Two common buzz words in the financial services sector are “real-time” and “analytics.” This sector, arguably more than others, depends on speed, accuracy, and action based on the dissemination of enormous amounts of data.
According to Investopedia, the financial services sector — when compared to other industries — has widely adopted big data analytics to inform and educate, with the intention of making better investment decisions and consistent returns. Algorithmic trading, for example, uses vast amounts of historical data and pairs that data with complex mathematical models in an attempt to maximize returns.
The role of data within the finance sector comes from a “two AI” perspective:
- Artificial Intelligence
At its core, Artificial Intelligence involves the practice of leveraging the orchestration of solutions to drive automation and real-time analytics. AI and the implementation of these solutions is the result of digital transformation and continuous modernization within a financial enterprise.
- Actionable Intelligence
Once digital transformation instills the appropriate solutions, which are integrated within a larger big data strategy, financial organizations start to realize the difference between data that is simply noise and data that produces actionable direction. At that point, data becomes intelligence.
These two AI’s are imperative to the advancement of the many financial services companies that have adopted these two skills as part of their core-competence. The companies advance with the intention of gaining productivity and improved financial returns and shareholder value. They also tend to outperform their competitors.
86 percent of executives say their organizations are only somewhat effective at meeting the primary objective of their data and analytics programs.
Robo Readers and Social Intelligence
In practice, we are starting to see the leveraging of these two AIs within multiple financial services organizations. Mortgage providers, for example, are using artificial intelligence for several functions, including contract analysis, market trends, credit worthiness and risks, among a few. We are also starting to see firms use robo readers for application review and claims processing.
As a result, these companies can now execute multiple functions with greater speed and accuracy, such as:
- Reading, reviewing and evaluating documents in the fraction of time it takes humans
- Find anomalies with a higher rate of success — and not just within their data sets, but across any comparable data sets that are accessible
In a similar way, financial services companies are starting to use social media to derive the actionable intelligence that leads to better trade information. Dataminr, a New York-based technology company, for example, helps hedge funds follow the nearly 500 million tweets per day that gets posted on Twitter in order to help drive actionable intelligence.
Importance of Partnering
Whether you’re looking to integrate artificial intelligence solutions into your enterprise, or to improve your company’s access to actionable intelligence, it’s important to partner with a company that understands both AI’s.
Contact us to learn more about how you can meet your goals within financial services.