AI Articles and Analysis in Finance

Customer experience (CX) teams often face a complicated puzzle when it comes to budgetary decisions and resource allocation within their organizations.

MetLife is a leading global insurance company headquartered in New York City. It provides its customers various insurance and financial services, including life insurance, health insurance, retirement plans, and investment management.

AI is revolutionizing how companies conduct operations, serve customers, and manage risks – driving a USD 20 Billion investment in AI capabilities among BFSI firms last year. As AI continues to transform the industry, financial services organizations will seek to build effective AI teams to stay ahead of the competition. 

Goldman Sachs was founded in 1869 and joined the New York Stock Exchange in 1896. Since 2016, Goldman Sachs has begun moving into consumer financial products. The company is headquartered in Lower Manhattan with regional offices in England, Poland, Hong Kong, Tokyo, Bangalore, and on US soil in Dallas and Salt Lake City.

Proving the economic value of AI projects remains paramount to the success and continuation of any machine learning-related project. As more companies adopt AI technologies, measuring these projects' success is increasingly important – unfortunately, proving this value is proving anything but straightforward.

PwC (PricewaterhouseCoopers) is a professional services firm that provides a range of consulting, audit, and advisory services to clients worldwide. Per its annual report, the company's revenue was USD 50.3 billion, employing 328,000 people in 152 countries.

Bank of Montreal (BMO) is a North American bank that provides personal and commercial banking, global markets, and investment banking. The bank caters to over 12 million customers with over 1000 branches. Per the bank's 2022 Annual Report, BMO earned approximately CAD 33.71 billion in revenue.

Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP).