Operant.AI is working with leading accounts receivable groups to revolutionize the collections process. By integrating the rich data associated with every account, we use machine learning and reinforcement learning to personalize the collections approach in order to improve customer experience, increase repayment rates and maximize retention.
Credit losses are one of retail banks’ largest expenses, costing over
$55B per year in North America. Unfortunately, many collections groups
are writing off millions of collectible dollars per year due to operational
opacity and generic customer treatment.

Customer Journey Model
All customer circumstances are unique. When a customer is in
collections a rich understanding of their situation is essential.
By considering all available data, our customer journey model
identifies the best times and ways to interact with customers
to maximize collection effectiveness. While humans are great at certain tasks,
analyzing vast amounts of data and determ...
Operant.AI is working with leading accounts receivable groups to revolutionize the collections process. By integrating the rich data associated with every account, we use machine learning and reinforcement learning to personalize the collections approach in order to improve customer experience, increase repayment rates and maximize retention.
Credit losses are one of retail banks’ largest expenses, costing over
$55B per year in North America. Unfortunately, many collections groups
are writing off millions of collectible dollars per year due to operational
opacity and generic customer treatment.

Customer Journey Model
All customer circumstances are unique. When a customer is in
collections a rich understanding of their situation is essential.
By considering all available data, our customer journey model
identifies the best times and ways to interact with customers
to maximize collection effectiveness. While humans are great at certain tasks,
analyzing vast amounts of data and determining the optimal course of action for each customer requires a unique approach to data processing in collections.
Reinforcement Learning Our AI model looks at the complete customer history to evaluate the expected value of all possible actions that the bank can take with
this case. The model uses an AI technique known as reinforcement learning, which
enables algorithms to make decisions in the near term that optimize the long term.

Dialer Prioritizer
The Dialer Prioritizer module
seamlessly integrates with your
existing dialer solution and provides
the list of cvustomers the Model
suggests to contact in the next hour
in order to maximize the pay-offs.
Agent Scheduler
The Agent Scheduler module
optimizes shift assignment to ensure
the effort of the workforce is evenly
matched with the debt portfolio’s
demand for it.
SMS and Email Optimizer
The SMS and Email Optimizer
module creates behavior-driven
campaigns for each customer, and
provides you with performance
metrics.
KPI Dashboard
In order to address the issue of
operational opacity, as well as
provide a coaching solution for the
agents, we have developed the
Dashboard, which is an AI-powered
data visualization reporting tool.
The Management version of
the Dashboard rolls up across
the organizational structure and
provides each stakeholder with a
bird’s-eye view on the performance
of each team and agent. The Agent
version of the Dashboard delivers
real-time performance reporting
and actionable coaching to each
agent.
More information

Employees

Allan (Amnon) Fisch
Admin
Allan (Amnon) Fisch CEO Founder - Operant.ai - Serial AI Entrepreneur