AI in Focus: Financial Services


Global investment in artificial intelligence across the banking industry is predicted to reach $3.3B in 2018, trailing only the retail industry. Given the quantitative and data-driven nature of financial services—as well as its need for regulatory adherence—it is not surprising that the sector is gearing up for major investment in AI.

Here are three trends we’re seeing in our client work that are evolving the industry now:

__Supercharging Customer Engagement and Loyalty__
As in other industries, AI tools utilizing real-time predictive analytics, machine learning, and natural language processing are being applied to customer-facing touchpoints to grow engagement and loyalty. While it may seem unintuitive to leverage artificial intelligence to interact with humans, the proliferation of AI chatbots in financial services provides a centralized and always-on service tier that shortens service interactions and increases customer satisfaction. Through better algorithmic identification of purchasing signals mapped to customer profiles, AI also enables companies to offer sophisticated and relevant personalization of communication and offers. Engaging potential customers at the right time in their user journey–and with the right product–can build valuable loyalty and trust for a given financial services brand.

__Sophistication in Qualification__
As computing power multiplies and big data analysis grows more complex, financial institutions are increasingly better equipped to qualify transactions. By using data science to assess a potential borrower’s entire digital footprint, companies can accel beyond typical metrics like FICO scores to determine creditworthiness, particularly of those with little credit history. Similarly, advancements in machine learning have increasingly automated instant fraud detection and streamlined detection performance. Traditionally, the predominant rule sets in fraud management were human generated. As artificially intelligent computer systems grow in capability, they could autonomously predict, act, and iterate without preprogrammed rule sets. This enables an increase in amount of data analyzed and real-time decisions reached, as well as a decrease in processing time and cost.

__RegTech__
With technological advances growing both the number of fintech companies and the damaging effects of fraud and cybersecurity breaches, there’s also a sharp increase in regulatory and compliance oversight. Regtech sits at the intersection of financial institutions and regulatory bodies, using technology to help companies meet compliance standards and risk management protocols. Investments in regtech startups have reached $5B over the past five years and for good reason. These startups are purporting to use machine learning, data science, and cloud computing to bridge the compliance gaps in legacy infrastructure, saving costs, and lowering risk for financial institutions.

Each of these applications of AI promise to make the financial services industry more streamlined, effective, and attuned to customers’ needs. And AI will only get exponentially more sophisticated.

That said, while retail and logistics industries appear ready to embrace fully autonomous AI that requires no human intervention, such adoption may not be so simple in financial services, where the human touch has long been associated with trustworthiness. In an industry where the global economy hangs in the balance, financial services professionals must navigate an increasingly complex world with an arsenal of AI tools without alienating its consumers or experiencing any product downtime.

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