Posts Tagged ‘Financial Services’

If you’re reading this, it’s probably because you keep hearing that blockchain is the next transformative technology. And while you want to make sure you’re fully informed and in a position to exploit any opportunities this technology could bring to you and your organization, you still don’t fully understand what blockchain means. Moreover, based on […]

When 401(k) plans were introduced in the early 1980s, most had only one-to-three funds available. Typically, participants would find a low-income/low-risk fund (often called a “guaranteed” investment vehicle) and an employer stock fund. As the plans became more popular, the U.S. Department of Labor (DOL) determined that plan sponsors had to offer more options that […]

In an attempt to lure younger customers, JPMorgan released a new mobile app called Finn by Chase. The app will allow users to open an account, deposit checks, track spending, and perform other activities that many companies already offer. JPMorgan is testing out an iOS version of the app in St. Louis, a city where […]

In our guide titled “6 Ways to Mitigate Risk in Cross-Selling for Financial Services,” we briefly touched on the use of artificial intelligence and intelligent machines, along with comprehensive processes, to fight fraud. In combination with ‘know your customer’ (KYC) processes to help catch suspicious banking activity and reduce risk through the analysis of data […]

In the recent “Shaping Digital Finance” session at the 20th Milken Institute Global Conference, Corrie Elston, chief technology officer, financial services, Google Cloud Platform, said that a financial services institution may experience 80% accuracy in detecting fraud and 99.5% false positives. As mentioned earlier, only about half of money laundering or terrorist financing incidents were […]

One of the buzzwords in the financial services industry is “machine learning.” While even among experts in the field there is no single accepted definition of machine learning, in simplest terms, machine learning focuses on the use of technology (often referred to as artificial intelligence or cognitive computing), to find solutions through continuous learning. It’s […]

While anti-money laundering (AML) programs may present the biggest opportunity for machine learning to thrive, there are many issues when it comes to fighting money laundering. The number and high caliber of resources required to battle fraud in today’s highly regulated environment are immense, and the cost – of both personnel and technology required to […]

According to the U.S. Department of the Treasury’s Financial Crimes Enforcement Network (FinCEN), “Money laundering is the process of making illegally gained proceeds (i.e., ‘dirty money’) appear legal (i.e., ‘clean’). Typically, it involves three steps: placement, layering and integration. First, the illegitimate funds are furtively introduced into the legitimate financial system. Then, the money is […]

Business intelligence (BI) technologies enable wealth management firms to analyze raw data, with the goal of improving decision making, enhancing client relationships, increasing operational efficiency, and adhering to legal and regulatory compliance mandates. A properly designed BI framework can provide financial services companies with a rich, intuitive user interface that enables business users to run […]

There are many considerations when it comes to the development and operation of a business intelligence (BI) program, especially when it is specific to certain sectors of the financial industry like wealth management. Nonetheless, there are several fundamental beliefs wealth management firms should embrace as they pursue their BI efforts: BI is a powerful tool […]

Good day and welcome to my blog spot! That simple opening can help set the tone for whatever your message is to follow. I could just have easily opened with: You can permanently damage your eyes by staring at the sun for a minute and a half. My opening was a bit more casual and […]

The process of implementing a business intelligence (BI) program varies based on the scope. A comprehensive, enterprise-wide BI program typically starts with an assessment phase to identify the data domains, systems of record, core data elements, and analytical requirements. Some level of process flow analysis may also be required to understand the origin and usage […]