AGE OF BIG DATA
“Big data is not about the data! The value in big data (is in) the analytics”
Harvard Professor Gary King
Everyday, new technology is bringing forth more devices that are capable of streaming data constantly about their users. Implicitly or explicitly, we are sharing information about ourselves just by using smart devices and services as innocuous as the map and search. This is in addition to all the data that is collected from our cards, phones, browsers, and social media. The fact is, we live in an age where almost every aspect of our lives can be tracked, analysed, and optimised.
For the financial services sector, the Age of Big Data is actually the dawn of hyper-competition. No one can take customer loyalty for granted because the pervasiveness of data breaks down traditional barriers. A competitor who can harness the power of Big Data better than you will be able to steal your customers with the right offer, through the right channel, at exactly the worst time for you. Furthermore, competition will emerge from new quarters as control shifts from "product manufacturers" (e.g. insurers) to a decentralised network of "channels and portals" where customers perform the critical activities of searching, planning, and decision making (e.g. Google, travel booking sites). Read this World Economic Forum report on the Future of Financial Services.
Hence, the Data Scientist is the sexiest job of the 21st century not just because in those mountains of data lies great gems that only these specialists can mine, but more so because the engine of growth of any large organisation needs to be converted to run on data, ideally real-time data. After all, isn't data the new oil? No where else is this more evident than in financial services, an industry in which PulseMetrics has accummulated deep domain knowledge and experience.
ANALYTICS FOR FINANCIAL SERVICES
Over the past decade, we have worked with multiple leading banks in the region to gain deep insights into consumer wealth and lending behaviours. Using cross-sectional observations of key events such as marriage, childbirth, income plateau and mortgage payoff, we have developed sophisticated Life Stage and Wealth segmentation models that tap on Big Data sources to enrich our clients' customer data. These models are just one of the innumerable ways that PulseMetrics has helped our clients in the banking industry to generate significant new value through innovative use of data analytics.
Insurance analytics is a mature field and PulseMetrics has extensive experience in this area. Through astute applications of analytics, we have helped our insurance clients to boost marketing response, lengthen policy persistency, detect fraudulent claims, increase product holding and enhance customer affinity. We have also optimised the effectiveness of insurance distribution channels such as agency and bancassurance. In fact, PulseMetrics has served very well in the niche role of being the analytics enabler of partnerships between our insurance clients and their partners in banking and retail. To address the relative scarcity of customer data in the insurance sector, PulseMetrics has also built a proprietary Data Enrichment Engine for the Singapore market. Using only a few basic attributes such as name, date of birth, gender, and address, our algorithm can infer many things about the context of the customer's life, such as wealth, life stage, and family structure.
By nature of their business, credit card issuers collect copious amounts of data on their customers. This brings great opportunity as well as heavy pressure because credit card companies are expected to be very savvy in using the data to serve their customers better and to compete against the flood of similar products on the market. Consumers are no longer interested in mass marketing offers that are not personalised to their needs and preferences. Having sophisticated capabilities in data analytics is now a core requirement for any consumer credit company. PulseMetrics has empowered our clients in this field by serving as their internal "data science lab". Through the years we have created many behaviour models that capture customers' psychographics (e.g. being "Family Focused") and their attitudes (e.g. being a "Spender" or a "Saver" in various categories). These insights not only enable the card issuers to create highly targeted offers, they also endow our clients with highly valuable data assets to forge fruitful partnerships with other companies (e.g. retail merchants). This is one of the ways for "internal data" to create "external value".