The Untapped Potential of Analytics in the BFSI segment

By Mohan Jayaraman, Country Manager, Experian India

The total lending and deposits in the India market are increasing at a CAGR of 20 percent and are further poised for growth backed by demand from housing and personal finance. Credit Bureau importance and relevance is coming across significantly with the reduced NPA’s across products. Telecom penetration, online retailing and new category banking licenses in the payments and local banking space are the key changes facing the market. These are also forcing the larger banks to look at their digital processes which will drive automation and demand for solutions.

The key focus areas for the BFSI sector to be profitable and at the same time impactful in the consumers mind are acquisition, customer portfolio management, risk management, operational efficiency and compliance. With the help of analytics, companies today are developing score card systems and using analytics to segregate customers and enable institutions to take data driven optimized solutions. On the data front, companies today are increasingly trying to use structured and unstructured data to gain a better understanding of the customer.

On the business front, companies today are increasingly using analytic tools for loss forecasting, portfolio management, peer benchmarking and to arrive at valuations for buy-outs and sell-downs. Lastly on the customer front, analytics is used to study customer behavior, assess customer credit worthiness and identify the next best product or offer for customers. Analytics helps companies group their customers by characteristics such as demographics, lifestyle, behavior, purchase history and so on. With continuous changes in business policies and external environment, every score-card also deteriorates and hence, there is always need for an expert to continuously monitor & track its performance.

With the broadband and mobile telephony on the rise and companies aiming to set up digital shops rather than the traditional brick and mortar stores, customers have begun to find multiple engagement channels to engage and communicate with organisations thus making it imperative for the BFSI sector to move away from segmentation and gravitate towards customization and thus understanding the what, where, why, which, who and how when dealing with a customer. Data analytics is increasingly used to understand consumer behaviour across the banking and financial services, insurance and e-commerce sectors.

According to Nasscom, India’s big data outsourcing opportunity is projected to reach around USD 1.2 billion by the end of the year 2015. Having said that, big data initiatives are at their infancy in India and organizations are yet to explore the full potential of big data and the value it brings to them.

Most Indian organizations are still grappling with the amount of data they generate. The early adopters of big data are expected to emerge from sectors such as BFSI, retail, hospitality and media. The challenge faced by most sectors is to analyze the data collected and identify new opportunities to store them securely and affordably.

Financial institutions as well as insurance companies are facing challenges like customer identity authentication. Through structured data, financial institutions can leverage on information collected and developed by analytics firms thereby making it more actionable. It is not only about knowing the customer's value to retain them for future but also using big data to effectively manage delinquency rate as well as fraud detection.

In the financial services sector, the benefits of the big data initiatives are likely to translate into a better customer experience, operational efficiency while reducing fraud and thus losses. Economic customer acquisition and persistency are the big challenges and big data initiatives will definitely help in managing these problems in a data driven manner. Leveraging developing data sources like the Credit Information Companies in conjunction with internal data initiatives will help the insurers’ structure data better to make it actionable.

Organizations are now realizing the value of big data Analytics in mining customer preferences and propensity as well as in devising technologies that deliver actionable strategies to the front end. As far as pricing goes, big data will help in optimizing the risk segmentation leading to better pricing structure. Better insights into customer segments and preferences can also help in developing innovative and customized products and services while also helping insurers channelize their resources in a more effective and organized structure.

Large capital spends is not a requirement to derive benefits from organizational data resources. Often simple data marts focused on specific use cases can drive value in the organizations and may be the appropriate starting points to get the business teams in readiness to accept increasing levels of complexity of analytics solutions.

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