How Local Tech Companies Use AI to Drive Decision-Making

February 25, 2020

Humans are inferior to technology when it comes to making objective decisions. According to Harvard Business Review, cognitive biases heavily influence judgment, often steering us away from objective decision-making. 

Companies are now turning to artificial intelligence to optimize their data-based business decisions. AI-driven workflows crunch data, consolidate insights and provide best possible outcomes, saving humans time, money and of course, error.  

At dealmaking software company Ansarada, Vice President of Sales, Americas Sean Elder said their AI Bidder Engagement Score assesses 57 separate data metrics to determine a bidder’s behavior. 

“This allows dealmakers — whose time is stretched thin during these events — to prioritize the serious bidders and focus their time and energy where it counts,” said Elder.

Leveraging AI does more than improve internal business decisions; it can also arm businesses’ customers with valuable information. Just as Ansarada helps dealmakers make better investments, KAR Global’s Pricing Insights allows customers to price their cars more accurately and find buyers faster. 

But humans aren’t obsolete — yet.

By removing humans from data processing, they can work on the business components that AI can’t replace, such as strategical insights, company values and mission and branding goals. 

To see how local tech companies are leveraging AI, we asked Elder and Rodney Ellis, director of data science at KAR Global, how they’re using the technology to inform decision-making and the impact that’s had on their businesses’ bottom lines.
 

KAR Global
KAR Global

KAR Global is a physical, online and digital auction marketplace where manufacturers, insurance companies and dealers come to buy, sell and trade used vehicles. Director of Data Science and Pricing Analytics Rodney Ellis told us how the company’s Pricing Insights tool uses AI-powered processing to give customers the best car pricing to sell their vehicles fast. 

 

How is your team currently leveraging artificial intelligence and/or machine learning to inform decision-making in a specific area of the business?

While some of KAR’s original equipment manufacturer (OEM) clients have an idea about how to price their vehicles, others have even less data-driven insights at their disposal. Enter Pricing Insights powered by DRIVIN. Pricing Insights uses AI and machine learning to equip our customers with real-time, data-driven pricing and channel optimization, allowing their off-lease vehicles to sell faster and for the best prices. When an off-lease vehicle first grounds, it is sold on OpenLane, KAR’s online, closed, upstream sales platform. With Pricing Insights, optimized pricing and channels are returned to the client within the OpenLane platform. This capability is real-time, meaning customers can immediately change their pricing strategy, allowing prices to be optimized relative to the vehicle’s market. 

The more AI/ML that is infused into KAR’s product and services, the more value is returned to our customers.’’  

 

What impact has AI/ML-driven decision-making had on the business thus far and what impact do you hope if will have in the future?

AI and machine learning-driven decision making are at the forefront of the capabilities that the DRIVIN team has built for KAR Global. Moving forward, they will continue to be the focal point of the team’s work. Products that leverage AI and machine learning-driven decision making provide our customers with valuable insights about their inventory that allows them to optimize their buying and selling strategies and ultimately increases their profitability. The more AI/ML that is infused into KAR’s product and service offerings, the more value is returned to our customers. 

 

Ansarada
Ansarada

Sean Elder, VP of sales, Americas, said the AI Bidder Engagement Score at Ansarada helps dealmakers make data-driven decisions regarding mergers and acquisitions, IPOs and capital raises. The AI Bidder Engagement Score gains smarter insights every time it operates. Thus, dealmakers have the confidence they are getting the strongest outcome with Ansarada’s platform.

 

How is your team currently leveraging artificial intelligence and/or machine learning to inform decision-making in a specific area of the business?

The team at Ansarada has built and honed the AI Bidder Engagement Score over the last two years. It’s a machine-learning algorithm that assesses 57 separate data room metrics to determine a bidder’s behavior, including factors like data room logins, time spent in room, C-suite engagement and more. 

The algorithm has successfully proven that it can identify who the winning bidder is likely to be, with a staggering 97 percent accuracy by day seven. This allows dealmakers — whose time is stretched thin during these events — to prioritize the serious bidders and focus their time and energy where it counts. 

They can confidently establish who the strongest bidders are while there’s still time to act on the information and impact the outcome of the deals. Basing these decisions on real data eliminates the guesswork and makes for much more efficient and effective dealmaking.

Basing these decisions on real data eliminates the guesswork and makes for much more effective dealmaking.’’

 

What impact has AI/ML-driven decision-making had on the business thus far and what impact do you hope it will have in the future?

In terms of impact on clients, we’ve had incredible feedback. One client, a director at a New York investment bank, has experienced a 100 percent success rate using the score to assess the winning prospect. Another, a partner at a major advisory firm, has called the insight “invaluable” to sales processes; the ability to assess how engaged a bidder is, quickly identify the stragglers and focus on the people that are genuinely interested in the asset can free up an enormous amount of time and reduce stress.

Our hope is that this impact continues to have a roll-on effect, especially from an advisor perspective where you have limited resources but need to get the best outcome. The more the tool is used, the more insights are gleaned and processes can get even more efficient and targeted over time. Ultimately, the impact we hope to have is confidence. We want to give dealmakers the confidence they will achieve the strongest outcome, every time.

 

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