Meeting customers needs and behaviour with data analytics
Data analytics has become the key determinant in predicting customer needs and behaviour.
Data analytics is transforming the banking and financial services industry. The rapid rise of big data, faster computers and innovative technology in analytics has resulted in a range of new opportunities for banks and finance teams to understand past results and efficiently measure current trends and patterns for the future. Today’s banks use data analytics to control a range of challenges including fraud detection and credit risk management but more focus is needed on converting data into actual insightful decisions. As customers become less attached through new technology and innovative tools, banks and financial services will need new ways of generating information on customer behaviour. Implementing new analytical techniques, banks can understand and measure customer’s requirements for banking products and services at a particular time with relative accuracy.
In recent years, data analytics has transformed the functions of financial businesses. Predictive analysis, smart customer management and AI driven solutions have enabled companies to manage potential risks more effectively and improve overall customer experience, improving overall profits. In particular, developing regions have found real value in analytics in generating a more inclusive system for an imbalanced financial market. Deep learning and Natural Language Processing tools are allowing for more detailed interactions and languages. Digitalisation and data analytics is expected to support the rapid transformation of conventional techniques of working in finance.
Big Data and analytical tools can allow financial institutions to improve their credit underwriting processes by accessing new data sources, such as e-commerce transaction data, social data and other sources, allowing a clearer idea of risks for customers with lower credit scores. This allows banks to select credit valued customers from a potential list of people that may never have acquired credit because of insufficient details for banks to measure their risk because of lack of sufficient information for banks to assess their risk.
We also see an opportunity for expansion in breadth of analytics usage from traditional focus areas of risk and marketing into hitherto untapped avenues of – HR (to improve the effectiveness of employee recruitment and retention), Compliance (moving to 100% transaction monitoring instead of traditional sample-based testing approach to detect anomalies), Operations and Finance functions.
According to research at EY, there are three core areas where financial services businesses are seeking investment to develop new capabilities in data, infrastructure and people:
Data: Data lies at the core of analytics-driven innovation. Companies are investing in not just integrated existing data source within one place but also attempting to understand new data sources for creation. There is a strong emphasis on finding new data feeds, such as social media channels to further strengthen the entire insight generation system.
Infrastructure: In order to manage ever-changing data sources, including the range and volume means businesses need to improve their infrastructure. Financial businesses are now more willing to work with open source tools and cloud-based platforms.
People: people skills are essential for utilising the data and creating the infrastructure to give a business that competitive edge. Companies are investing heavily in finding and hiring the right talent for their business. Most companies are using a combination of in-house talent blended with external systems to manage the continued changes in the market.
Understanding customer behaviour on an individual basis and when to make contact is a challenge that can be solved via AI platforms. This requires a visionary team and people collaborating across an entire business. Another particular challenge is real-time involvement. Nearly all financial institutions still rely on batch processing for customer interactions. Transforming this process to real-time will improve the overall outcome as well as enhance the customer experience. Other industry professionals highlight that financial businesses need to shift their focus away from products and to establish a customer-focused strategy.