Using artificial intelligence to analyse individual transactions, the company provides recommendations on diversification, taxes and fees that are specific to a client's financial profile and risk tolerance.
In short, machines using artificial intelligence could contribute to productivity not only because of their speed and accuracy, but also because they could enable people to make more efficient use of their time.
So what should financial services keep in mind if they want to implement more intelligent automation solutions?
- Embrace intelligent machines as increasingly valuable members of their workforce, as operations assistants, client liaisons and advisors.
- Automate back-office and commodity functions (such as reconciliation) and further lower costs by using robotics to complement or even displace already low-cost utility labour arbitrage models.
- Apply artificial intelligence to many front-office client interactions, such as client onboarding, risk appetite assessments, portfolio allocation and rebalancing, sales and trading-freeing people to perform higher value tasks.
Companies that adjust their organisation 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.
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