This article is based on an in-depth study of the data science efforts in three large, private-sector Indian banks with collective assets exceeding $200 million. The study included onsite observations; semistructured interviews with 57 executives, managers, and data scientists; and the examination of archival records. The five obstacles and the solutions for overcoming them emerged from an inductive analytical process based on the qualitative data. More and more companies are embracing data science as a function and a capability. But many of them have not been able to consistently derive business value from their investments in big data, artificial intelligence, and machine learning.1 Moreover, evidence suggests that the gap is widening between organizations successfully gaining value from data science and those struggling to do so.2

Artificial Intelligence (AI) is having a seismic impact across the banking industry. Its utilisation is broad and diverse, ranging in application from chatbots and virtual assistants to profiling customers, streamlining processes, identifying trends and patterns in customer behaviour and risk management. If you're new to the world of AI, getting to grips with the terminology can seem daunting, but getting started in AI is way more straightforward than you might think – and the rewards for taking action early can be vast in terms of keeping your customers happy, providing a unique competitive edge for your business and reaping the associated commercial rewards. According to industry analysts, AI has the potential to drive one of the greatest and most profound technological revolutions in modern history. Artificial Intelligence, or AI as its more commonly referred, relates to the design and creation of systems, machines or applications that possess the ability to undertake complex tasks traditionally performed by humans.

Artificial intelligence (AI) is one of the most impactful technological revolutions the world has witnessed. Customers today are increasingly exposed to advanced technologies such as AI-enabled chatbots and intelligent voice assistants like Apple Siri, Google Assistant, and Amazon Alexa, making personalization a high priority for incumbent banks. Today, AI enables financial institutions to solve many critical problems, thereby saving money and increasing the efficiency of the workforce. By deploying AI-based solutions, banks can improve the outcome in various dimensions such as customer service, risk management, cross-sales, etc. A MEDICI research study of 34 major banks across several geographies (US, EU, Singapore, Africa, Australia, and India) found that 27 out of these 34 banks have implemented AI in their front-office functions in the form of a chatbot, virtual assistant, and digital advisor.

New analytical capabilities have the potential to transform the way banks and other payment providers price products and services. Obtaining fair compensation for complex payment products, such as corporate cards, merchant acquisitions, and treasury-management services, has long been a major challenge. This is primarily because these products tend to be intricate, offered in myriad forms, and implemented across diverse markets. Treasury services, for instance, might have 1,000 or more different fees, and prices are often embedded in private contracts not shared within the organization. Throughout the payment industry, these problems are further complicated by ever-changing payment methods and platforms created by the rapid evolution of payment technologies.

Historically, consumer packaged goods (CPG) were designed to be sold in a brick-and-mortar retail environment -- in packaging flashy enough to catch a consumer's eyes while presenting the right information to compel a purchase. But packaging doesn't need to sell the product anymore. The Internet is becoming the primary channel for marketing and sales, customer experiences are being tailored to reflect our "smart" and "connected" world, and data has become the most valuable commodity to target the right customers at the right time. Producers have new ways to optimize. They may choose more environmentally friendly, cost-effective, or shippable packing.

Robots, blockchain, artificial intelligence... the list of new-tech innovations battering the finance sector seems endless but there is still one area where the humble human rules supreme - at least for now. The rarefied world of private banking and wealth management seems to hover above the day to day grind of everyday bank functions, dealing as they do with well-heeled, discreet clientele. Anyone trusting a bank with millions - billions, even - wants to be sure they are getting the human touch and not just another algorithm. That means someone who looks you in the eye, has a firm handshake and can talk you through the various ways they plan to protect your legacy and grow your money for your progeny. And yet even within this plush corner of the financial sector, the steady drumbeat of technology is advancing ever louder.

According to Wikipedia, when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving", it is said to use Artificial Intelligence (AI). Today, we see AI is disrupting almost every industry and threatening jobs due to automation capabilities. Banking and financial services (BAFS) involves serious data crunching, which is why it is no wonder that it has been an early adopter of AI. In Anti Money Laundering: Money laundering is the dark reality of financial services industry. Having identified the loopholes in the financial system, money launderers became experts in making illegal transactions look perfectly legitimate. However, they leave trails that reflect patterns in money laundering.

Banking providers must raise service levels, profitability and competitiveness by efficiently and effectively fusing digital technologies with personalized human interactions. Retail banks and credit unions are plagued by inconsistent online- and offline capabilities, and generic customer propositions. To overcome these fundamental issues, Boston Consulting Group (BCG) says financial institutions must embrace a "bionic" a strategy. According to BCG, a bionic transformation essentially consists of three interrelated elements. First is the blending of digital and personal interactions to create a more responsive and cost-effective distribution model.

Several months ago, we read a Facebook post about how the jobs that many people have today will not exist in ten years time. The post discussed topics ranging from anyone that worked in the transportation industry not having a job because all cars will be automated to many types of doctors not working because you will have a chip in your arm that will detect diseases before either the patient or a doctor could diagnose them today. It gave, in many respects, a very Draconian view of the world -- raising questions about how we employ people in a world where computers and machines can do things better, faster and cheaper than anyone else can do them. That got us thinking about the topic of this article, because the comparative number of Google results one receives upon searching "artificial intelligence" (AI) plus most other topics far outweigh the results regarding AI and the wealth management space. The scarcity of the commentary on this subject made us start thinking about how AI would impact the wealth management sector. In this article, we look at how certain areas of the wealth management sector may be affected by AI.

Several months ago, we read a Facebook post about how the jobs that many people have today will not exist in ten years' time. The post discussed topics ranging from anyone that worked in the transportation industry not having a job because all cars will be automated to many types of doctors not working because you will have a chip in your arm that will detect diseases before either the patient or a doctor could diagnose them today. It gave, in many respects, a very Draconian view of the world-- talking about how do we employ people in a world where the computers and the machines can do things better, faster and cheaper than anyone else can do them. That had us thinking about the topic of this article, because the comparative number of Google results one receives upon searching "artificial intelligence" (AI) plus most topics far outweigh the results regarding AI and the wealth management space. The scarcity of the commentary on this subject made us start thinking about how AI would impact the wealth management sector. In this article, we look at how certain areas of the wealth management sector may be affected by AI.