Read the Emerj team’s latest coverage on AI use-cases and trends in banking:
ByAlicia McGarry
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…
ByRiya Pahuja
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,…
ByRiya Pahuja
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…
BySharon Moran
Traditional investors have several mechanisms for achieving their desired portfolio risk level. One of the most common methods involves the use of correlations. The more well-known 60/40 and 80/20 models…
ByMatthew DeMello
While machine learning might be as close to a household name as any AI capability in 2023, any serious historian will tell you the technology itself is nothing new. The…
ByRiya Pahuja
Voice of the customer (VoC) is a term used in modern business practices to describe customers’ feedback about their experience with the products and services both inside and outside any…
ByRiya Pahuja
As of 2023, AI and machine learning are widespread technologies in various applications and use cases throughout the financial services industry. Both demand factors in profitability needs, competition, and regulations…
ByRiya Pahuja
The concept of customer experience is reaching new heights with technological advancements. Mobile technology and applications are increasingly becoming part of consumers’ lives. The impact of technology on customer experience is growing…
ByRiya Pahuja
With so much competition in the market, it is easy for customers to switch their banking partners. Data and analysis of customers’ financial data help banks reduce churn by channeling…
ByNicholas Denittis
AI and machine learning are increasingly used across use cases throughout the insurance industry. Examples include automating underwriting, streamlining claims processing, improving customer service, and predicting customer risk. As noted…