Chatbots: - Doing what’s right Vs what’s hyped!
Well! 2017 was the year of “chatbots” and it’s well past us. Even if you are oblivious to it, everyone has had at least one interaction with a bot by now. While the world, in general, is aware that bots will soon become prevalent in day-to-day life and will aid us in making decisions, run errands, etc., most of the bots that are consumer-facing today are rule-based bots. It’s time we separate them from their distant cousins who did a Masters in the realm of intelligence, AI Bots.
What makes a chatbot different from an AI-bot? Let’s take a simple analogy. Say, Mary runs a media agency and thrives on business discovery from sharing content at fixed intervals. Mary is tired of posting it everywhere, even though HootSuite is there to help. She hears from Jina, a friend and management consultant at some big firm, that chatbots are the latest trends in customer engagement and she should have one. Mary does some research and hires a development agency to build a bot which can send content periodically from her content design base to a large group of followers on Facebook, Twitter, etc. All set! Well, besides saving time and reaching out through social, what else did she achieve! An AI-bot could have easily glanced through the reams of information updated daily and curated content based on Mary’s brand appeal. Then, it would have collaborated with Mary and her content-design team in real-time to complete the final version swiftly. An AI-bot could have got all this done and shared media at the most opportune moment. Did someone whisper “ROI”?
An AI bot is far more advanced in terms of Natural Language Understanding and can leverage other elements of Artificial Intelligence to perform highly complex tasks with little human oversight. While it’s beneficial to have a chatbot for every consumer-facing channel you have, AI bots could turn into a long-term asset. They can augment the perpetual business activities of assisting the customer journey, experience, and engagement at all points, thereby enhancing business.
Let’s take a detour from the media agency use-case and dive into the world of finance, investing and wealth management. FinTech was added to the Oxford dictionary in 2016 and its impact can be assessed by the fact that more than $16.6 Billion has been invested in FinTech startups in 2017 alone. In the domain of Investment and Wealth Management, AI can be expected to disrupt two significant points of engagement, the investment process and the client interaction.
As of now, wealth advisors and brokerage firms (or at least FSBs) have been dependent upon analysts to capture insights from market data, check portfolio health and advise accordingly, thus periodically rebalancing portfolios. Instead, portfolios can be tailored to each individual client and advice can be given at shorter intervals to mitigate as many risks as possible. Clients can be assigned to pre-defined cohorts with fixed asset allocations comprising of a set of financial instruments and given periodic advice on the changes that would affect such buckets. Customers will, obviously, be provided with their own, customized dynamically-changing buckets, derived from a holistic understanding of their financial situation and goals. This aligns with the vision of businesses to truly understand their clients and provide value.
Imagine a machine that talks to us the way a human does, continuously optimizing our portfolios and offering advice to improve our FinHealth (if I can call it so!). Users will be able to ask questions regarding their positions (e.g. size) and ask the chatbot to alert them when prices reach certain levels. A personalized style of communication and content will make for deeper and engaging conversations and better client engagement.
A very torn down and simplified approach to building such bots would consist of the following components: -
- A live database to store the knowledge from which the AI will draw its data and information
- An NLU Engine to understand the data, provide responses, learn from the mistakes and become more intelligence over time
- A central nervous system that gets data, retrieves information, manages conversations and leverages other data-munging elements to manage the whole interaction.
- The user interface with which the end user engages across various platforms, for example, Facebook Messenger, a website, an app on a device or something else altogether.
- An integration with other tech components specific to the business as well as 3rd party APIs.
On the other hand, you could have simply inserted some menus and generic information into your chatbot along with a scheduler for sending out periodic alerts to clients on the market news. It would have been cheaper and easier but would have lacked flexibility, scalability and the ability to provide long-term returns.
Hence, AI bots are being focused upon by the wise and the visionary. AJ Bell youInvest platform launched in 2000, is one of the UK’s largest providers of online investment platforms and stockbroker services. With more than 131,100 customers and assets under administration exceeding £28 billion. They utilize AI for real-time investment by applying bank-level encryption, advanced authentication methods, and other layers of security. Merrill Lynch, for example, has been working on “an AI stock-picking tool to help it identify value in small-cap stocks that conventional analysts might have missed,” says Bill Studebaker, president & CIO of ROBO Global.
Do you want to develop a smart bot or want to know how your business may benefit from the same? Drop me a line at sangram.sabat@saarthi.ai
