Global

Details

  • Industry: Financial Services, Investment Management
  • Type: Business and industry issue
  • Date: 3/19/2013

Potential industry disruptors 

Potential industry disruptors
Even as the global investment management industry struggles to adapt to a rapidly changing landscape, it finds itself facing a new set of serious threats from outside its traditional sphere of competition. Thanks to advances in technology and the ‘sector creep’ of industry giants like Google and Facebook, these industry disruptors are rapidly developing new business models that have the potential to fundamentally change the status quo in the investment management industry.

Apple

Apple has more than 400 million iTunes accounts, all attached to valid credit card holders. That’s a sizable and loyal client base from which to build a potential banking entity. Imagine if Apple were to enter the financial services arena with its Net Promoter Score (used to gauge client loyalty) of 70, compared with the major financial services brands, which have either low or negative Net Promoter Scores.

Google

What would motivate Google to enter the banking industry? As bank robber Willie Sutton once famously stated, ‘Because that’s where the money is.’ Banking wouldn’t be the first, nor last, industry that Google disrupted. The company has already caused significant challenges for the telecom, GPS, news media and advertising industries to name a few.

Facebook

With more than a billion registered users who already use the site as their ‘virtual ID’, Facebook has access to more personal data and information on users’ behavior than any other company on the planet. And in 2011, 15 percent of the company’s revenue was generated by processing payments (primarily by users making purchases within social games). Having already succeeded in the difficult task of convincing nearly a billion people to use their site as a virtual ID online, the road to becoming a virtual wallet would be a breeze in comparison. Just the thought of Facebook entering the financial services industry would have to be enough to make even the most even-keeled banking executive sleep with one eye open.


There is also a crop of bold, new companies on the horizon, preparing to fundamentally challenge the status quo, such as:

Wealthfront

An SEC-registered online financial advisor catering to the young and tech-savvy Silicon Valley community. The company, which only offers investments in ETFs and index funds is already thought to have millions of customers using its services. The company has adopted a ‘freemium’ model, whereby the first USD25,000 is managed free of charge and the next USD10,000 is managed free if you introduce a friend to the service. While Wealthfront’s services are not yet available to the public, it’s only a matter of time before that happens.

Dataminr

This real-time social media analytics company picks up more than 340 million tweets each day, which it then uses to predict events on behalf of clients in the financial and government sectors. The company represents an entirely new category of social media analysis. Their analytics engine has the potential to transform social media streams into actionable signals for financial services and government clients, providing what amounts to one of the earliest-warning systems on the market.

SNTMNT

Along the same lines as Dataminr, SNTMNT describes itself as the first Application Program Interface (API) in the world that gives predictions based on Twitter sentiment for all S&P 500 stocks. The company says its algorithm provides an extra indicator on top of fundamentals and technical analysis.


SNTMNT’s ‘machine learning’ algorithms generate an indicator capable of predicting share price movements between one and seven days into the future with an accuracy rate of 56 percent. The company employs a two-step process as part of its offering. The first is natural language processing that is sourced from Twitter, Facebook, blogs and news sites to identify what it calls ‘mood states’. Then, they employ machine learning and predictive analysis to make their predictions.

 

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