banking


Banking for Humanity: Technology to Increase the Human Touch

#artificialintelligence

Banks have been struggling with the concept of being more personal with their customers. 'Banking for Humanity', a concept explored by fintech guru Chris Skinner, is considered as a remedy for this; with new banking technology innovation spearheading the way for banks to adopt a human touch and be more empathetic. Chris Skinner stated that the concept is about "how banks can make their services more human". According to Skinner, there are five primary aspects for discovering Banking for Humanity: financial literacy, financial inclusion, financial wellness, financial capabilities for the vulnerable, and promoting sustainability. However, with the aftermath of the financial crisis earlier in the century, lack of confidence and trust is prevalent amongst customers.


A GLANCE VIEW OF AI TECHNOLOGY IN 2020

#artificialintelligence

The technology of today is advancing rapidly in every aspect of society both positively and negatively, making it subjective, changing our lives with high efficiency of operation, and simplifying access to various facets. While it has improved quality of life in specific ways, for the most part, it has only given an illusion of enhancing the quality of life without actually doing so. Society is dependent; instead, it works on technology. We use technology in our daily life, and demands increase exponentially due to its ease of use. Everything that exists has pros and cons.


AI Facial Recognition and IP Surveillance for Smart Retail, Banking, and the Enterprise

#artificialintelligence

Facial Recognition technology detects faces in the camera's field of view and matches them against faces previously stored in a database. Anti-spoofing is provided through liveness testing without the need for a stereo or a 3D camera. Face Recognition technology is now taking a further step as it is being combined with IP surveillance. Gemalto, a part of the Thales Group and a company that focuses on Digital Identification and Data Protection in order to counter the two root causes of cyberattacks, identity theft, and unencrypted data, defines Facial Recognition as the process of identifying or verifying the identity of a person using their face. It is a technology that captures, analyzes, and compares patterns based on the person's facial details.


The 5 Hottest Technologies In Banking For 2020

#artificialintelligence

In the movie All The President's Men, Woodward and Bernstein meet their informant in a parking garage and are told: "Follow the money." If you want to know which technologies are hot in banking, you should do the same. The truly "hot" technologies in banking are the ones that financial institutions invest in--which are not always the ones the pundits talk about. At the end of the past six years, Cornerstone Advisors has surveyed financial institutions to find out where their technology dollars will go in the coming year. In the new What's Going On in Banking 2020 study, the top five technologies for 2020 are: 1) Digital account opening; 2) P2P payments; 3) Video collaboration/ marketing; 4) Cloud computing; and 5) Application programming interfaces (APIs).


IoT in Banking: Examples of IoT solutions in finance

#artificialintelligence

Banking is becoming more convenient thanks to the Internet, and the future of the banking industry is growing increasingly digital. Whether discussing the future of retail banking or the future of mobile banking, technology is playing a larger role in our everyday transactions. The Internet of Things (IoT) is part of this rapid evolution toward the bank of the future, and both consumers and financial institutions need to adapt to these retail and mobile banking trends. Below, we've detailed the past, present, and future of the banking industry as it relates to the IoT, and how these emerging technologies will transform the way we conduct our financial business. Retail banks have actually been using an early prototype of an IoT device for decades: the automated teller machine (ATM).


Machine learning as a service: serving reusable ML models - Codemotion

#artificialintelligence

Artificial intelligence and machine learning are huge topics at the moment. So, when I saw the title of this talk at Codemotion Amsterdam 2019 I was intrigued. The talk was given by three developers from ING, who build components for the rest of the business. Read on to find out how they managed to create a solution that can efficiently serve ML models across multiple teams. Effi Bennekers, Pierre Venter and Marcin Pakulnicki work as developers in ING's Omnichannel and DevOps teams, providing tools and services for other teams to use.


Apache Spark Project Predicting Customer Response in Banking

#artificialintelligence

Telemarketing advertising campaigns are a billion-dollar effort and one of the central uses of the machine learning model. However, its data and methods are usually kept under lock and key. The Project is related to the direct marketing campaigns of a banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed.


An ML Toolkit for InterSystems IRIS: Co-Innovation In Banking

#artificialintelligence

Python and R are the de facto standard languages for data science, due to their ease of use and huge array of third party libraries for machine learning and analytics. This video provides an introduction to the ML Toolkit and demonstrates using InterSystems IRIS as both a standalone development platform and an orchestration tool for predictive modeling. Takeaway: The ML Toolkit enables machine learning and other complex application development in the R and Python languages.



How AI is Revolutionizing the Banking Sector

#artificialintelligence

Artificial Intelligence (AI) is becoming ubiquitous in recent years and its uses are seen in every industry from health, to travel, to banking, to hospitality and finance. According to the IHS Markit's "Artificial Intelligence in Banking" report, the global AI market is expected to reach $300 billion by 2030. AI is becoming important for all businesses that rely heavily on data. This is because this technology has the ability to teach itself and make it better through its practice. This is done through deep learning which includes the acquisition of new knowledge, the development of motor and cognitive skills through experience or practice, the assembling of knowledge into general, effective presentations and the discovery of new facts and theories through observation and experimentation.