AI powered valuation
models made easy
Drag and drop your financials, and we will give you your model — CAPM, WACC, DCF and more — in seconds.
Failure rate per Meckl & Röhrle (2016), Do M&A deals create or destroy value? A meta-analysis, European Journal of Business and Economics: across 55,399 transactions from 33 studies (1950–2010), only 47.6% of deal announcements earned a positive capital-market reaction — 52.4% destroyed value (p < 0.001).
The problem
Traditional models
ignore the human variables.
CEO personality is uncounted
CAPM assumes rational, risk-averse investors and identical information. It cannot see the leader driving the firm.
Supply Chain Risk Management
Disruptions in supply chain are not priced into valuation models.
Firm culture is invisible
Culture, innovation profile and risk tolerance shape systemic risk — but never enter the discount rate.
Valuation ignores qualitative signal
Earnings-call transcripts, decision patterns, and behavioral cues stay outside the model.
The solution
A transformative valuation model, rebuilt with AI.
Scaredy-Cat layers AI-quantified risk factors onto CAPM — feeding into WACC, DCF, and terminal value — so your share prices reflect the full picture.
Increase systematic risk accuracy
Add validated qualitative factors to the discount rate.
Better investment decisions
See how CEO characteristics shift target share price.
Increase deal performance
Enter transactions with a defensible range, not a point.
Reduce loss in M&A
De-risk the 52.4% of deals that historically destroy value.
The platform
A web-based valuation cockpit.
Scenario analysis, model selection, and CEO-characteristic impact — in one integrated dashboard. Available on web, mobile, and via API.
Valuation Model Selection
CAPM, WACC, DCF and beyond — configurable per deal.
Scenario Analysis
Stress-test share price across risk factors in real time.
CEO Characteristics Impact
See exactly how personality shifts your terminal value.
SaaS model
Free · Paid · Premium · Corporate — with mobile apps & API integration.
Competitive advantage
Affordable insight, where the incumbents are expensive noise.
Research foundation
Findings and algorithms rooted in established academic research.
More than data
Beyond gathering: unique insights that feed pricing models directly.
Data sources
Public and proprietary data combined into robust, defensible models.
Talent
Co-founders bring financial and scientific experience and a deep network.
Pushing boundaries
New research and technology ship into the product quickly.
About us
The people pricing what others miss.
Scaredy-Cat Insights is a technology startup that leverages artificial intelligence to help business leaders make better decisions — focusing on mergers & acquisitions by quantifying qualitative data, such as CEO personality, into asset pricing models.
Nikisha D. Alcindor
CEO & Co-Founder
Nikisha Alcindor is an AI-focused strategic management leader with expertise in artificial intelligence operational management, machine learning, and curriculum creation for organizations undergoing digital transformation. Her work bridges business strategy, emerging technologies, and workforce development — helping companies leverage AI to solve complex problems, drive innovation, and cultivate future-ready talent.
In 2025, Dr. Alcindor was named one of Unstoppable WOW3's Most Inspirational Women of Web3 & AI. She holds a Ph.D. in Business (Strategic Management) from the Graduate Center of The City University of New York (CUNY), Baruch College – Zicklin School of Business, where she was a CUNY Graduate Center Fellow and Provost Enhancement Fellow. Dr. Alcindor is a member of Beta Gamma Sigma, the International Business Honor Society, and is an Assistant Professor at the Saunders College of Business, Rochester Institute of Technology.
Nikisha's professional background spans investing, fundraising, organizational change, and public-sector development. She previously served as a Board Member for the Upper Manhattan Empowerment Zone, contributing strategic guidance to economic and community initiatives. She holds a BA in Chemistry from Emory University and a Finance-focused MBA from Columbia Business School, where she was a Leon Cooperman Scholar.
Joseph Harrison
COO & Co-Founder
Joseph is a data scientist with 10 years of experience in statistical modeling, natural language processing, and machine learning. He holds a Ph.D. in strategic management from Texas A&M University and a B.S. in finance and entrepreneurship from the University of Richmond.
Prior to receiving his Ph.D., Joseph worked for three years as a consultant and technology lead with PwC in Washington, DC, and as the assistant to the CFO for PartnerMD, a concierge medical practice in Richmond, Virginia. Joseph currently teaches and does research at the University of Tennessee, where he has co-developed multiple machine learning applications that extract meaning from unstructured data and provide insights related to corporate strategy and performance.