Data-driven Banking

Banks have a competitive advantage because of the quantity and quality of the data they hold. Information such as customer’s spending habits, mediums of investment, response to marketing campaigns, and more make banks the custodians of a wealth of data.

An understanding of what data sources to use, can drive improved approaches to decision-making. Traditional banks need to respond by seamlessly integrating all of their services to become a modern 360° financial partner for their customers. The ability to predict customer needs, offer personalized financial products and services, mitigate risks, and comply with ever-expanding regulations will be key to any bank's success. This cohesive strategy implements modern data architecture, which leverages large volumes of data from many sources.

Becoming a Digital Bank does not happen overnight and does not happen by implementing a single innovative solution. In order to be truly digital and ready for future challenges, a bank needs to have a comprehensive digital strategy with defined tactics. Data-driven, high-quality experiences and insights on customers are the key for a bank to establish a relationship with customers and become their trusted advisor.

Artificial Intelligence Tools for Customer Experience

Artificial Intelligence (AI) is increasingly critical to banking services and will enable banks to drastically improve customer experiences.

With AI, banks can increase labor productivity and obtain competitive advantages. AI tools like [ChatBots and Virtual Assistants](link to Weaver Financial Page) are already widely used to improve the customer experience, while [Robotic Process Automation (RPA)](Future post about "What is RPA?/How RPA is going to change efficiency") plays an important role in cost-cutting and improving efficiency.

The main needs banks need to address are:

  • Real time decision making
  • Personalization
  • Advanced predictive analytics
  • Seamless customer experience through all channels

A bank that reacts to customer needs in real time and offers the right products/services on the customer's preferred channel will become the first choice when it comes to banking, and thus emerge as the market leader. Those that fail to fully embrace AI and the benefits of data analysis, on the other hand, risk being left behind. By observing and addressing customer needs, banks can maximize their retention rate, attract new customers, and accelerate into the digital future.

The Role of Artificial Intelligence in Data-driven Banking

According to global research conducted in the banking industry, applying Artificial Intelligence results in a 40% increase in labor productivity. Research also shows that 47% of digitally mature companies already have a clearly defined AI strategy, and 84% of businesses believe that AI will enable them to obtain a competitive advantage. AI tools like ChatBots and RPA have the potential to significantly benefit all business segments: front-office, back-office and regulatory compliance.

ChatBots need to be trained to have complex, human-like conversations, and to be able to adapt to all languages. The main goal of ChatBot platforms is to become a Personal Financial Advisor to the customer.

Next Generation Relationship Platforms need to continue where traditional CRMs leave off. They must go beyond simply managing information, by automating customer journeys and transforming engagement across all channels.

Innovative Real-Time Decision Hubs and user-friendly front-ends are some of the platform components that can elevate a bank's level of productivity. CRMs have to enable sales and marketing automation, lead management, and the optimization of processes, all while increasing customer engagement. A unified platform enables banks to provide an [opti-channel experience](How an Omni-Channel Can Elevate you Customer Experience Above Multi-Channel) to their customers, and empowers building long lasting relationships with customers.

Customers now demand optimization and a seamless experience across all channels. Due to the fact that customers expect to be targeted on the right channel, with the right product, CRM systems are crucial in banking. With a 360° view of the customer, predictive analytics, and process automation, banks can provide a robust customer experience across all channels.

Steps to Becoming Data-Driven Bank

The first step to becoming a data-driven bank is, of course, to use all available data.

The next step is to make this data and results of analyses available to the customer. By doing this, banks provide added value, increasing customer loyalty and empowering cross-selling. For example, by informing a customer that they are spending more on food than usual, the bank is following a customer-centric approach and providing tremendous added value.

Financial institutions hold immense knowledge, and the platforms they implement need to leverage that knowledge and expertise. For example, user stories on ChatBot platforms need to adapt to flow changes in real time. When a bank sends a generic email campaign (outbound campaigns), conversion rates are often as low as 0.8%. On the other hand, when customers interact with ChatBots (inbound campaigns), the conversion rate has been shown to be as high as 80%.

Customers have become desensitized to generic campaigns, and channel preference is drastically shifting in favour of data-driven, adaptive experiences.

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