Firstly, one must define the Internet of things (IoT). Put simply, it is the network of physical objects which are embedded with electronics, software and sensors. The physical objects become ‘Iot-enabled’ through network connectivity which enables these objects to collect and exchange data. (Internet of Things Global Standards Initiative, 2015)
Cisco estimates that businesses generate $612bn per year of additional profits because of connected devices. Hence with potential for a market as large as the financial one, why is there still so much unused potential?
It is a short-sighted view to say that the financial industry is a business of providing services and not “things”. Analysis by Deloitte suggests that perhaps “as many as one-quarter of sensors deployed in 2013 could be of use to the financial sector, rising to one-third in 2015 and then an increase to 50% by 2020. In other words, one could reasonably assume that by the end of the decade, companies will have deployed several billion sensors that could provide data of interest to financial firms of one kind or another.”
Key Sectors
What areas of financial services can leverage the Internet of Things technology, and how?
There is a massive potential for IoT in the connection of financial services. For example, from a retail perspective, trying to connect payment cards and investment accounts to some of the common household devices. As banks are becoming less ‘somewhere you go, but something you do’ (Brett King, 2013) retail banking can move with the trend by modernising ATMs and information kiosks in bank branches and/or cards by using sensing technology to monitor and take action on the consumers’ behalf. This can be beneficial to tackle P2P lenders and niche fintech companies which aim to disrupt the industry as we move further into a 4.0 Industry realm.
Middle and back-office functions at banks, insurance firms and investment management shops could also potentially benefit from the IoT technologies.
IoT applications might help banks improve underwriting processes and reach new markets. The physical performance and behavioural data generated from biometric and positional sensors for individuals as well as shipping and manufacturing control sensors for businesses could provide new opportunities for credit underwriting. This is especially interesting for those under-served customer segments lacking a credit history. For example, lenders could partner with electronics and white goods manufacturers to proactively make credit offers to individuals if their purchased items begin to show noticeable wear or face imminent failure. Leasing companies could monitor the condition of leased assets in order to determine a more precise residual value of the asset at lease expiration, or determine with greater accuracy any discounts or penalties for preferred or unacceptable use.
Capital Markets
The potential stretches to capital markets, both Debt Capital Markets (DCM) and secondary deals in Equity Capital Markets (ECM). IoT-enabled opportunities can further automate trading and investing activities. This is driven by continued acceleration in algorithmic trading and the enhancement of the application of IoT sensor data. It can be considered that with the removal of the human element in combination with more comprehensive real-time data flows firms could develop analytics that might better evaluate suspected market bubbles. This theory has real-life examples as seen by hedge funds now working towards running completely on AI without human interaction.
Moreover, venture capital, in theory, can be completely shifted by the Internet of things. This is because crowdfunding and micro-investing could emerge based on analysing of data through the medium of the IoT.
The Internet of Things has the potential to impact Wealth Management and Investment. Financial institutions could utilise information from a client’s IoT “ecosystem” to tailor investment decisions and asset allocation.
Consequently, IoT could create an intimate understanding of a client’s interests and purchasing patterns based on behaviours, preferences, and location. Investment offerings could be tailored based on these data, leading to the extension of concepts similar to socially responsible investing. Hence, this could lead to the exciting concept of automating portfolio investment.
The Insurance Industry
One area of finance which has already taken the plunge is insurance. This is evident through telematics. IoT integrates real-time monitoring driving behaviour. Thus, the cost of an individual’s car insurance is determined by their behaviour. Hence, a fairer system for all which to some extent removes some discriminative biases such as age and sex.
The Internet of Things has future potential to be in health and life insurance through monitoring fitness/activity levels of individuals to assess their rating. This can lead to a personal health monitor that is also connected to your investment account. At the sign of any serious health hazard (e.g. heart attack), the investment account could automatically rebalance to limit your downside exposure or transfer your holdings to more liquid securities, in anticipation of future cash needs. Similarly, other potential applications in insurance are homeowner’s insurance and worker’s compensation in the commercial arena. Although this may seem implausible now, it is not completely out of the realm of possibilities. With the right level of business investment and empathise on research, anything is possible. The beauty of making the improbable a reality.
Mitigating risk is essential to financial services. It is a method of generating revenue, i.e. through creating loans which create new money, a debt (risk) is also created. Banks have increased the amount of money in the economy by an average of 11.5% over the last 40 years. The Internet of Things has the potential to reduce the amount of risk that financial institutions hold whilst still generating the same revenue. This can be achieved through quantified self-concepts.
One must give consideration to the long-term impact. The Internet of Things could lead to the eventual emergence of radical transparency. This may have a more enduring impact on financial institutions.
Information asymmetries, which are an important aspect of the profitable operation of capital markets businesses, may wither away due to IoT. The pattern of ‘life data’ could emerge as a new way to de-commoditize consumer financial products. Consequently, new businesses may emerge to meet the market need for access to these data flows. As one door closes another opens.
Potential Risks and Challenges
Foremost, the deluge of new data is likely to complicate data management for financial services firm. Challenges involve developing an understanding of which kinds of data are best predictive of creditworthiness, as well as the potential risk of new forms of redlining based on so-called “pattern of life” (POL) analyses.
Cyber-security is at the forefront of discussions and that is especially the case with financial services. The future potential for finance to move towards a cloud platform is held back by worries regarding data theft. Cyber-crime is a serious issue which is a worry for every individual and group who share their personal data through the fascinating medium that is the internet. IoT-enabled financial services create more issues for cyber-security and due to the unforeseen consequences, the theory may just stay that and never become a reality.
However, encrypted technologies such as blockchain can offset the issues of implementing IoT due to cyber-security concerns. Paul Brody (EY Americas Strategy Leader) argues that “blockchain shifts cyber security from depending on one to depending on many” with the significance of this being that a large volume of people is much more trustworthy than any one individual. It could significantly decrease the risk of error and the time spent on error checking.
Bottlenecks in the process caused by the Internet of Things could mean a slowdown in the supply chain due to the shift in the procedure, at least in the short-term. This is because IoT applications in financial services may increasingly shift from common uses with tangible measures to uses with intangible measures.
Another bottleneck is the communication stage. Due to the sensitivity of the data held by financial firms, not all information needed in the sector is freely available as it may be in other industries.
In spite of this, there is a solution to the bottlenecks referred to as Information Value Loop. One of the implications associated with the Internet of Things is that a product’s information content is now as valuable as its performance. This is because simply the flow of information around the Value Loop creates value for customers that companies can then capture. Analysing this flow of information can help companies locate specific strategic and technical challenges facing them in an IoT-enabled world.
Unfortunately, information does not flow evenly around the loop. A bottleneck will exist at one stage of technology, which limits the flow and thus the value. Alleviating this bottleneck can increase the flow of information, creating value for customers, and the company that controls the bottleneck is in a place to capture the bulk of value created.
Conclusion
In light of everything, it is clear that the Internet of Things is diverse with uses from capital markets to wealth management; the potential is seemingly unlimited. The problem of implementing IoT is that interrupting the old large infrastructure debt in financial processing systems for even a short time could be catastrophic, and in the current realm where financial services want to mitigate as much risk as possible, is this wise?
However, as mentioned above with the potential to develop IoT to better evaluate suspected market bubbles, perhaps in the future the industry will be pushed towards the technology. Whether it likes it or not.
Ultimately, the uneven progression of sensor deployments highlights the fact that for many emerging IoT applications, the bottleneck is at the creation stage of the Value Loop. Therefore, it is fair to conclude that until some minimum critical mass of sensors is in the market, more sophisticated uses beyond the few existing tangible examples will be impossible.
