AI for the Accounting Guy: MindBridge Artificial Intelligence-Auditor

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Amalgam Insights’ Net-Net Summary of Mindbridge Ai

Based on a briefing with MindBridge Ai on June 19, 2017 and MindBridge Ai’s $4.3 million funding round on the same date, this summary provides guidance to auditors and accountants seeking guidance on applying artificial intelligence to risk, compliance, and audit efforts. Amalgam Insights believes that this emerging approach is an important governance step for financial transactions as digital transactions become increasingly diverse and auditors are responding by either building self-built tools or working with internal data science teams.

Why Mindbridge Ai Matters for Financial Audiences

Artificial Intelligence (AI) is the technology buzzword for 2017. Everybody in the enterprise applications world claims to be working on AI but nobody seems to understand how to bridge the gap between interesting AI technologies and algorithms and the practical nature of work. In response, business has created the role of the “data scientist”: statistical programming wizards who understand all aspects of business, statistics, data, and coding to bridge the gap between technology and business. Yanir Seroussi describes this impossible combination well:

The Perfect Data Scientist
The Perfect Data Scientist via

However, this search for the unicorn data scientist is not sustainable. The global size of data is estimated to double every 18 months and the potential for digital multimedia and the Internet of Things could make that data accelerate even faster. And in that data, it becomes easier for “needle in a haystack” fraud attempts or transactional errors to slip through an incomplete compliance net.

This is the world that accountants are now facing in monitoring an increasingly diverse set of transactions, customers, and financial environments. Amalgam Insights believes that the challenge of Technology Consumption from a financial perspective is escalating in a business world where: digital transactions accelerate; the variety of payments increase with based on per-unit, per-interval, and per-outcome measures that strain traditional double-entry book accounting efforts; and financial data starts to expand beyond the formats used for accounting, business workflow, and other enterprise applications traditionally used to support audit and compliance.

In this context, Amalgam Insights was interested in speaking with MindBridge Ai to better understand the direction of MindBridge’s Artificial Intelligence Auditor and the current go-to-market targeting of the organization.

What is MindBridge Ai?

MindBridge Ai was founded by Solon Angel in 2015 to solve fundamental challenges in fraud and compliance based on his experience in this industry. With the assumption that fraud analytics tools were not keeping pace both with the evolution of fraud and compliance change and the subsequent needs that auditors face, MindBridge Ai focuses on building a self-learning platform that would learn to detect anomalies, optimize fraud algorithms, and provide visualizations and accounting integrations. Over the past two years, MindBridge has grown from a three-person team to over 30 employees.

On June 19th, 2017, MindBridge Ai raised a $4.3 million seed round from 8VC, MaRS Investments, Real Ventures, and individual investors from Capital Angel Network and Fresh Founders. This seed round is intended to allow MindBridge Ai to employ another 10 employees while managing growth at a responsible rate and is part of an internal roadmap to target an IPO in the next five years.

Briefing Notes for Mindbridge Ai
In this briefing, Amalgam Insights was joined by
Dipalli Bhatt – Marketing Lead
Robin Grosset – CTO
John Colthart – VP of Growth

In this briefing, MindBridge Ai focused on the key challenges that it sought to solve as an artificial intelligence solution. Rather than go to market as a generalized platform, MindBridge Ai focuses on the challenges of the auditor to see where revenue, audit, and other financial challenges will potentially affect corporate governance, key stakeholders,and equity shareholders.

MindBridge Ai currently sees itself as a company that solves a general problem, but with a new approach that leads to MindBridge Ai having companies adjacent to it rather than true competitors. Large enterprise vendors currently handling audit management do so through a case management based approach that focuses on process and paperwork while largely leaving anomaly detection and analytics alone. This vacuum allows MindBridge to focus on the data-driven aspects of audit management, credit risk, and fraud and to provide tools that can start competing against the black-hat fraudsters and hackers who are expert in gaming the traditional audits and processes that protect financial systems.

At this time, MindBridge Ai goes to market in selling into audit firms and enterprise organizations with significant financial audit needs. In addition, MindBridge Ai has recently signed an agreement with Thomson Reuters’ Tax and Accounting Audit Suite. Amalgam Insights believes that, over time, MindBridge Ai will continue to productize its machine learning and analytics capabilities to go downmarket from a company size perspective as it continues to support risk, Know Your Customer, and internal audits. Because MindBridge Ai solves accounting audit problems that are seen even in small businesses, Amalgam expects that there is latent demand for MindBridge Ai’s capabilities.

Recommendations for Accounting and Audit Teams Evaluating Artificial Intelligence:

Whether through direct solutions such as MindBridge Ai-Auditor or with other service-based or model-optimization-based artificial intelligence solutions focused on auditor needs, Amalgam Insights recommends that auditors bring in a fit-for-purpose artificial intelligence service or solution that will effectively detect compliant or fraudulent transactions.

Otherwise, auditors are stuck in a two-front war both against the constantly changing world of government-defined compliance and the black-hat world of hackers seeking easy money. New generations of auditors are starting to conceptually understand how artificial intelligence-based logic and approaches used to support compliant and clean financial environments and cutting edge auditors are learning relevant data science techniques to build their own AI-based audit tools. But as auditors learn about this new world of machine learning and AI-augmented audits, Amalgam Insights advises that these professionals also evaluate options in today’s market for directly supporting audit standards and automating high volume, low value work.

Note: Mindbridge Ai is one of a few innovative solutions that Amalgam Insights has recently identified to identify audits. In addition, Amalgam also recommends looking at FloQast for financial close and internal audit management and at DataRobot as a data science tool to optimize risk model development and deployment.

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