Opportunities for cognitive computing in the banking sector can be broadly divided into three key parts:
1. Cognitive engagement: User experience (UX) is at the core of this tenet; and includes providing seamless user engagement to bank’s customers during customer-facing activities.
2. Cognitive automation: AI-driven robots and Robotic Process Automation (RPA) are playing a key role in enabling back office hyperautomation of various mundane tasks like image and text processing for form filling and straight through processing (STP) of other repetitive tasks.
3. Cognitive insight: This involves looking into various sources of structured, unstructured, and numerical data to build actionable insights for the bank. It requires processing of huge volumes of disparate data and using AI to enable near real time fraud detection and regulatory compliance.
AI in retail banking: Three key use cases
When it comes to deploying AI solutions, doing it alone can get tricky. Banks can partner with IT firms to leverage the latter’s in-house cognitive assets and AI partner ecosystem to enable these key use cases:
a) Account opening
The current process, in most banks, is still time and effort intensive (See Figure 2).