In financial services, chatbots are becoming a buzzword on par with Big Data, Machine Learning, and Artificial Intelligence. In fact, some companies market their chatbots using this holy trinity of buzzwords: “Machine Learning, Artificial Intelligence systems to leverage Big Data.” The truth is that chatbot marketing is well ahead of the technology itself. Often, we are sold this idea of how wonderful chatbots could be for our business, but in many ways, the technology falls short. So why do chatbots fail in finance? Read more

The big headline at the Gartner Data and Analytics Summit this year was about highlighting the value of data and analytics solutions as well as developing a culture of data enablement. While these concepts shouldn’t sound new to most of you, it should make you feel a sense of urgency to go beyond just doing analytics for analytics sake. You should be achieving tangible business goals. After attending all the talks and hearing the buzz around the event floor, here are our top 3 technology takeaways from the Gartner Data and Analytics 2018 event. Read more

Imagine what you could do with an extra 13 hours in your work week? What if automating written reports could give you 30% of your work week back? According to McKinsey, “60 percent of occupations could have 30 percent or more of their constituent activities automated.” With the technology available today, many of the monotonous, data-driven tasks could be automated, freeing up your time to focus on more interesting, creative tasks. Finance in particular is an industry where automation technology is being adopted across the board. This is no surprise as finance in particular relies on providing results quickly, incorporating large amounts of data, all while taking into consideration the changing regulatory financial landscape. To give you an idea of specific examples, here are the top 4 use cases when it comes to automating written reports in Finance today Read more

The AI market is expected to grow to $9.88 billion in 2022, from last year’s figure of $2.61 billion. So how can solution providers take advantage of this growing market and increase adoption rates? The answer is simple: providers need to start presenting their solutions in the context of real-world business problems. If you think about it, AI is one of the only technologies on the market where the conversation is dominated by technology not AI business use cases. For example, why are we talking about Machine Learning, Neural Networks, etc when we could be talking about uses? Imagine if Apple only sold the iPhone by talking about complex processor specifications? This tech-driven approach makes no sense for business looking to adopt AI since they are lost in techno babble, and it makes no sense for AI companies either. Businesses aren’t going to move forward with a “technology that solves everything” – they want to fix a certain pain point or focus on achieving a particular goal.   Read more

Today, AI is truly everywhere. From phone apps to advertising, to home devices like Alexa and Google, AI already has a strong influence on our daily lives. From a business perspective, this holds true for both B2B and B2C companies. AI is helping drive businesses to make better use of data and help decision-making. As we look forward to 2018, here are our predictions for what AI business trends you will see over the upcoming year: Read more