Finally, retail banks are immediate candidates for IoT innovation. The ATM is the most common physical endpoint for any retail bank, and, to many, serves as the only non-human physical interface between regular people and the finance industry. The model is simple: insert a card, enter a PIN, and retrieve the money. One must ask, however, what does a piece of plastic, even one embedded with a chip, do that a mobile device or biometric scanner cannot? Instead of using an easily-spoofed card, why not use a mobile device that can not only verify identify but can also take a short interaction at an ATM and turn it into an opportunity to provide a customer personalized offers from other service lines such as personal loans or different savings vehicles.
The above are both examples of conventional IoT applications. The examples to follow are perhaps more derivative, but also hold even more transformational potential for the BFSI industry.
Banks also have a tremendous opportunity to capitalize on the transaction data held across multiple industries. As information about Wall Street grows more and more transparent, how can IoT data on asset utilization in factories, mines, supermarkets, etc. provide an advantage to investors? By examining purchasing decisions as well as usage trends, a bank would be able to profile customers such as UPS or DHL to monitor delivery activity during the holiday season and make decisions based on real-time data rather than waiting on reports on consumer sentiments.
Commodity traders feast on data: agricultural yields, consumer behavior, weather patterns, etc. Why not connect a trader who specializes in pork belly futures, to feeding trough behavior at a few bell weather hog farms in Iowa? With the proper analytics engine, the trader is no longer waiting on reports but is trading based on the same day feeding behavior of hogs he is buying or selling. This same scenario holds true for any trader relying on any agricultural yields. This value stream could venture well beyond commodity traders to farmers and end consumers. For example, were the type of data above to indicate a demand spike for a product like grass-fed, grain-finished beef, farmers would be able to justify their borrowing to purchase grass-fed calves and grain feed to their lenders.
Commercial realty lending is another field where a tweak to the way IoT is employed holds enormous potential for driving value. Insurance agencies, lenders, and even REIT managers benefit directly from sensors that track foot traffic, consumer behavior, and even energy usage. This information, correctly applied, would provide a valuation based on the real-time behavior or occupants rather than making projections based on comparable properties.
As the IoT industry matures questions change from ‘what can sensors detect?’ to ‘what information will allow you to make better decisions?’ IoT in financial services represents the significant opportunity to figure out how data from tangible assets can inform decision making over electronic flows of capital. Financial institutions need to take the plunge and invest in the expertise, platforms, and data integration that will allow them to derive value from all data available. The data is already at the fingertips of the BFSI industry; it is time to grasp it and monetize it.