The gray matter inherent in banks’ investment strategies is the lifeblood of any industry leader.
That gray matter, however, is no longer contained solely in human form. As artificial intelligence (AI) technologies advance, investment banks have much to reap from the transformational insights artificial intelligence enables.
As a client-centric approach becomes more of the norm across the board, and as investment banks wrestle with a complex regulatory environment that shows no signs of lessening, the competitive edge and agility artificial intelligence offers could become crucial to future success. Those banks who don´t move beyond basic automation into the more unfamiliar area of artificial intelligence might be left behind as others compete at an entirely new level.
There is automation and then there is artificial intelligence-enabled automation. Many capital markets companies are automating, but the level of intelligence they are incorporating into that automation is still rather minimal. The key advantage to intelligent automation capital is that it is self-learning; it constantly improves, rather than degrades, in value.
As banks rationalize business lines and re-focus on a client-centric approach, they usually move away from product silos to an advice-oriented approach. This approach, as well as clients’ desire to self-serve via a variety of digital options, will require automation with sufficient intelligence built into it for increased agility, speed and scale.
The future ‘virtual workforce’ within investment banks will likely comprise a suite of technologies—from basic robotics process automation through cognitive computing and natural language processing. Not only will this workforce be able to provide cost savings, it frees its human counterparts so they can focus on roles that add the most value—from innovation to client relations.
Look into automating back-office and commodity functions (such as reconciliation) as you improve quality and further lower costs by using robotics to complement already low-cost utility labor arbitrage models.
Look into applying artificial intelligence to front-office client interactions where possible—client onboarding, risk appetite assessments, portfolio allocation and rebalancing, sales and trading—as this could free people to perform higher value tasks.
Companies that adjust their organization and culture to incorporate intelligent automation as co-workers, rather than people replacements, could reap important rewards: more reliable performance and insight, extension of services to previously unprofitable markets (such as lower-end retail markets and smaller institutions) and continuing cost reductions.
Automated intelligence tools and virtual workforces could drive a new, more productive relationship between people and machines through deeper analytics and recommendation engines, maximizing client service and product needs.