BotViser ©

BotViser © is our chat-bot to cater the brokers and the sell-side. It generates ideas for the day-trader on demand.

  • It generates, customizes and communicates trading ideas for the day-trader
  • The back-end uses the same technology with 4estRobot ©
  • The engine that sits between the back-end and the front-end of Botviser(c) is basically an unsupervised NLP chat-bot in which the typical text classification algorithms are embedded:
    • It takes the textual input from the user of the chat-bot through the front-end as the “question of the user”,
    • it maps this question,
    • connects to the back-end service and requests an answer,
    • gets the response of the back-end,
    • presents this response through the front-end as the “answer of the user”.
  • Front-end is customized according to our clients priorities.

Value proposal of BotViser©: Affordable and quality advice for the masses

  • We aim at the ‘mass segment’ with this product : It would make the “advisory service” much affordable for the masses
  • Mass market is high in number of clients (hard to customize)
  • Yet it is low in revenue yield (per client) (hard to convert the effort into revenues)
  • Comes with quite high(er) coverage costs (as human interaction is costly)
  • It requires substantial investment in Human Capital, HR, training, main-frames (‘retail is detail’)
  • Bank-affiliated brokers find it hard to service the bank’s massive customer base (never-ending pressure from the bank)

BotViser© to reduce:

  • The cost of HR given the automation of client coverage (AI-based algorithms generate ideas, present ideas, customize ideas)
  • The human error
  • The overall time required to handle the ‘usual’ requests from this segment (i.e. “What to trade today?”, “Dollars or equities today?”, “How much of my portfolio to invest into that stock?”)

BotViser© to increase:

  • The quality of service, the integrity of service (IVR, web-site, app)
  • The ability to orchestrate the channels (phone, web-site, e-mail, app, advisory),
  • The speed to respond to the market developments (machines are faster, accurate)
  • The opportunities to convert the “service” to “revenues” (online processes) (i.e. “press ok to invest in this recommendation”)
  • Segment profitability (through reduced costs, increased revenues)
  • Presumably with lower fees (machines and software are always cheaper)
  • Differentiation (based on risk preference, age, ‘earlier actions’)
  • Customization (this is the key)
  • Evolving into a ‘dedicated personal advisor’ through Data-science (‘know-your-client’)
  • Fit to the changing habits of the average client (mobility, apps, web services)

For more information, please contact VeriZeka at