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Life sciences companies can face a range of challenges when looking to utilize data within their compliance program. 

In this interview for the Informa Connect Life Sciences Compliance and Legal Series, Lextegrity's Parth Chanda delves into some of those key issues. He also explains how they can be overcome with Lextegrity's off-the-shelf technology, which is designed to prevent and detect counterparty and spend risks through data analytics and automation.



Edited Transcript 

Parth, tell us a little bit about yourself and Lextegrity.

I'm the Founder and CEO of Lextegrity – an enterprise software company. I am a compliance lawyer by training and I am really specialized in FCPA healthcare compliance and kickback statute compliance.

I spent about a decade in-house, seven of which I was at Pfizer where I led their global anti-corruption program as well as compliance for their global oncology business. I had experience with their FCPA matter that ended up in a deferred prosecution agreement, and matters with patient assistance foundations that ended up in a CIA (Corporate Integrity Agreement) after I had left.

So, I had a lot of really deep experience working in high stakes matters and also in terms of implementing systems and controls.

In 2017, I decided to leave Pfizer to launch Lextegrity because I really didn't see good solutions from a technology perspective in the marketplace. I wanted to build the dream system I wish I had when I was in-house.

I partnered with a couple of other in-house former auditors and compliance professionals and we launched Lextegrity. Our purpose and goal is to provide technology that's off-the-shelf, but really powerful, to prevent and detect counterparty and spend risks using a mix of data analytics and automation.

We're differentiated in terms of what we offer in that we look at the entire life cycle of risk. From front-end budget approval workflows around HCP engagements, grants, donations and sponsorship, conflicts of interest and third-party onboarding, all the way through to using data analytics to monitor your enterprise spend data.

We apply advanced analytics to your data from systems like SAP, Concur, Oracle, aggregate spend systems, and so on.

We have had a lot of experience working with global pharma, biotech and med device companies and our technology has been battle-tested in front of regulators as well. We've appeared in three FCPA monitorships and our software was cited in Alexion's FCPA resolution as a remediation factor.


One of the things you emphasize is utilizing data more effectively to meet the DOJ's expectations. What are the challenges you see when you speak to life sciences companies around the use of data in their programs?

Let's start with the DOJ’s proclamations and their updated guidance (2020).

They put a clear stake in the ground in terms of their expectations that compliance, audit and other functions have access to data. But beyond access, to use that data analytically to test policies, procedures, the program itself, transactions, etc. And to do that in a more “real-time” way as opposed to periodically, by using more sophisticated analytics than random sampling.

So the challenge with that – and they've obviously seen very advanced companies come before them which has raised the standard in their eyes - is that for many companies, that's very difficult today.

Data is often sitting in silos throughout the organization. You may have access but you don't have access in a clear and easy way. Getting it, and then joining it all together to perform analytics on that data, is particularly difficult.

So when we think about that life cycle that I mentioned, a lot of processes may be in place around HCP engagements, grants and donations, third-party onboarding that are in different systems, that are in silos, that don't talk to one another, that don’t connect.

Then your enterprise data from your financial systems, aggregate spend systems etc., may not be brought in somewhere centrally and you may not be performing really advanced data analytics on that data.

We looked at this at Lextegrity as something that needed an end-to-end solution. Before us, there really wasn't one in the marketplace.

So really, it’s bringing technology to address the DOJ guidance head-on; bringing data analytics on your spend on the detective side (at the end of the process); and bringing technology on the front end workflow approval and diligence side to prevent things from happening and contracts from being signed before significant issues arise.


So how would you say an organization can go about solving that challenge - and how does Lextegrity attempt to solve this challenge for customers in the life sciences sector?

From a data analytics perspective, we take a really different approach in terms of risk scoring. We risk score transactions - ideally 100% of your spend items.

So, all of your invoices, your distributor transactions, your aggregate spend transactions, your expense line items from your Concur or other expense systems…everything goes through the system and has analytics applied to it in the same way to give each transaction an aggregated risk score.

Now that's really important because often compliance and audit teams are working on a sample basis, looking where they think they should be looking where you may have problems in areas or countries or markets or business units where you're not heavily focused.

But if you take the analogy of buying a car, consumer reports will assess a car and rate a car based on multiple factors. We're doing kind of the same thing for each spend item and in an automated way, so this is happening real-time in the background daily or weekly.  

We’re helping companies implement these really sophisticated tools out of the box without needing to hire armies of consultants. But then what we're doing is we're bringing in that data - those aggregated risk scores - giving the compliance team, audit team and investigations teams workflows to manage and escalate those transactions; follow up and document everything in one place; use that data to inform live monitoring, speaker audits, ride-alongs etc.

And then visualizing that data - because you're only going to have escalated to you those highest risk, small percentage of transactions – but since you have risk-scored everything, giving you visualizations to explore all of your data to your heart's content from a risk perspective.

So, not just looking at the highest spend HCPs, but looking at each with a risk lens of applying more sophisticated data analytics to their transactions.

On the data analytics side we're really helping organizations find those needles in a haystack using technology in a way that's very, very difficult (if not impossible) for humans to do in the traditional kind of audit/monitoring model. Then using machine learning and AI to improve that model over time.

We take the approach of really thinking about data analytics on the front end of that process as well. So we have a broad workflow engine that supports everything from HCP engagements, grants and donations, patient engagements ,annual needs assessments, political contributions etc.

We bring in data analytics there too, to automate fair market value to automate aggregate spend caps, provide contextual analytics etc., so that you can make determinations before an HCP is even engaged or a patient assistance donation is even provided.


That sounds impressive - is there anything you can show our audience that would bring this to life?

Yes! [Opens screenshare] So as I mentioned, we have those two sides of our application: the monitoring, and the pre-approval workflow system.

I’m going to dive into the continuous monitoring solution. It has three core components:

The monitoring review area, where we are risk-scoring transactions and escalating for review - those highest risk transactions.

The risk insights visualization engine - now that we've risk scored 100 of your items we're going to give you this powerful visualization engine

The compliance program scorecard that visualizes your compliance program KPIs, which is a nice benefit for compliance officers not to have to create, manually, Powerpoints every month for their board and C-Suite.

Let’s maybe to jump over to the settings area. This is really the brains of our data analytics solution. What we are doing here is providing our customers with a library of forensic data analyses without a single data engineer, data scientist or forensic auditor needed in the company.

They’re the types of analyses you could spend millions of dollars developing with a big four accounting firm but they all exist out of the box and they're highly configurable by you. Turn them on or off, change the weighting, all the way through to changing scoring criteria for each analysis.

These analyses are applied together to drive a risk score for that transaction. In the monitoring review area, you can see an invoice that has a 5.0 risk score (out of 5) because it has four different analyses that it has a match for, from a risk perspective.

What we're doing here is giving your internal compliance, audit and investigations colleagues a forensic digital file on this specific transaction. There’s a whole bunch of detail from the source systems as well as a narrative explanation for that risk score. Why is it risky? Let’s explain it to you to save you a lot of time.

And, if it is something that needs to be followed up, there's a full workflow with an audit trail - from the follow-on steps all the way through to corrective action plans and remediation - that can be driven from here.

So that’s the workflow that’s going to impact a small percentage of your transactions that are the highest risk.

But you have, now, risk-scored all of your transactions. So what we're doing in the risk insights area is giving you a data-driven risk assessment and visualization tool. You can see countries compared against one another not from a Corruption Perception Index perspective, but from where the true data risks are - where your spend-related risks are.

So now I can compare Russia to China to Mexico, and then I can explore and drill down on this data as far as I want. I can go from the country down to the specific vendors and employees in that country.

Maybe I want to look at one person’s specific transactions and profile. I can then pull up all of their expenses, risk scored, where they are on every analysis.  

This is a really powerful tool for investigators. It really helps them not having to wait for Finance and IT to get them data weeks later. They can come in and find risk-scored information in seconds.

This is also really powerful for audit, the live monitoring team etc. So that's those are the core elements of our continuous monitoring tool.


Where can our audience go to hear more about this?

Well you can reach out to me - I'm always happy to connect with fellow compliance, audit and investigations peers. We'll also be at the Informa Compliance Monitoring & Data Analytics Conference in Philadelphia in February (2022) so we look forward to seeing you all there!


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