Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

How AI Will Enhance the Compliance Industry in the Future

Compliance, sometimes referred to as governance, risk, and compliance (GRC), is slowly but surely benefiting from artificial intelligence (AI). Organizations of all sizes are starting to deploy AI and automation technology to better manage compliance disclosures and ethics training.

AI’s role in compliance will grow significantly in the next decade as systems evolve and organizations look to increase efficiency, make more informed decisions, and, ultimately, reduce legal and reputational risk amid increasingly complex regulatory and social environments. Compliance professionals will benefit not only from the data AI delivers but also from the time saved from busy work that the technology will handle.

Top AI ML insights: Winning the Analytics Battle in a New Decade of MarTech

Predictive Power

Currently, AI can be used to analyze compliance training data and identify individual users who may need additional learning and resources, and then automatically adapt the reinforcement learning experience to every employee. This frees up compliance professionals from poring through training results—which could number in the thousands or hundreds of thousands depending on the size of the organization—and creating hundreds of versions of reinforcement solutions, eliminating human error and deployment complexity.

Eventually, AI in compliance will move beyond base analysis to predictive integration. From triangulating training data, disclosure reports, and chatbots, systems will be able to flag high-risk teams and departments as compliance risks and take stronger measures on compliance procedures—such as automatically updating policies—to mitigate the danger. AI will see the threats that compliance professionals won’t have the time to discover, even if the threats are months or years in the future and thousands of miles away from the home office.

Top Analytics Update: Salesforce Service Cloud Gets New Advanced Embedded AI, RPA and Call Mining Features

Managing the Data

AI models for compliance processes require data—just like any other AI model. Bringing that data together will be the next progression to integrate AI and automation into compliance. Business processes are going to undergo the transformation that the world of marketing has seen in the last decade in predictive intelligence.

To truly achieve impactful risk insight, the data must show not only whether people are struggling but also why they’re struggling. This is why human behavioral data will be so crucial over the next decade. What are employees telling the hotlines that they’re reporting incidents to? What simulations during training modules do people continually struggle to navigate? What are the common denominators showing up again and again in disclosure reports?

Related Posts
1 of 7,487

Manually, overworked compliance teams may not be able to connect the dots from the data coming in. Digital technology opens the doors to find the trends, thus informing GRC strategy like never before.

Before that can happen on a wide scale, data from multiple compliance technologies within the organization will need to feed into a centralized system. We’ll likely see more tools emerge to make this convergence easier and give AI a chance to maximize its potential.

Overcoming the Challenges

A valid concern with AI in corporate compliance is the view that technology is replacing decisions that for decades have been made by humans. Furthermore, for ethics and compliance professionals to embrace AI, they need to move beyond these valid ethical and compliance concerns.

If the data going in is biased, the recommendations coming out might be too—we’ve seen this with hiring practices, loan applications, and other AI-assisted decisions that unintentionally violated regulatory standards. Because compliance teams are so focused on not violating standards, AI automation may seem risky.

Data privacy protections also represent a challenge for compliance teams to overcome. We may see more AI compliance inroads in the United States, where regulations aren’t as strict as, for example, in the European Union.

To avoid these challenges, corporations would be best placed to closely evaluate their data generation tools for response bias and utilize behavioral data as is rather than taking it through an interpretation or machine learning layer, avoiding the possibility for bias and other ethical implications.

Ultimately, AI won’t replace compliance teams, but it will help them do their jobs more efficiently.

GRC professionals will have the best insight at their fingertips to build strategy and mitigate risk. Compliance emergencies will decrease because organizations, with AI’s help, will be better able to anticipate challenges before they escalate.

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.