to know what your customers want. When you discover valuable insights from your data pile, you can progress beyond traditional transactions to build long-lasting relationships with your clients. After all, customers are increasingly searching for a reliable and long-term partner that meets their needs rather than just a one-off banking transaction.
However, as the bank of data grows, financial services firms struggle to track and anticipate customer interactions, creating challenges in developing customer-centric strategies. A next-generational architecture that lets you build an enterprise-level data fabric that harnesses and harmonises data across the entire organisation is an effective way to achieve customer-centricity at every touchpoint and every step in the buyer journey.
If you couple data and digital innovation to place customers at the centre of your decisions, you will continuously uncover new business opportunities and new ways to engage with your customers. For example, you will not only know the name of your customer, but you’ll also know if they’re a frequent flyer, a young couple ready to buy their first property, or a farmer looking to expand their business. Once you gain a better grasp on your business and customer data, you can better understand the inherent needs of your customers, which is the secret to realising customer-centric solutions and services that sustain long-term business success.
[1] https://intersystems-finance.com/top-data-lob-apac/
