Bill Sarda (HighRadius)

Bill Sarda (HighRadius)

Director, Solution Engineering
Company Logo

Connect on Linkedin

Bill Sarda is the Director of Solutions Engineering at HighRadius and has spent over 6 years at HighRadius working across the Product & Consulting teams and has been involved in various AR transformation projects over the past few years.

Session Summary:

Takeaway 1:
Say Hi to Freeda: Digital assistant powered by natural language processing (NLP) backed by HighRadius AI engine – Rivana
Key Points
  • Leverages the power of machine learning to take accurate decisions, discover insights, improve productivity, and forecast accurately.
  • Leverages NLP algorithms to understand, process, realize the intent and provide appropriate response and information.
  • Leverages NLP to bring out customer information, analyze data, and predict future customer behavior.
Takeaway 2:
Call of NLP in finance today
Key Points
  • Dashboards that improve user experience and make work easy.
  • Transcribes customer interaction, capturing key action items.
  • Gives intelligent suggestions and analysis intent in emails and over phone calls.
Takeaway 3:
Future of Finance with Colleagues like Freeda
Key Points
  • Recommendations on real-time questions that can be asked while on a customer call.
  • Suggestions on how to answer customer questions while predicting the probable questions that may be asked.
  • Assistance in identifying the customer’s intent using sentiment analysis.
Bill Sarda 0:00

All right. Hi everyone. Excited to be here. I had to make sure I look my absolute best when I’m on the Texans field. So one thing I did need to remember is to dye my hair. Yeah, I do have some gray hair. And since it’s a new thing, I It’s hard to remember. So first thing I did was I told Siri. Siri, remind me to dye my hair tomorrow. Works like a charm. Today wake up to a 5 am alarm it said die today. Well that’s, in short natural language processing for you.

Bill Sarda 0:41

We will go into details. Talk about natural language processing, how it relates to accounts receivable, and so on.

Bill Sarda 0:54

So what is NLP right natural language processing is a branch of AI that deals with more of intent identification and using normal language that people talk to each other and, and understanding what they want to do right here is an example of how NLP works you have a statement here. What is the number of open invoices for revive pharmacy, right now what NLP does is it breaks the sentence down into an intent and an entity. Intent is, what the user is trying to do, right, in this case, find out the number of invoices entity is from where do I need to pull the data. So that’s how it works. Takes english sentences, breaks it down, identifies the intent and identity. So we actually leverage this highradius and extended this to be a part of our AI platform, which is called Rivana right Rivana stands for receivables nirvana. That’s how we came up with that name. And it’s our AI platform right. The idea is to have better predictability.

Bill Sarda 2:13

Make user life better take faster decisions better insights and so on. And one branch off Rivana is the virtual assistant that we launched Freeda. I’ll let Freeda introduce yourself. Sure. Hi, I am freeda, and I am Bill’s digital assistant. I leverage natural language processing algorithms to understand and process human language, realize the intent and provide responses and information accordingly.

Bill Sarda 2:43

Thank you Freeda, you’re most welcome.

Bill Sarda 2:50

Now, having an assistant is nice, it’s cool, but what does it really do. Right. Obviously, the idea is to make your life easier.

One is save time when you’re looking for data, right, especially when sometimes data is in like, let’s say multiple folders and so on. And you need to look for one particular invoice for a certain customer or pull up their aging report. You can commission the virtual assistant and just ask it to a can you pull this information for ABC products. The other is, because it understands your language. It is also able to understand the intent so if someone sends you an email saying,hey I will pay these invoices on the 15th of September, it creates a promise to pay for 15th of September by reading that email, or being on a call or listening to your customer.

Bill Sarda 3:41

And the third part is helping you prepare for a call so it takes all the data that’s available whether it is past you previous communication history, broken promise to pay us and so on. And, and give you like a bullet point summary of what you need to do or how you need to prepare before you get on a collections call. Right. All of this is possible because of NLP and, of course, AI, which kind of powers it.

Bill Sarda 4:11

These are the four areas that we will cover today about user experience, and some specific examples I’ll walk you through it. Let’s take a look at a three minute video, see Freeda in action, and how it is working.

(3 min introduction video of Freeda presented in the webinar) 4:27

Good morning, Samantha. Welcome to work. Let’s see what impact you can make with collections today. Welcome to your work board, you could call accounts I have identified as critical, send some of you automated email correspondence, review new credit applications, or the latest credit risk updates, let’s get started with the calls first. Sure, bringing up your call workboard in a second. Welcome to your call workboard. You have 27 customers to call today. I have already prioritize these accounts based on my AI enabled prediction of their aging 30 days from now, for instance, permalink has one broken payment commitment for $68,000 and has more than 50% of their AR balance past due by more than 30 days. Would you like to start with them? Absolutely. Here are the key reasons for this call with permalink. As you can see, this is their current aging and here is my prediction of their aging 30 days from now, you can see a surge in their 61 to 90 day aging bucket, growing to 43% of their total open invoice value. They also have no upcoming payment commitments which you might want to touch upon on the call, they have already reached 85% of their credit limit and you could use this to negotiate payment. Jeremy Jones, manager of Accounts Payable is your key contact at this account. Let me know when you’re ready to get started. All right, let’s call Jeremy. Sure, I will stand by to take notes. Hi, this is Jeremy permalink. Hi Jeremy this is Samantha from Penta core. I was expecting to receive payment for $68,000 Yesterday, just calling to check whether you’ve already made the payment. Hi Samantha, really sorry about that. My manager has been out sick the last few weeks and he missed approving your payment, you will have to wait till the first week of March for him to get back. Well, I just wanted to let you know that you have over $16,000 in invoices which are over 30 days past due, and I might have to escalate. Your credit utilization is already at 85% and new incoming orders are likely to get blocked. Yeah, no, no, I understand. See, I am only authorized to process payments up to $30,000. I would have got your payment approved but my manager just fell sick and has been out of the office. Well, Jeremy, let’s see what we can do here. I’m seeing two invoices which total up to around $20,000 Could you help me with payments for these since these are well within your authorization limit. Sure, I could do this by next Tuesday, could you please send me the invoices. Sure, sending them to you right now, you should be receiving an email. Thanks. Thanks, Jeremy, I will be looking forward to the payment on Tuesday for two invoices for 28k. Thanks. Have a nice day. That was a great first call to start the day with. I have already captured the key action items from the call. I will create a payment commitment and set a reminder for you to follow up with Jeremy. Are you good with these things please save these. Alright, I have drafted a summary email for you to send to Jeremy by using an available template from the library. I have also attached the invoices, they need to refer to let me know if you are good with this email and I will send this out. This looks good. Please send this done, let’s keep the day rolling. Here’s your next customer.

(End of the Video presentation)
Bill Sarda 8:00

So before I kind of break it down, Break down the video into different parts and then talk about how we utilize NLP and AI. The solution is live, we have some customers using it, we’ve actually set up a demonstration on the second floor suite 257 and 258. Feel free to walk in and do a test drive. Talk to Freeda our mega live collections call and see it working in action so I’d highly recommend that. Whenever you do get time. And now breaking it down on how the solution actually works it first is of course the improve user experience right.

Bill Sarda 8:41

Obviously you have the natural as the, the virtual assistant, Freeda, which is kind of doing a lot of stuff, but the entire system is designed to operate with touch and voice right so it’s designed for more like a mobile kind of a UI, right, you can just click on a call word board, and if you want to see your convoke board in detail. It will just give you a list of calls, high level summary and further before you make a call it will analyze all that data and tell you what you need to do on the customer call right, the customer has three broken promise to face, talk to them about some blocked orders and so on. It’s actually analyzing all of that and giving you ready made material to prepare for your call. The second is taking notes right. I mean, that’s the thing I hate most about my job right whenever I want to call. Take all notes log them in so on. Well, Freeda can solve that problem.

Bill Sarda 9:43

Whenever you are on a customer call it is actually doing a live transcript takes all the notes for you, creates a call log, not only takes the notes but using NLP it is going through those notes and identifying the intent or any action item that you need to do as a part of follow up so it will take the notes, it will summarize them. And it will also create follow up action items that you can see here, the intelligent suggestions for So, and this is this something that you probably would have noticed, even during the call.

Bill Sarda 10:19

Now because it is able to understand language right from the call. We extended the same thing to emails, right, so the highradius collection solution, it also reads your incoming emails right whenever you’re sending a Dunning notice the customer replies. Can you give me a copy of proof of delivery, can you send me an invoice copy, it does that. So on the email open an email, and go through the details, it will actually identify what needs to be done in that email and show that intent to you and also create action items from emails, similar to how it does over calls. So your as an example, goes through the email identifies the intent is promise to pay right then there’s an amount so it captured that and made a suggestion, and users need to approve it.

Bill Sarda 11:21

So, Freeda, what else can you do. Thank you so much, Bill for introducing me to the audience today. Now let me tell them what I am learning right now and what I will be able to do in the future, I will be able to suggest real-time questions that you can ask your customer on comms provide suggestions on how to answer customer questions, predict the probable questions that your customer might ask, and identify the customer’s intent using sentiment analysis. I hope by doing this I will become your most trusted colleague. Thank you, everyone.

Bill Sarda 11:57

Any questions.

Bill Sarda 12:06

Alright, so if you don’t have any questions, that’s also my end but I do highly recommend, again, trying out the solution. Making a live collections call this, I mean, use it, see it to believe it, second floors, 3257 and 258. Thank you.

Enjoyed the Session?
Here are some other sessions you might be interested in

Experience the Power of AI-Enabled Receivables
& Treasury Applications

Schedule a free demo