Financial services organizations can gain a unique advantage by effectively using data, given both the nature and the enormous volume of data that is available to them. Using this data, every aspect of a customer’s experience can be improved upon—from providing a seamless experience across multiple channels to customized products and personalized wealth management.
As new data sources become available, data science enables banks to be more data-driven in their decision making, and at the same time empowering their customers to do the same. A bank’s risk management practices and functions, including fraud detection, credit scoring, anti-money laundering, and financial crime prevention and stress testing can all be materially improved. Emergence of new data sources and competition from fintech firms has also presented opportunities for innovation and for creating new business models, go-to-market strategies and monetizing different data sources.
When navigating this industry, you must keep several things in mind:
- Data science presents unique opportunities and hurdles for the financial services industry. Getting it right offers a huge competitive advantage, while getting it wrong can be very costly.
- Be strategic about your data science adoption and investments.
- Making the right data engineering investments in a rapidly evolving landscape is challenging. Be sure to seek the proper technology expertise.
- Prioritizing and undertaking the right data science projects is paramount to get the expected business outcomes and return on investment. Strategic choice of data science projects can often address a number of high value business use cases simultaneously, allowing greater progress. Data science initiatives often fail or fall short of expectations due to lack of coordinated vision owing to competing priorities.
The links below illustrate how some financial services organizations are using data science and big data analytics to innovate and improve their products and services and become more data-driven. They also highlight some of the key challenges and open questions.
The Force Awakens: Data Science in Banking—”Big data could transform businesses and economies, but the real game changer is data science.” This article discusses how banking can approach the data revolution.
Big Data & Analytics Drive Profits—In part one of a three-part series, Vamsi argues that banks must adopt new organizational models to fully take advantage of data’s benefits.
Data Analytics Critical to Success in Banking—Banks need to embrace data analytics if they’re going to be successful in the modern marketplace. So what is holding them back?
HSBC’s Peter Serenita and BBVA’s—”The question is: can the banking world keep up with the astronomical speed at which data science tools are evolving?”
Analytics, ML and Data Science Help FinTech Offer Better Services—This article looks at how fintechs are using, or not using, data. Some of the areas examined include credit scoring and customer acquisition.