Technology expert, FinTech leader, co-founder and CTO of Hexaview Technologies
While online banking has made customers expect first-class services regardless of time and location, embedded finance and open banking have raised the bar even higher. With embedded finance, the non-banking firms enable their clients to get credit through their platforms. On the other hand, open banking allows third parties to access financial data through APIs. With the rise of such banking activities, customers expect their banks to anticipate their needs and wants.
For example, a bank should offer a personalized car insurance policy to its customer after purchasing a car or propose budget tips for savings accounts. Such innovations in banking and finance have taken the data game to a whole new level. The banks and other financial services must use additional data collected from outside sources to meet their growing consumer expectations.
The 2019 Salesforce Report (including 8,000 business and consumer buyers worldwide) report that 84% of consumers believe a customer experience is just as important as the products and services offered by a company. Therefore, banks and other financial services companies must adapt to innovative business models to serve their customers based on their preferences and needs in today’s digital world.
Importance of data collection and optimization
In this high technology era, people are more willing to share their personal data/information by leaving reviews, marking locations, creating accounts on social platforms, etc. Such willingness and tolerance for risk sharing personal information delivers a huge amount of data from multiple channels. This sharing of data through external sources opens up new opportunities for financial service providers.
How deploying data-driven capabilities can help financial services
Let’s take a look at some data-driven changes you can make to drive value.
• Digital products and services
Financial services firms can use the data they collect about customers to create new and innovative products and services to drive revenue streams. It can take many forms, such as using data to partner with non-banking institutions to develop a network of services. For example, a bank could partner with a car organization that allows customers to purchase a vehicle directly from the bank’s website. You can also monetize data by collecting customer behavioral data and understanding RMs.
† Increased efficiency
Collecting and optimizing data can help financial services streamline and optimize their internal processes using robotics, artificial intelligence and machine learning. As a result, financial services companies can reduce operating costs and improve overall performance. They can use their customers’ data to reduce operational risks and lower processing costs.
There are several ways to create a hybrid workforce of machines and people; use automated data to remove processes or upstream issues; and stimulate robot automation with artificial intelligence to allow machines to make value judgments. Moreover, by using offline and online channels efficiently, banks can increase their number of customers.
To gain real-time customer insight, banks can segment their customers using available data (e.g. customer profiling, analysis of transaction patterns, past and immediate customer behavior). By doing this, it is possible to predict the products or services that customers are most likely to buy next (i.e. predictive analytics), allowing banks to determine the next best offers and determine other possible actions.
One of the key benefits of collecting and optimizing customer data is achieving data-driven personalization.
Banks can use the data they collect to tailor their products and services to a customer’s personal needs. This can involve tailoring pricing, aligning necessities with services, insights to increase financial well-being, etc. As a result, this personalization can increase customer engagement and thus revenue.
• Increased turnover
Financial services can view behavioral trends, market trends and internal process efficiency of their customers by collecting and analyzing real-time data. For that reason, banks can gain a competitive advantage because they can identify and anticipate new business ventures and retain and acquire new customers.
Banks can maximize revenue by identifying their customers’ willingness to pay using advanced and AI-driven data analytics. This can significantly improve the accuracy of pricing models and reduce the need for “best estimates” when pricing a new product or service.
Financial services can make more informed decisions in the future by collecting and optimizing customer data. For example, some important steps have been taken using AI to predict more sophisticated financial crimes. This data-based forecast can help financial institutions detect fraud, extend credit decisions, improve collection strategies, predict liquidity needs, mitigate risk and reduce costs.
For a financial institution looking to be a top player in the industry, AI can help it get there, whether it’s providing 24/7 financial guidance through chatbots powered by natural language processing or personalizing wealth management solutions.
Financial institutions can also leverage AI to maximize sales by improving their cross-selling efficiency. By building predictive models on existing customer behavior data, companies can create more relevant cross-selling offers for each customer.
† Improved risk management
Financial services can reduce compliance risks by ensuring reliable data, which is essential for regulators. These regulators can create and evaluate risk profiles to improve fraud detection and credit management. By taking a robust data-driven approach, financial services can also extract valuable insights from it through powerful analytics. Such insights can help the financial industry better understand customers, accelerate decision-making processes and improve business processes.
Data is constantly changing the current landscape of many industries, including the financial sector. Many banks and financial institutions have started using data analytics to gain a competitive advantage. At the moment, data analysis offers new opportunities for the development of banks. Financial institutions using this technology can better understand their customers’ needs and make the right decisions.