July 18, 2022
Read time: 4min
Growing data footprints, emerging regulations, AI solutions, and more will shape data analytics in financial services over the next few years. Here’s a look at how five trends will influence the changing landscape of data analytics in financial services, as the sector grapples with increasing innovation pressures alongside regulatory compliance.
Banking and insurance enterprises have always been data-heavy. But the rise of mobile banking and consumer demand for easy, instant banking experiences has rapidly driven the financial services industry’s digital transformation—and with it, massive data growth. Every transaction, click, mention, comment, and interaction across mobile apps, kiosks, social media, and webpages is collected and analyzed. The key for Financial Services enterprises is to securely collect and store the exploding volume of data but also effectively, and compliantly, extract value from big data with elevated data analytics.
Top of mind for banks and insurance firms is how to effectively leverage big data in financial services to provide highly personalized offers and recommendations. With the right tools, there’s potential for financial institutions to analyze and manage massive datasets and predict the needs of customers on a micro level. Banking and insurance firms could leverage analytics to provide exceptional banking experiences tailored to each unique patron. The shift to a customer-centric approach in financial services starts with effective data management and data analytics at scale.
With growing data footprints and hyper-personalization, banks and insurance firms are better positioned to embrace inclusive finance—a growing trend towards suitable, accessible, fair, and equitable financial products and services. Consumer data analytics in financial services can help identify barriers that lead to financial exclusion. And with those insights, banks and insurance firms can build a deeper customer understanding and better solutions for inclusive banking and insurance experiences.
Changing and emerging government regulations will continue to shape data management and data analytics in financial services. Strong yet agile data management is key for financial firms to keep up with shifting government rules and regulations and to avoid risk and loss in the future. Relatedly, as customers become more and more aware of, and concerned for, how financial firms manage customer information, financial institutions may increasingly emphasize transparency to earn customer trust, confidence, and loyalty.
With ever-expanding data footprints and changing regulatory requirements, FinServ will look to artificial intelligence for effective data management, data analytics, and compliance processes. According to Gartner, banking and investment firms will invest heavily in technology in 2022, trending towards Generative AI, autonomic systems, and privacy-enhancing computation. AI in finance has the potential to analyze the vast amount of growing data from many sources, so banks can understand their customers more and provide smarter, better experiences while also staying in step with rules and regulations in the sector.
Financial Services organizations must simultaneously deal with an explosion of new data, increased disruption from startups and neo-banks, as well as increased demand for consumer centricity in their services.
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