A contextual banking experience is the intersection area between bank offerings and customer needs. To execute this well, a robust data strategy is key. Contextual banking allows financial institutions to anticipate consumer demand and upsell or cross-sell products directly. It is what delivers the seamless experiences demanded by consumers and talked about by bankers and credit union executives.
Personalization
A key factor in contextual banking experience is the ability to deliver a personalized experience for customers. This involves knowing what they want, when they want it, and how they want it. This approach is already being used by companies like Google and Apple, but banks can also take advantage of it. Banks can implement contextual banking by upgrading their data analytics capabilities. They should also focus on their customers and develop a customer-centric business model. This will allow them to create seamless experiences that elevate customer satisfaction.
Contextual banking uses data to refine how transaction banking services are provided to customers. For example, if a customer has a low balance in their account, the contextual model could recommend a credit solution to fix it. This type of personalization improves performance and brings better results for the customer, as shown in a McKinsey study. It can also reduce costs and risks for the bank. Learn more about contextual treasury in our on-demand webinar.
Transparency
If your financial services are based on contextual insights, it can help you anticipate your customers’ needs – not just in the way they think but even before they realize them. Imagine, for example, that your customer’s bank app detects a shortfall in their account due to an unscheduled big payment and offers them a credit solution before they even notice the deficit themselves. This type of hyper-personalization is only possible with contextual banking. And it’s the only way to create a relationship with your consumers that is rooted in trust and relevance.
To deliver on contextual banking, a bank has to be ready in three key areas: business goals and opportunity discovery, data foundation readiness, organizational and technological readiness, and ecosystem partnerships to ingest or provide functionalities and data. To achieve this, banks should also consider collaborating with fintechs. As we discussed in our article on embedded finance, this is a great way to manage the complexity of contextual banking.
Artificial Intelligence (AI)
The cash management system is comprised of different actors. These include the bank itself with its core and embedded banking capabilities, fintech partners, digital companies, and ecosystem partners. Banks are aiming for a high level of personalization and seamless experiences across channels. To accomplish this, they must use data-driven tools broadly and provide a consultative relationship to customers. One way to do this is through context-aware, smarter technologies like AI.
For example, let’s imagine Maggie is searching for her first home. She can ask her bank app, “Can I afford this neighborhood?” It responds with a detailed analysis of the suitability of the area based on schools, crime, walk score, taxes, etc. This type of personalized, contextual service is the future of banking. In this context, AI is a key technology that can help banks build the right products and services for their customers. AI is also a crucial component in embedded banking. This is where banking happens as a by-product of the customer’s normal business, such as when a landlord opens a virtual account for each property or a lawyer keeps track of client cases in escrow.
Embedded Finance
The emergence of embedded finance is changing the way customer’s access banking products. By integrating financial services into a customer’s normal non-financial journey, embedded finance offers more simplicity and convenience than traditional methods. It also allows for more assertive offerings that are better suited to the customer’s needs and consumption habits. One example is invoice financing, which allows businesses to plug sizable cash flow gaps in their balance sheets by advancing the value of outstanding invoices. This enables them to pay contractors and suppliers faster than they would have been able to if they took the longer route of applying for a loan or overdraft.
To compete with embedded finance, banks need to rethink their product offerings and capabilities. They will need to embrace new platform business models, as well as harness partners as assets to open up new distribution channels and amplify complimentary offerings such as treasury management. They will also need to get comfortable with platforms and enablers making credit decisions that affect their traditional balance sheets, based on real-time and contextual data held outside of the bank.
Conclusion:
In the fast-paced world of banking, the concept of contextual banking experience is a game-changer. By harnessing data, artificial intelligence, and seamless interactions, banks can offer personalized, real-time solutions tailored to individual customer needs. This approach is ushering in a new era where banking is not just a service, but a truly responsive and anticipatory experience, making managing finances simpler, more intuitive, and customer-centric.
