How Artificial Intelligence Can Support Financial Firms
Financial services firms aren’t short on data. Thanks to advances in data collection, curation and analysis tools, financial companies now have in-depth information about client preferences, transaction trends and security risks. This massive amount of data, however, comes with its own challenge: a lack of context. Without context, data can deliver operational value but stops short of being transformative.
AI can help firms reshape data management in three key areas: fraud detection and prevention, risk management, and customer service.
Artificial Intelligence Can Help Banks Detect and Prevent Fraud
The ability of AI to detect patterns and learn over time makes it an ideal candidate for improved fraud detection and prevention.
For example, AI tools can be used to identify the telltale signs of internal fraud, such as employees requesting access to large amounts of data, or exfiltrating this data offsite. AI is also well suited to detecting external fraud; for example, identifying spam or phishing emails before they reach employee inboxes.
In addition, AI can help banks reduce the risk of client identity theft. By synthesizing what firms know about customers into a single, unified profile, businesses are better prepared to detect potential deception.
How AI Helps Banks Manage Risk and Reduce Threats
Balancing risk is a core component of success in financial services, and AI has become an indispensable tool. Lenders use it to evaluate potential clients’ creditworthiness.
Firms might also use AI to evaluate investment decisions. By combining historical data, current information and future trend predictions, AI makes it possible to better understand an investment’s impact over time.
How Banks Can Better Customer Service with Help from AI
Financial services is one of the industries in which chatbots have become ubiquitous. Modern versions of these AI-powered digital assistants are effective at understanding customer requests, context and even tone of voice, allowing companies to deliver customer service at scale.
Some firms are also using AI to gain insights into customers’ needs and preferences, allowing them to offer more personalized services and products.
How Can Your Bank Best Implement AI?
While AI itself offers opportunities, many banks still encounter barriers to implementation. Some of the most common include:
- Lack of internal expertise: Effective implementation of AI requires experienced data scientists, developers and user experience experts, all of whom are in short supply.
- Uncertain ROI: The connection between AI investment and ROI isn’t always clear. Depending on where AI tools are implemented — in the cloud, on-premises or both — and how they’re used, ROI can vary significantly.
- Lengthy time commitment: The scope and scale of AI projects often mean they can drag on if not managed expertly, resulting in projects that are aspirational rather than operational.
- Legacy frameworks: AI adoption is often slowed by outdated code or proprietary on-premises technology.
There’s no denying the impact of AI on financial services. Maximizing the benefits of AI, however, means discovering where current barriers impede adoption. Teaming up with an expert partner can help determine what’s viable, what’s not, and what comes next.