In today’s rapidly evolving digital world, companies across the globe are integrating artificial intelligence (or AI) into their business operations. Businesses of varied types and sizes now regularly use AI in multiple ways. The investment and financial industry is no different and is a good example of this technology adoption trend.
Dr Leen Kawas
Within the financial industry, investment firms operate in a distinctive niche. Leen Kawas, Ph.D. is Propel Bio Partners’ co-founder and Managing General Partner. Propel Bio Partners is an investment firm that provides financial resources and technical expertise to biotechnology companies.
In her Propel Bio Partners leadership role, Dr. Kawas continues to explore AI’s utility in the firm's operations. She believes AI can provide significant advantages for companies introducing significant efficiencies.
Investment Candidate Selection Criteria
Each speculative investment has considerable risk. In addition, the firm is likely besieged with emerging companies seeking cash and/or technical expertise. To formulate an investment candidates shortlist, the venture capital firm uses several predetermined criteria.
Experienced Management
Investment firms want to invest in a company led by a seasoned management team. Ideally, the business’ leaders will have proven success in delivering good returns for previous investors.
Significant Market Size
According to a recent Forbes article by Leen Kawas, Investment firms are looking to invest in companies with substantial market size. A $1 billion market size would likely get a venture capital firm’s attention and potentially its investment dollars.
Quality Product with a Market Advantage
Ideally, the company’s product or service will provide a real solution to a common marketplace problem. The offering should be better (and less expensive) than competitors’ products or services. The venture capital firm wants to rack up substantial sales before competitors reduce the item’s profitability potential.
The favorable upside to downside profile
Every start-up or emerging business investment carries substantial risk. The venture capital firm may be concerned about the company’s financial resources, potential regulatory or legal problems, and an unclear exit strategy. Each business’ overall risk profile and potential upside is a major factor in the investment decision. If there is a clear skewed probability of success with a significant upside then this would make a unique and attractive investment opportunity.
How AI Can Change the Playing Field
Evaluating each potential investment target takes time, and many companies are looking for investment dollars. To streamline the process, investment firms have begun to integrate AI technology into multiple aspects of the candidate selection process.
Enhanced Industry Trend Analysis
Investment firms closely monitor industry trends and technologies. Done consistently, this information can highlight emerging opportunities and challenges.
AI-driven software seamlessly accomplishes this task by gathering relevant data from news articles, credible studies, social media, and other sources. Finally, AI identifies candidates with pioneering technologies that may optimize opportunities and resolve challenges.
More Efficient Due Diligence
Conducting thorough due diligence on investment candidates is important. Equipped with relevant data, an investment firm executive can make a better-informed decision on allocating the firm’s funds. However, sifting through multiple candidates’ application materials is a time-consuming task.
Fortunately, AI-enabled software can analyze targeted data in an accurate way if the investment criteria are clearly defined, which will lead to an efficient triaging of opportunities. To illustrate, the AI software swiftly scans all candidates’ legal documents, financial statements, pitch decks, and other documentation. One growing aspect is the ability of AI software to provide detailed information on intellectual property, an early indication of the freedom to operate in a specific space, and most importantly, the competition that is out there. Based on the results, AI-driven software can pinpoint early-stage businesses that may match the firm’s investment parameters.
Examples of firms that use AI
In Stockholm, Sweden, EQT Ventures integrates its proprietary “Motherbrain” AI platform into the firm’s initial candidate evaluations. The platform rates investment candidates on a 1 to 340 scale. The company’s investment professionals first evaluate the higher-ranking companies.
For perspective, Motherbrain helped to facilitate four initial investment opportunities. One of those companies has already been sold at a significant profit.
Targeted Fundraising Initiatives
Investment firms depend on a steady influx of investor cash. With that said, the typical fund manager must evaluate a large volume of investment opportunities and potential investors. Even the most efficient fund manager would find this a laborious, time-consuming task.
That’s where AI can help. First, AI-enabled software creates individual investor profiles. Next, the AI evaluates each investor’s risk tolerance, physical location, and investment history.
Equipped with this information, an AI algorithm produces a profile of optimal investors for each fund. Now, a fund manager can market to prospects who are most likely to say “yes.” This maximizes the manager’s time, and the fund’s resources, that might have been wasted on poorly qualified prospects.
Optimizing Investor Exchanges
Interestingly, AI can also conduct optimized exchanges with investor prospects. First, the AI algorithm analyzes an investor’s tone and language. Based on the results, a fund manager can create a message likely to persuade that individual to invest in the fund. This tactic can be especially effective when a fund manager wants to communicate highly technical information to a non-expert audience.
Two Notable AI Applications
The venture capital industry is increasingly making use of two AI applications. These AI subsets are typically used in the investment candidate evaluation process.
Natural Language Processing
A natural language processing (or NLP) algorithm analyzes an investment candidate’s corporate language and investment presentations. Based on the results, the algorithm presents details of a start-up’s competitive landscape. Now, a venture capital firm can identify candidates with a good value proposition and a favorable industry position.
Machine Learning Algorithms
Machine learning is a system’s ability to learn from large dataset analyses. Through repeated use of an algorithm, the system gradually makes better-informed decisions. Machine learning algorithms have at least two venture capital industry applications.
After some training, a machine learning algorithm can predict a candidate’s performance based on its financial reports and data. To illustrate, the algorithm could predict a candidate’s revenue growth relative to its previous financial performance. This enables the venture capital firm to deliver a higher-accuracy assessment of the company’s success potential.
Machine learning algorithms can also analyze non-traditional datasets. The algorithm could gradually become adept at analyzing social media data, revealing candidates that are gaining consumer recognition. Even if the brand is relatively new, or doesn’t have a big following, the company could be a viable investment target.
Signalfire’s AI Evolution
Since 2013, early-stage investment firm SignalFire has used Beacon, an AI-enabled software, to enhance the firm’s investment activities. During the past decade, SignalFire has directed Beacon’s performance of increasingly complex tasks.
Historically, Beacon has gathered internal and competitive data on SignalFire’s investment candidates. The company also used AI for multiple back-office operations. However, today Beacon has morphed into a generative AI function similar to the increasingly popular ChatGPT.
With its large language model capability, Beacon can now seamlessly interpret huge volumes of information. Therefore, SignalFire can now view companies’ similarities and interrelationships without the extra steps required in previous iterations.
How AI Can Transform Recruiting and Hiring Practices
Companies’ human resources departments are increasingly integrating AI tools into the recruiting and hiring process. These time- and cost-saving technologies enable hiring managers to focus on higher-value tasks. In turn, AI can enhance each business’ operating and competitive positions.
Candidate Identification Tasks
AI tools can perform large-scale resume and social profile scanning along with viewing previous position applications. An AI model can also be trained to eliminate unconscious bias in the recruiting process.
Taken together, these tasks should produce a well-rounded talent pool for each opening. However, the AI tool takes it one step further, guiding candidates through the recruiting process.
Targeted Talent Acquisition
To identify in-person interview candidates, the AI tool can perform personality testing, job simulation, and virtual interview functions. Candidates who successfully navigate this process are more likely to match the position requirements and sync with the company’s culture.
Streamlined Onboarding Process
Once a candidate accepts a position, the AI tool can handle repetitive tasks such as performing background checks and assembling required documentation. This enables faster employee onboarding and permits human resources staff to focus on higher-level issues.
Dr. Leen Kawas Envisions an AI-Enhanced Future
In her Propel Bio Partners leadership role, Dr. Leen Kawas regularly handles investment candidate engagement and technical support tasks. Before assuming her Propel Bio Partners position, Dr. Kawas excelled as Athira Pharma’s Chief Executive Officer. She successfully guided several drug developments and led the company through its initial public offering in September 2020 raising over $400 million to support the company's growth and advancement.
Today, Dr. Leen Kawas channels her background and industry expertise to guide emerging biotechnology companies forward. She embraces the advantages AI tools can bring to the financial and biotech industries. Dr. Leen Kawas believes AI’s current applications only scratch the surface of this powerful technology.