There’s been much buzz around conversational AI and machine learning-powered CRM.
To throw the sharp light of reality on AI in the UI, Celent launched its inaugural AI in the UI Request for Information (RFI), which benchmarks current and future adoption, the prime use cases, and the underlying business cases. Our findings shed a promising light.
To date, much of the AI energy and success in corporate banking have been concentrated in back-office operations such as payments and trade finance processing, fraud detection, and compliance. In the middle office, AI has been driving step change in small business credit underwriting, commercial loan negotiations, booking, and monitoring. In functional areas, AI is making efficiency inroads, particularly in accounts receivable processing. AI is now ascendant in the front office. We found that a slight majority of total use cases supported by vendors in production are employee-facing (54%). We had similar findings for proprietary solutions based on conversations with vanguard banks. These findings are not surprising given the relative complexity of implementing customer-facing AI in corporate banking compared to retail banking. While use cases are primarily basic customer support-related (e.g., “tell me”) more advanced use cases are increasingly being launched (e.g., “advise me”). It follows that the primary business case is cost savings. Improving customer engagement, however, is increasingly a goal.
Based on our findings, we are publishing two series of reports, one covering corporate banking (includes small business to multi-national corporations) and the other covering retail banking. We recently published the first report in the corporate banking series. The next report, which reviews vendors offering front office AI applications, will be published in June. The third report will cover pacesetters including banks, solution providers to banks, and third-party providers to businesses.