CONVERGE is in its 6th year of bringing together the world’s leading companies for 2 days of dynamic speakers, thought-provoking breakout sessions, and opportunities to connect with like-minded professionals. This year the conference has gone virtual. You will leave the conference with new resources and best practices allowing you to continue the hard work of driving ethics to the center of your business. In today’s episode I visit with Philip Winterburn. We visit about his presentation at Converge21 on Digital Ethics: AI, Privacy and More.
A successful whistleblowing program doesn’t start with installing a helpline–it starts with fostering an environment that protects whistleblowers, makes them feel supported, and makes clear the value they bring to the business. So how do you build that “speak-up culture?” Join this session to hear from a panel of practitioners who manage whistleblowing programs and whistleblower advocates who’ll share their insights, experiences, and challenges they’ve faced.
For more information and , go to Converge21.
Tag: AI
Welcome to the Great Women in Compliance Podcast, co-hosted by Lisa Fine and Mary Shirley.
Colleen Dorsey, our Great Woman in Compliance of the week, is well known for influencing Compliance careers early – she leads the University of St Thomas Compliance programming, preparing our Compliance Officers of tomorrow. Get a behind the scenes look into the evolution of Compliance education at the tertiary level.
Also in this episode Colleen gives the GWIC listenership a run down on using Artificial Intelligence and Machine Learning in Compliance programs. In Compliance, as with everything else, it’s important to keep up with new developments and tools that can help us achieve our goals more accurately and more efficiently. Those who don’t keep up will most certainly get left behind. Fortunately Great Women in Compliance listeners are invested in their own professional development and keep up with the wealth of information provided by GWIC guests. Colleen gives basic understanding to lay the foundation of what AI and Machine Learning are and explains how these tools can be used to benefit Compliance programs, using a real life example and what the future might hold for these areas.
Finally Colleen shares some of her wisdom surrounding self-awareness – you cannot improve yourself unless you know what you’re working with and where your gaps are so it’s important to be honest with yourself and be able to self-reflect objectively – with the help of others where necessary. Mary weighs in with some sound practical advice from Organizational Psychologist Adam Grant with a tip to make soliciting feedback easier for yourself and those around you.
Corporate Compliance Insights is a much appreciated sponsor and supporter of GWIC, including affiliate organization CCI Press publishing the related book; “Sending the Elevator Back Down, What We’ve Learned from Great Women in Compliance” (CCI Press, 2020). Thank you to all those who have taken the time to rate the GWIC podcast and book, it’s much appreciated.
If you’ve already read the booked and liked it, will you help out other women to make the decision to leverage off the tips and advice given by rating the book and giving it a glowing review on Amazon?
As always, we are so grateful for all of your support and if you have any feedback or suggestions for our 2021 line up or would just like to reach out and say hello, we always welcome hearing from our listeners.
You can subscribe to the Great Women in Compliance podcast on any podcast player by searching for it and we welcome new subscribers to our podcast.
Join the Great Women in Compliance community on LinkedIn here.
Over a couple of blog posts, I am exploring topics raised in a recent Harvard Business Review (HBR) article, entitled “How to Design an AI Marketing Strategy: What the technology can do today—and what’s next”, by Thomas H. Davenport, Abhijit Guha, and Dhruv Grewal where the authors focus on the use of Artificial Intelligence (AI) in marketing. I believe their work could be adapted for the compliance professional. Yesterday, I used the article as a jumping off point about how Chief Compliance Officers (CCOs) and compliance professionals can use AI for internal compliance communications and communications with key stakeholders outside your organization that you need to work with on compliance, such as third-party agents and vendors in the Supply Chain. Today I want to consider the framework that a compliance professional can implement to use these tools effectively for both internal and external marketing of a corporate compliance program.
The authors posit that AI can be categorized according to two dimensions: intelligence level and stand-alone or integrated platforms. Further, the intelligence level can be broken down into two subgroups: task automation and machine learning. Task automation performs “repetitive, structured tasks that require relatively low levels of intelligence.” They bring a level of ease as they are “designed to follow a set of rules or execute a predetermined sequence of operations based on a given input” However, such tools cannot handle complex problems such as nuanced employee requests for information. Chatbots fall into this category. Such tools can provide basic assistance to employees during basic interactions, moving employees down a defined decision tree, but cannot ascertain intent, offer customized responses, or learn from interactions over time.
With machine learning, “algorithms are trained using large quantities of data to make relatively complex predictions and decisions.” Such algorithms can decipher text, segment issues, and anticipate how employees will respond to various initiatives. Moreover, machine learning can drive programmatic decision-making in a compliance program for employees through a “customer relationship management system”. The next step is what the authors term the “more sophisticated variant, deep learning, are the hottest technologies in AI and are rapidly becoming powerful tools in marketing.” That said, it’s important to clarify that existing machine-learning applications still just perform narrow tasks and need to be trained using voluminous amounts of data.
Stand-alone applications are “best understood as clearly demarcated, or isolated, AI programs.” Conversely, integrated applications are embedded within existing systems and such AI applications are often less visible than stand-alone ones. This allows employees to be delivered a more sophisticated solution for the Quote To Cash (QTC) or Procure To Pay (P2P) processes. With a stand-alone system, employees need to go to a dedicated app and request suggestions. It appears that compliance professionals will “see the greatest value by pursuing integrated machine-learning applications, though simple rule-based and task-automation systems can enhance highly structured processes and offer reasonable potential” for not simply more efficient compliance processes but for commercial returns.
For corporate compliance professionals with limited AI experience, perhaps the “way to begin is by building or buying simple rule-based applications.” You can start with “crawl-walk-run” approach. Once a compliance function acquires basic AI skills and an abundance of data, you can start moving from task automation to machine learning. Moreover, new sources of data, “such as internal transactions, outside suppliers, and even potential acquisitions”, are something compliance functions should have access to, since most AI applications, particularly machine learning, require vast amounts of high-quality data. Once again this is precisely what the Department of Justice (DOJ) specified in the 2020 Update to the Evaluation of Corporate Compliance Programs when it mandated that compliance have access to all corporate data even when siloed.
There are challenges in implementing an AI tool for communications as “implementing even the simplest AI applications can present difficulties. Stand-alone task-automation AI, despite its lower technical sophistication, can still be hard to configure for specific workflows and requires companies to acquire suitable AI skills.” It will also require “careful integration of human and machine tasks so that the AI augments people’s skills and isn’t deployed in ways that create problems.” The bottom line is that while AI holds enormous promise, for compliance professionals for a variety of uses, it still accomplishes only narrow tasks.
But it will be a journey for compliance. The compliance function “and the organizations that support it, IT in particular, will need to pay long-term attention to building AI capabilities and addressing any potential risks.” Yet compliance professionals cans start developing a strategy today to take advantage of AI’s current functionality and its likely future. Compliance communications to both internal and external stakeholders is certainly one use that should be on your horizon. When we receive the next iteration of the Evaluation of Corporate Compliance programs you may well see AI specifically called out as a tool, the DOJ may expect multi-national companies to have AI in place and be using for a variety of compliance activities.
Many Chief Compliance Officers (CCOs) are still challenged by the concept of internal marketing for a compliance program. Indeed folks like Ronnie Feldman, founder of L&E Creative, and Ricardo Pellafone, founder of Broadcat, are on a mission to move the compliance profession away from rote, boring and frankly useless training and communications tools. I was therefore intrigued by a Harvard Business Review (HBR) article, entitled “How to Design an AI Marketing Strategy: What the technology can do today—and what’s next”, by Thomas H. Davenport, Abhijit Guha, and Dhruv Grewal where the authors focus on the use of Artificial Intelligence (AI) in marketing. I was interested in how their work could be adapted for the compliance professional. Over the next couple of blog posts, I will be using this article as a jumping off point about how CCOs and compliance professionals can use AI for internal compliance communications and communications with key stakeholders outside your organization that you need to work with on compliance, such as third-party agents and vendors in the Supply Chain.
The authors posit that in order to realize AI’s giant potential, marketers (or CCOs) need to have a good grasp of the various kinds of applications available and how they may evolve. They categorize AI along two dimensions: the first is the intelligence level and whether it stands alone or is part of a broader platform. Simple stand-alone task-automation apps are a good place to start. The second is the advanced level, which integrates applications that incorporate machine learning and have the greatest potential to create value.
Compliance marketing has a huge amount to gain from the use of AI. This is because a marketer’s core activities are to understand customer needs, matching them to products and services, and persuading people to utilize those products or services. These are all capabilities that AI can dramatically enhance. The only difference for the compliance professional is that your customers are your employees and third parties to your organization that need compliance communications.
The authors note that AI has made inroads in marketing, and they well expect it to take on larger and larger roles across the function in the coming years. With the enormous potential of AI, it is important for all compliance professionals to understand the types of marketing AI applications available today and how they may evolve. One of the key changes for compliance coming out of the Covid-19 pandemic has been the use of data. This same use of data can be applied to internal and stakeholder communications for your compliance program through AI strategies such as Robotic Process Automation (RPA).
Many corporate compliance functions now use AI to handle narrow tasks, assist with broad tasks, like enhancing the accuracy of predictions, and augment human efforts in structured tasks, such as customer service from the compliance function. There are multiple examples of current uses of AI by compliance. Some of these include:
- Chatbots for employee support,
- Inbound call analysis and routing, and employee comments and email analysis, classification, and response,
- Marketing campaign automation,
- Social-media planning and execution,
- Social-media sentiment analysis,
- Web analytics narrative generation,
- Website operation and optimization.
However, you can use AI in marketing for a wider variety of the employee lifecycle. When potential employees are in the pre-hire “consideration” phase and researching your organization, AI can help guide their search and this task. After hiring, AI-enabled bots can help compliance professionals understand employees’ compliance needs, increase their compliance engagement in a search, nudge them in a desired direction, and if needed, connect them to a compliance professional by chat, phone, video, or even “cobrowsing”—allowing a compliance professional to help an employee navigate a shared screen. Does that sound like marketing? You bet it does and that is why every CCO and compliance professional needs to learn to think like a marketer.
AI can streamline the compliance process by using extremely detailed data on employees, including real-time geolocation data, job duties, sales information from platforms, such as Salesforce, and other information to create highly personalized compliance offerings. But this is not a one-time communication. As an employee moves through the sales cycle with a customer, AI can reduce the likelihood that the employee will abandon their compliance focus by not simply reading updated communications. AI can synthesize additional information as an employee moves through the sales lifecycle (i.e., Quote To Cash) or on the vendor side of things (i.e., Procure To Pay).
After the sales cycle is concluded or after a new third-party sales agent is contracted, AI-enabled agents can be available 24/7 to triage employees’ requests—and are able to deal with fluctuating volumes of service requests and inquiries. They can handle simple queries can escalate more-complex issues to a compliance professional. In some cases, AI assists compliance professional by analyzing employees’ tone and suggesting differential responses, coaching compliance professionals about how best to satisfy employees’ needs or suggesting intervention.
If all of this sounds like a brave new world of compliance; it is. But that world is here now, and it is in marketing. These new concepts for compliance demonstrate the speed at which compliance is evolving and how data collection (continuous monitoring) and its use (continuous improvement) is required. Now does that sound familiar? Of course it does, as that is precisely what the Department of Justice (DOJ) set forth in the 2020 Update to the Evaluation of Corporate Compliance Programs.
Join us on Wednesday where I look at the authors’ framework for implementing the use of AI in compliance marketing.
In this podcast we explore how new advances in artificial intelligence and machine learning take on the challenge of hunting for insider risks within your organization. Insider risks aren’t easy to find, however, with its ability to leverage the power of machine learning, artificial intelligence can uncover hidden risks that would otherwise be impossible to find.
Listen to the episode now:
Welcome to Uncovering Hidden Risks, a broader set of podcasts focused on identifying the various risks organizations face as they navigate the internal and external requirements they must comply with. We’ll take you through a journey on insider risks to uncover some of the hidden security threats that Microsoft and organizations across the world are facing. We will bring to surface some best-in-class technology and processes to help you protect your organization and employees from risks from trusted insiders. All in an open discussion with topnotch industry experts!
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Tom Fox welcomes Simon Moss to this week’s show. Simon – who describes his background as “eclectic”, having worked in and led many companies over his career, including IBM – is now the CEO of Ayasdi, one of the most innovative companies in the artificial intelligence space. Simon and Tom discuss the important work Ayasdi is doing for its clients.
The Data Problem
Tom asks why AI can’t seem to keep up with the volume of data that needs to be reviewed for AML, ABC and trade sanctions. Simon disagrees that it’s an issue of volume. The problem is diversity and distribution. He says, “The problem with data now is that it is so diverse, so distributed, and we’re still trying to deploy products of extraordinary innovation – including AI products – in the same ways as we did in the 1970s.” He laments that we try to homogenize data into a construct, which uses 80% of our data management resources. “We have institutionalized redundancy in data management, and it is getting worse because of the proliferation of data sources.” While this structure works for data at rest, it is unsuitable for unstructured data and data in use.
A Unique Approach
“We don’t use the data model approach,” Simon remarks. Ayasdi believes that a company is represented in its data, so they create a model that is unique to each client. “…it knocks 40 to 50% off the time to actually deploy innovation,” he says. He explains why machine learning cannot effectively predict or discover crime or compliance issues. “Hypothesis-based machine learning is brilliant for finding a needle in a haystack… The problem with compliance is you’re looking for a needle in a stack of needles.” Ayasdi’s approach, on the other hand, is to let the data tell the story. “The breakthrough that Ayasdi uses,” Simon says, “is what’s called unsupervised learning as part of a machine learning process. In other words, we are not going to give the software a hypothesis of what to look for. We simply say, ‘Go find interesting stuff.’ Let the data tell us the story.”
Innovating for the Future
Ayasdi is engineering the operational diligence and deployment needed for the future. It was technology that drove the blue collar transformation of the early 2000s, and it is technology that will drive the transformation of the white collar industry over the next decade. “We’re engineering our technology to make sure that we can service a customer expectation in the future,” Simon says. Tom comments, “It strikes me that the insights that could be generated [go] really far beyond the anti money laundering and fraud and corruption.” Simon agrees. He shares three examples of how Ayasdi has helped their clients gain valuable insights and profit from them. “What we’re doing is we’re creating true Alpha. We’re creating true opportunity and we’re creating true transparency. When those decisions are made, you know that the decision that has been created has all the explainability, all the referential insight that’s needed, all the appropriate data, so that when a regulator comes in and says, Why did you do this? It’s all completely supported.”
The true challenge of innovation, Simon argues, is that a solution works at scale. “The challenge is, How do you optimize the operating model of an institution? And you do that by looking at the institution as a whole.”
Resources
Ayasdi.com
Simon Moss on LinkedIn
In this episode, we discuss the rapidly expanding use of artificial intelligence, machine learning and robotic process automation to undertake trade surveillance and mitigate fraud. In this episode, we discuss the rapidly expanding use of artificial intelligence, machine learning and robotic process automation to undertake trade surveillance and mitigate fraud. Joining me today are two experts on the subject of Artificial intelligence from both the technical and legal and compliance perspectives.
Join us each week as we take a deep dive into the various forms of fraud across the world and discuss crime families, penny stock boiler rooms, international money launderers, narco-traffickers, oligarchs, dictators, war lords, kleptocrats and more.
Scott Moritz is a leading authority on white-collar crime, anti-corruption, and in the evaluation, design, remediation, implementation, and administration of corporate compliance programs, codes of conduct. He is also considered an authority in the establishment, training, and oversight of the investigative protocols carried out by financial intelligence, corporate security, and internal audit units.
In this week’s Innovation In Compliance show, Tom Fox, together with guests Sean Freidlin, Yan Tougas and Patrick Henz, have a roundtable discussion about their experience with taking Seattle University’s free course, AI Ethics For Business. They chat about what they felt were the highlights of the course, as well as the opportunities for improvement.
Patrick Henz
Patrick likes how trainers from different disciplines work together as a team to present the course. He suggests that this interdisciplinary approach could be used by companies for compliance training, since compliance is becoming more of an integrated function, mainly due to budgetary constraints. Patrick emphasizes the importance of continuous learning: the world is changing so quickly that we cannot rely solely on our university training to keep abreast.
The topic of robotic process automation was missing from the course, Patrick thinks. He believes that psychology and ethics, topics discussed in the first module, are relevant for all compliance practitioners. He comments, “We’re not only here to identify the bad employees but furthermore to protect the good employees, which includes protecting them against themselves…”
Yan Tougas
Organizations using and/or creating AI must create their own set of governing values and principles from the outset, Yan points out. Two of those values should be transparency and agency. “If we are going to use AI to make some critical decisions about people’s welfare,” Yan says, “…we need to create room in the process for a human to make a final decision.” He points out that the pressure to rush to market is one reason companies do not create their own values and principles around AI. “We need to be extra careful and make sure that we don’t let this pressure to get to market and this pressure to adopt AI blind us from the homework we need to do up front,” he comments.
Yan appreciates the Operational Readiness document in Module Three, which he describes as a practical tool compliance practitioners can use. On the other hand, he thinks that the user interface and the quizzes at the end of each module could be improved.
Sean Friedlin
Sean finds it refreshing that a large corporation such as Microsoft has partnered with Seattle University to create free training for the public good. He hopes that more companies would embrace these types of partnerships in the spirit of corporate social responsibility. Sean sees this as the emergence of a deeper commitment to ethics as AI develops. He notes with interest that the Vatican has joined in this conversation.
Sean poses two interesting questions:
- What impact will COVID-19 have on AI advancement?
- What makes a good online learning experience?
Having the subject matter experts as narrators and anchors throughout the course establishes their credibility; Sean views this as a pattern other course creators should follow. He finds the course content too text-heavy, however, and the UI design mobile unfriendly.
Tom Fox
The exercise emphasized for Tom the need for companies to start with ethical values and accountability for the entire organization. You cannot simply ask those involved with these cutting-edge questions to be the sole corporate repository of ethical and moral values, he argues. Put these values in place now, enshrine them throughout your organization so when the
business opportunity or a crisis arrives, you would already have the framework in place to make a decision aligned with your company values.
The course is a good reminder to consider governance and structure as part of your compliance regime, Tom comments. It was a positive experience overall; however, it may not work for ongoing communications or training due to time.
Resources
Seattle University course- AI Ethics for Business
Rome Call for AI Ethics
Rome Call
Vatican joins IBM, Microsoft to call for facial recognition regulation
One thing is certain going into 2020 and beyond is that technology that will improve the efficiency of compliance and will assist in the operationalization of compliance into fabric of every business which embraces it. I would posit that the compliance professional who incorporates the techniques they advocate into their organization’s compliance program will not only move their compliance program forward but also make their company run more efficiently and, at the end of the day, more profitably.
AI is a step which weds the human interaction and experiences with the data which is available to every company – its own internal information which is most generally sitting in siloed verticals and not being used. This data can provide the foundation for business research and risk-forecasting models and AI. When you couple this data with the insights into what humans do well or poorly; you can pair the best of these two seemingly disparate incongruities. Moreover, when a compliance function embraces the use of AI and embraces this human and technological approach for forecasting and risk assessments and then keeps improving their risk management techniques, it will create a sustainable strategic business, compliance and intelligence advantage over its competition.
Three Key Takeaways:
- Use the big data in your own organization.
- Break down silos to get the data.
- Using the data in your own organization will drive greater business efficiency and greater profitability.
We previously considered how AI can be used as a business advantage for compliance. The power of AI can extend the more traditional functions of prevention, detection and remediation. The first way is in simply the mass amount of data which could inundate a compliance practitioner. Many compliance practitioners are overwhelmed about the amount of data available to them and do not know how or even where to begin.
Patrick Taylor has said that AI allows the compliance practitioner to understand the “subtle clues in that pattern of activity that will clue me in to take a different look.” He likened it to seeing “patterns in raked leaves” which allows you to then step in and take a deeper and broader look at an issue, either through an audit or investigation. This is where compliance practitioner can step back and literally keep an eye on the big picture and longer term as opposed to just the immediate numbers and information in front of them. It may also be the best hope for finding that kind of systemic fraudulent behavior
Three key takeaways:
- Do you know what your information means?
- AI can help both the detect and prevent prongs in a best practices compliance program.
- AI can help you to see the patterns in raked leaves.
