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ARTICLE

24-MAY-2022


SMART COLLECTIONS: THE UBER WAY



When managing business processes, most agree the ideal combination is Artificial
Intelligence plus Human Intelligence. 

The Collections Process is a perfect example. This article lists 5 ways
Autonomous Software is helping transport and logistics giant Uber achieve a
whopping transformation in its accounts receivables.

 

 1. Some context: Autonomous Software is intelligent technology that uses data
    to learn. This means the technology that Uber is using to help manage its
    collections process is learning from:
    
    a) data relating to customers, such as payment history, credit worthiness,
    and how long Uber has spent on the phone talking about Collections with each
    customer and
    b) data relating to other users’ interactions with those same customers.

 

As the seconds, minutes and days go by, each company’s profile expands and the
technology’s intelligence concerning each customer deepens. As a result, when
the system provides a confidence score regarding each customers’ reliability to
pay on time, we can be pretty sure that the confidence score is dependable.

 

 2. When it comes to building out a profile of each customer so that sensible
    actions can be taken, humans cannot keep up. Autonomous Software pulls up
    lists of customers to call and organizes lists according to “Worst First.”
    There’s no point in having your Collections Analyst calling low-risk
    customers first. Instead, early morning calls need to be made to the “red
    flag” customers who will end up in your “write off” bucket if ignored. Uber
    works with HighRadius for its B2B and Freight businesses which transact with
    15,000 customers. The HighRadius Autonomous Software Digital Assistant,
    known as Freeda, does all the heavy lifting so each Uber Collections Analyst
    can focus on reducing:
    * Risk in receivables
    * Aged debt
    * Days Sales Outstanding (DSO)
    * Write offs

 

 3. How does Freeda work? It creates a Call Dashboard which is at the center of
    the Collections Analyst’s work world. Once logged, the Call Dashboard
    directs your Collections Analyst so they know:
    * Which customer to call
    * The intent of the call and the call “talk track” for each customer
    * How long the call should take
    * How many calls will be made in total that day
    * How long the Collections Analyst will be on the phone
    * How much value should be collected today based on the analyst’s calls

 

 4. Based on this information, what happens next? Freeda is like Siri or Alexa.
    Let’s say the first Customer on the list is “George.” The Collections
    Analyst says “Freeda, call George.” The system connects the Analyst to
    George.

 

 5. Then what? Not only has Freeda built a profile for each customer, built a
    worklist for the Collections Analyst based on urgency, and connected the
    Analyst directly to George, but it will then go on to:
    * Transcribe the entire call and log this in the system.
    * Capture all the actions that come out of the call (maybe in this case the
      Collections Analyst needs to resend two invoices and a delivery note).
    * Log in the system key outcomes, like update the Promise to Pay date that
      George referenced in the call.
    * Present a follow up email for the Collections Analyst to send to George
      with invoices and delivery note attached, a reminder of the Promise to Pay
      date quoted on the call, and a link to the payment site.

 

Freeda represents optimal efficiency in Collections. The Collections Analyst has
all relevant contextual information at hand, doesn’t need to take notes on the
call, has limited call follow-up work, and can make sure the “human element” is
high quality. Then they can call the next customer.

Freeda’s motto should be “Call. Collect. Repeat.”

Talking to HighRadius about Freeda, they admit it’s still an Early Adopters’
market, and that from 2022 to 2027 they will see technologies like Freeda become
mainstream. It’s not surprising that one of their Early Adopter clients is Uber,
a world-leading vanguard in disruptive technology.

Some benefits to the wider business to assist cash flow and make available
working capital to invest or direct towards M&A activity are:

 1. Reduction in DSO by 14 days
 2. An increase in growth by 20% in their Collections Effectiveness Index
 3. Staggering 7000 automated correspondences sent each month

Homer Smith, Global Process Owner - Billing, Credit and Collections, at Uber,
puts it this way:

“Autonomous Collections enables our collectors and users to be much more
efficient in their process. For example, when making collection calls, they’re
able to retrieve information about a customer’s account, view the notes, the
most recent interaction with that customer, and then provide up-to-date
real-time information, right there on the call.”

Does this mean the end to human intelligence in Collections? “No” responds
HighRadius. The perfect match is human and artificial intelligence. This
combination lends itself to top performing Collections KPIs.

When managing business processes, most agree the ideal combination is Artificial
Intelligence plus Human Intelligence. 

The Collections Process is a perfect example. This article lists 5 ways
Autonomous Software is helping transport and logistics giant Uber achieve a
whopping transformation in its accounts receivables.

 

 1. Some context: Autonomous Software is intelligent technology that uses data
    to learn. This means the technology that Uber is using to help manage its
    collections process is learning from:
    
    a) data relating to customers, such as payment history, credit worthiness,
    and how long Uber has spent on the phone talking about Collections with each
    customer and
    b) data relating to other users’ interactions with those same customers.

 

As the seconds, minutes and days go by, each company’s profile expands and the
technology’s intelligence concerning each customer deepens. As a result, when
the system provides a confidence score regarding each customers’...

AI Machine Learning/Artificial Intelligence Chatbots O2C sharedserviceslink O2C
AR sharedserviceslink and High Radius
Author

SUSIE WEST

CEO, sharedserviceslink


IN ASSOCIATION WITH:




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