Disruptors, Big Data, and FinTech have all become a part of our vocabulary over the last year or two. A company that doesn’t own any hotels, can give stiff competition (and attain much higher market valuations in the process) to one that is established in the hospitality industry and has thousands of properties worldwide.
Most of the disruptors we have seen in the last few years, have been technology (or IT) enabled companies, identifying the pain points within an industry, creating a much easier platform to link the demand and supply, and offering value-added services at the same time. While we have seen major impacts from these in the transport, hospitality, and social networking, the impact on the finance industry has not yet reached such a dramatic extent.
Things are however looking to change soon. The number of FinTech companies crossed the 1,000 mark in 2016 with more than US$100 bn in funding and US$870 bn in market valuation. The investment in FinTech more than doubled from 2014 to 2015. The number of companies offering new services, enabled through the use of IT – predictive analytics, intelligent algorithms, simplified platforms reaching an untapped customer base is increasing at a rapid pace. These companies cover a big part of the entire finance value chain, be it crypto-currencies, security, banking and payment, financing, investments, wealth management or insurance.
We have seen the rise of WeChat Pay by Tencent and Alipay by Alibaba group in the recent years. These services have not only revolutionized the way users perform online transactions, but also the way banks operate in order to provide services that are used by the end customer. In the cases above, it has been in some instances more important for the banks to enable a link through the payment application in a convenient way, than to have an online platform that is convenient to use – as users do not go through the usual banking platform anymore! The question I guess we all have is, what is next?
We have on our hands a magnitude of services which will be largely automated, significantly faster, and devoid of the possibility of human errors.
One of the important factors in the finance industry is the data available. This can be classified as structured and unstructured. Data in excel sheets, databases, and collected through other means is considered as structured data. This is used quite extensively among other things to manage existing clients, build up risk profiles, provide customized solutions, identify and pursue new clients, and so on. The unstructured data on the other hand is the information that exists on social media networks, email correspondences, and website content and is hard to use. With the developments in big data analytics, increased computing power, and capabilities to extract meaning and structure out of seemingly unorganized data, the intelligence that can be used to provide better, more effective, and faster services will be one of the key success factors.
Major companies across the world have in the recent years moved to or adopted the position of a Chief Data Officer or a CDO, with the aim of harmonizing the available data, synchronizing the multiple platforms they may be working on, and creating a vast database that can be used to provide the intelligence, in turn to be used to create a differentiating factor. Adding on the capabilities of big data analytics – using machine learning, AI, and feeding large sets of data to the self-learning algorithms, we have on our hands a magnitude of services which will be largely automated, significantly faster, and devoid of the possibility of human errors.
An example of such a service is evaluation of credit worthiness of a potential customer seeking a loan from a financial institution. A platform provides the service of collecting data from the customer, puts it through an intelligent tool, and compares it to thousands of sets of data previously collected and fed to the tool. In addition, the tool uses the information collected from systematic analysis of the unstructured data available on the customer – and churns out a recommendation based on the risk factors suggesting the credit worthiness in a matter of minutes! This is a simple example of creating convenience for the customer and reducing hours of work for the financial institution. Taking it further with even more sophisticated tools and intelligent algorithms – the services financial institutions provide for investments and wealth management will look very different from what it is now and have huge implications on the entire industry.
While the gap between the demand and availability of people with the required set of skills is still closing, with the solutions and focus on this area in the current environment, it is surely catching up. The downturn in major economies and industries in the recent years has put pressure on the financial industry as well. With the opportunities for expansion and outward growth reducing, the other way to increase profitability and shareholder value is to look internally for operational efficiencies. And this is again a key factor which will drive companies to explore and exploit the benefits available through the use of “IT”, in order to meet the expectations in terms of increasing profitability.