As it has always been, today too, technology managers have to contend with two complementing technologies for their attention and budget. In this circumstance, let us review where the tilt should be.
Let us circumscribe our scope to the BFSI vertical. The principles derived here, with some or no modification, may find application elsewhere. After the 2008 financial crisis, this vertical has been facing a global phenomenon of slow growth and immense pressure on cost management. This is directly forcing technology functions to deliver results that, in part at least, would give the leaders a breather, if not a differentiator. The review is made in such a context.
Revenue vs. Cost
There are some banks that have started their effort in rationalizing their customer and product profile as a precedent to focusing on other elements of cost. If these are pruned, they can, on their own, lead to economies of operations. There are banks which have got rationalization of upto 60% on their customers and products and are still not seeing a major impact on revenue; their costs are showing signs of decline or have declined a bit, and are on their course to further decline.
Most of these institutions have used AI which comprises of machine learning, natural language processing, algorithms and workflows to achieve their result. Unfortunately, blockchain is not one of them and this is not an intended domain for that either.
Width of coverage
There are products in financial services which have varying degree of dependencies on external parties for their fulfillment. Most of the investment or wealth management products have a large component on their interface connected to markets and counter parties. Same is the case with trade finance. In all these, while there are need for external interfaces, there is equal if not more spend on the internal processes for fulfillment.
Blockchain essentially has a play where there is external dependency which is critical to the completion of the process. AI has application irrespective of this.
Internal vs external dependency
Blockchain requires a substantial consortium of banks to institute common ground to transact business among themselves and to establish the process for bilateral or multilateral transactions. Its economies are derived from such common understanding.
AI is a technology enabler which an institution can apply irrespective of the need to strike such common grounds with any of their trade partners.
Maturity of the technology
Proven platforms have begun to emerge in financial services. Some of them manage risk and adaptation of product to suit the customer while a few of them also provide decision aids about the customer for closure of the transaction. Kabbage, LendUp and Lending Club are examples of the platforms.
In addition, there are tools that are available which have focused either on a process, like customer acquisition or retention or for a vertical, say financial services, and have established their maturity. Dataminr and Alphasense on sourcing data across various platforms and also types whether text, audio, visual or graphic are a case in example. Similarly, Blue Prism and UI Path have established that they can bring acceleration to process automation irrespective of whether they relate to front, mid or back office functions.
It is hard to point out any platforms or tools that have comes to similar maturity on the Blockchain front. It is not to state they are not there. Trading platforms like Hedgy, LedgerX and TeraExchange as well as issuance platforms like Linq or 10 are a few examples. They are, however, not comparable in terms of maturity to their AI counterparts.
Adoption and practice
There are two broad trends that are emerging in AI – Fintechs are coming out with platforms that are robust for adoption by even bigger banks; large banks themselves are aggressively pursuing their effort to streamline and economise their cost through adopting and adapting these tools. A few small and regional banks too have started their efforts along the same lines.
As regards Blockchain, consortium of banks like those in Australia or among large investment banking institutions in US have started their effort to derive value out of this. We need to see where we head from here.
Conclusion
At this time, both in terms of versatility and adoption, AI is ahead of Blockchain among the financial services vertical. What the future holds, one needs to wait and watch.
*This article was previously published in Finextra on May 9, 2017
