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Robots will control your personal wealth. Are you ready?

#artificialintelligence

Investments in the future will be based on algorithms and patterns charted by robot. Emerging as one of the hot sectors in fintech, robo-advisory can come across as the next big disruption in the space. According to YourStory Research, there are close to 50 Indian early-stage startups flocking around this sector. A Deloitte research paper states that the top 11 firms in this segment globally have seen explosive growth since market entry, managing close to 19 billion Assets Under Management (AUM) in 2014. This disruption in the personal wealth management space is called robo-advisory, which leverages client information through algorithms, automating and recommending tailored investments to individuals.


7 Ways Wealthtech is Digitizing Wealth Management

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"Customer experience is chief among the areas where traditional financial institutions have fallen short. Not long ago, wealth management was considered a service almost exclusively confined to the affluent. With their millions at the ready, wealthy investors could use wealth managers to provide a range of tailored investment-related services, and those services would normally come at a high price. But these days, such a perception of wealth management is becoming old, or simply not accurate. Innovation broke down those barriers of exclusivity, enabling services that were previously only accessible to the privileged few to be in the hands of the masses of ordinary investors. Wealthtech falls under fintech as a segment which specifically focuses on technology that aims to transform wealth management and retail investment. It involves the application of digital solutions to wealth management, ultimately providing new channels to deliver more efficient, cost-effective and efficient ...


How Digital 2.0 Is Driving Banking's Next Wave of Change

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DIGITAL BUSINESS August 2017 2. 2 How Digital 2.0 Is Driving Banking's Next Wave of Change Digital Business EXECUTIVE SUMMARY In the last few years, a wave of digital technologies changed the banking landscape as we know it. Social and mobile altered the way banks engage with customers. Analytics enabled hyper- personalized offerings by making sense of large datasets. Cloud technologies shifted the computing paradigm from a Cap-Ex-oriented model to a more flexible Op-Ex model, enabling delivery of multiple business processes as services from third-party platforms. Now, a second wave of disruption, or Digital 2.0, is set to drive even more profound change.


The fintech wave, part one BankNXT

#artificialintelligence

I wrote a blog the other day for The Next Web. I thought it was OK, and it has gained a lot of traction socially. Apparently, people like it and here I'm going to expand on the basic theme to give a detailed analysis of how fintech wings are spreading. There's been a lot of talk about fintech lately. We talk about the billions of dollars being invested in fintech; the wave of unicorns and startups in this space; the challenge they bring to banks and incumbents; the way in which they're reaching new spaces and places – but what is fintech?


12 Use Cases of AI and Machine Learning In Finance

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There's no doubt that the finance industry is undergoing a transformational change. The recent years have seen a rapid acceleration in the pace of disruptive technologies such as AI and Machine Learning in Finance due to improved software and hardware. The finance sector, specifically, has seen a steep rise in the use cases of machine learning applications to advance better outcomes for both consumers and businesses. Until recently, only the hedge funds were the primary users of AI and ML in Finance, but the last few years have seen the applications of ML spreading to various other areas, including banks, fintech, regulators, and insurance firms, to name a few. Right from speeding up the underwriting process, portfolio composition and optimization, model validation, Robo-advising, market impact analysis, to offering alternative credit reporting methods, the different use cases of AI and Machine Learning In Finance are having a significant impact on this sector.