Minerva is a risk assessment platform that is purpose-built to counter money laundering at a large scale. Pulse 2.0 interviewed Minerva CEO and co-founder Jennifer Arnold to learn more about the company.
Background Of The Founders
What is the background of the founders? Arnold said:
“My co-founder and I worked in traditional financial institutions (banks), designing and deploying Anti-Money Laundering (AML) programs. It was deeply frustrating to watch investigators spend hours cobbling together contextual information about a client to perform risk assessments, using systems that weren’t even dealing in live data.”
“The process was manual, slow, and error-prone, and because of this, the cost of AML compliance is a growing cost center. In leadership roles at Wells Fargo, CIBC, and BMO, I became all too familiar with the challenges of designing and implementing AML programs without introducing unnecessary complexity or cost. Now, we’re building efficient, effective solutions that scale for financial crime fighters everywhere.”
Formation Of Minerva
How did the idea for Minerva come together? Arnold shared:
“Minerva was inspired by our experience working in banks and watching talented investigators leave the industry because their profession had been turned into a call center. Minerva is my love letter to investigators so that they can actually perform risk assessments without all the wasted time and noise.”
Favorite Memory
What has been Arnold’s favorite memory working for the company so far? Arnold shared:
“We just had our first-ever company retreat. It was thrilling to see everyone, eat with everyone, and play with everyone in the same place for the first time.”
Core Products
What are the company’s core products and features? Arnold explained:
“Minerva is a real-time client risk and AML assessment platform that enables investigators to make accurate and high-quality risk decisions in just a few minutes. Minerva helps our customers with three core problems they face every day: 1) an overabundance of false positives; 2) the time and cost of investigations; and 3) difficult conversations with regulators where the financial institution is trying to demonstrate they have a risk-based approach, complied with the regulations, and consistently adjudicate risk.”
“Minerva uses sophisticated deep learning models and neural networks to analyze billions of data points and sources in real-time across 147 languages to help compliance teams get ahead of financial crime, prevent money laundering, and comply with government regulations. Using artificial intelligence (AI) gives us a significant competitive advantage by automating a manual process that could take hours or days and returning results 300 times faster, reducing costs by 55 percent. By automating the process with AI, Minerva is able to provide ongoing monitoring, enabling continuous risk assessment.”
“With its ability to instantly understand context, sentiment, and risk across structured, unstructured, open source, and proprietary data, the Minerva platform creates context-rich customer profiles and predictive risk analysis in real-time. Minerva is trusted by leading financial institutions that require faster, more accurate risk assessment results.”
Challenges Faced
What challenges has Arnold faced in the sector? Arnold acknowledged:
“Building a start-up is always challenging. You’ve got to move like water. As a new company in a highly regulated industry, it is a long road to build up your reputation, credibility, and trust with legacy financial institutions – even if you worked with and for them for years. In our excitement and naivete, we built Minerva for those big banks because their pains are so obvious and acute to us. So it was very disappointing when they wouldn’t engage.”
“So we started looking for a market segment that looked and acted like a bank, from an AML tech stack perspective, meaning lots of legacy tech, backlogs of alerts and cases, growing cost centre, increasing regulatory pressure, and scrutiny, etc. It became very clear, quite quickly, that crypto exchanges were a great fit for our tech where we could add immediate value.”
Evolution Of Minerva’s Technology
How has the company’s technology evolved since launching? Arnold noted:
“Minerva made significant advancements in our proprietary deep learning-powered investigations model, which performs at a 1 in 1000 error rate for investigation decisions on open-world data. Minerva has also made proprietary advancements in the field of named entity recognition on open web data. Internal language models and datasets are being tested in early research to recognize and associate unique individuals and identifiers in OSINT data for client risk assessment.”
Significant Milestones
What have been some of the company’s most significant milestones? Arnold cited:
“Start-ups measure their lives by customer growth (traction) and funding. Closing our seed round in mid-2021 was a changing point for us where we could expand the team beyond the founding team. Adding premiere organizations like Coinbase and Equifax to our customer roster was a huge celebration point for us. And, of course, our Series A at the start of 2023 was more cause for celebration.”
Customer Success Stories
After asking Arnold about customer success stories, she highlighted:
“One specific customer example is MOGO, an organization that is on a mission to make it easy for Canadians to achieve financial freedom while making a positive impact.”
“MOGO faced hurdles in identifying Politically Exposed Persons (PEPs) due to broad definitions by regulatory bodies like FATF and FINTRAC – covering politicians, international organization heads, and their associates, which complicated screening and put their compliance at risk. In addition, as many individuals were unaware of their PEP status (which can change over time), this added complexity to MOGO’s compliance efforts, requiring continuous monitoring and profile updating.”
“MOGO also struggled with outdated or specific-issue-focused lists for PEP identification, making the process time-consuming and error-prone, leaving them vulnerable to regulatory scrutiny.”
“These issues were further compounded by the fact that MOGO was dissatisfied with their previous service provider, which stemmed from reliance on outdated keyword matching, limited data access, and manual efforts, which were inadequate for evolving regulatory demands. In addition, previous PEP screening yielded incomplete results that lacked the depth needed for regulatory requirements, prompting MOGO to partner with Minerva for AI-driven screening and entity resolution.”
“By switching to Minerva’s AI-powered screening and entity resolution platform, MOGO addressed these challenges. In the context of daily sanctions and PEP screening, by using Minerva, MOGO enabled daily screenings, accurately identifying PEPs within just 1% of their customer base, aligning with their risk management strategy. MOGO also expanded their integration with Minerva to include ‘Legal Data,’ broadening risk assessment to regulatory disciplinary actions and cease trade orders, enhancing compliance and stakeholder confidence. MOGO went live with Minerva in October 2021.”
Funding
After asking Arnold about the company’s funding information, she revealed:
“With the last round of funding in January of 2023, Minerva has raised $11 million. FirstMark Capital is the largest investor.”
Total Addressable Market
What total addressable market (TAM) size is the company pursuing? Arnold assessed:
“Anti-money laundering is a $221 billion global market according to LexisNexis ‘True Cost of AML 2023.’”
Differentiation From The Competition
What differentiates the company from its competition? Arnold affirmed:
“Minerva provides actionable insight to users in just a few seconds, instead of hours or days of manual investigation work. Our platform is powered by sophisticated yet transparent deep learning and machine learning models, creating comprehensive customer risk profiles and enabling predictive risk analysis.”
“What makes all this possible is our entity resolution. Entity resolution is very challenging to apply to open source and unstructured data due to the amount of contextual and semantic insight that is required to correctly read and understand the text before consolidating. Minerva’s entity resolution engine, which leverages neural networks to automate the investigation process and connect the dots in the data to build unique profiles, has been trained on over 5 million investigation decisions to emulate the human investigation intuition at scale and in much shorter time scales.”
“Minerva ingests data using automated means and then hands that data off to the investigations model to connect the dots and perform a human-like investigation to build profiles in real-time. This technology reduces noise in the investigation output by only presenting unique profiles to the user, and at the same time improves accuracy and reduces false positives by ensuring that the right flags are assigned to the right profiles.”
“At the core of Minerva’s success are our neural networks, which operate seamlessly across billions of data points in 147 languages, empowering compliance teams to proactively manage client risk from onboarding to exit—in real-time. Our commitment to effective and efficient risk assessment is trusted by leading financial institutions like Coinbase, Equifax, Binance, and more, who rely on Minerva to drive their AML programs and stay ahead of illicit financial activities.”
“Minerva’s unique strength is her ability to instantly understand context, sentiment, and risk by harnessing billions of data (structured, unstructured, open source, and proprietary) and then organizing them into distinct profiles. This provides more accurate and instant risk assessment results, setting us apart as a transformative platform in RegTech.”
Future Company Goals
What are some of the company’s future company goals? Arnold concluded:
“Minerva will alleviate the cost burden associated with AML compliance caused by multi-step, manual processes, and disparate, patch-work tech stacks. When cost is no longer the conversation leader, we can turn our efforts to proactively detect and deter financial crime, protecting all communities from human trafficking, drugs, money laundering, and terrorist financing.”
