DataRobot Case Studies Innovation in Investment Banking Through AutoML

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	Innovation in Investment Banking Through AutoML DataRobot

Innovation in Investment Banking Through AutoML

DataRobot

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Big Data Analytics
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Services	Data Science Services
Challenge	Tommy Tan, CEO of TC Capital, a leading Pan-Asian boutique investment firm specializing in M&A and negotiated capital investments, was dissatisfied with the traditional methods of valuing firms used in investment banking. These methods, which include comparing past mergers and acquisitions, looking at stock market valuations of similar companies, and discounted cash flow models, were manually intensive and carried a high risk of human error. They could also lead to highly subjective valuations. Tommy and his team wanted to build their own valuation methodology, one that utilized cutting edge technology and took advantage of the amount of data available to bankers today. Read More
About Customer	TC Capital is a leading Pan-Asian boutique investment firm specializing in M&A and negotiated capital investments. The firm is led by CEO Tommy Tan, a veteran of over 30 years in investment banking across Asia. TC Capital is committed to utilizing cutting edge technology and data to improve their valuation methodology. They have access to a large dataset that includes information from 43,000 companies, with 560 variables on each individual company. The firm is also developing an app, CeeSuite, to help C-suite executives value public and private companies. Read More
Solution	Tommy and his team turned to automated machine learning and enterprise AI from DataRobot. They had access to a large dataset that includes information from 43,000 companies, with 560 variables on each individual company. This dataset took TC capital nine months to assemble. With DataRobot, they were able to automatically process this large dataset and generate dozens of high quality, reliable models that provided highly accurate valuations. In backtesting, the models beat the market by nearly 3x. The predictions from DataRobot were so consistent and accurate that Tommy soon relied on those valuations when voting on the valuation committee. TC Capital is also launching an app, CeeSuite, that leverages machine learning and data science to help C-suite executives value public and private companies. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Big Data Analytics

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Services

Data Science Services

Challenge

Tommy Tan, CEO of TC Capital, a leading Pan-Asian boutique investment firm specializing in M&A and negotiated capital investments, was dissatisfied with the traditional methods of valuing firms used in investment banking. These methods, which include comparing past mergers and acquisitions, looking at stock market valuations of similar companies, and discounted cash flow models, were manually intensive and carried a high risk of human error. They could also lead to highly subjective valuations. Tommy and his team wanted to build their own valuation methodology, one that utilized cutting edge technology and took advantage of the amount of data available to bankers today.

About Customer

TC Capital is a leading Pan-Asian boutique investment firm specializing in M&A and negotiated capital investments. The firm is led by CEO Tommy Tan, a veteran of over 30 years in investment banking across Asia. TC Capital is committed to utilizing cutting edge technology and data to improve their valuation methodology. They have access to a large dataset that includes information from 43,000 companies, with 560 variables on each individual company. The firm is also developing an app, CeeSuite, to help C-suite executives value public and private companies.

Solution

Tommy and his team turned to automated machine learning and enterprise AI from DataRobot. They had access to a large dataset that includes information from 43,000 companies, with 560 variables on each individual company. This dataset took TC capital nine months to assemble. With DataRobot, they were able to automatically process this large dataset and generate dozens of high quality, reliable models that provided highly accurate valuations. In backtesting, the models beat the market by nearly 3x. The predictions from DataRobot were so consistent and accurate that Tommy soon relied on those valuations when voting on the valuation committee. TC Capital is also launching an app, CeeSuite, that leverages machine learning and data science to help C-suite executives value public and private companies.

Impact #1	Automated processing of a large dataset that includes information from 43,000 companies, with 560 variables on each individual company.
Impact #2	Generation of dozens of high quality, reliable models that provide highly accurate valuations.
Impact #3	Backtesting of models showed they beat the market by nearly 3x.

Impact #1

Automated processing of a large dataset that includes information from 43,000 companies, with 560 variables on each individual company.

Impact #2

Generation of dozens of high quality, reliable models that provide highly accurate valuations.

Impact #3

Backtesting of models showed they beat the market by nearly 3x.

Benefit #1	The data science work that DataRobot automated for TC Capital would have cost the company $10 million and three years to do without DataRobot’s help.
Benefit #2	In backtesting, the models beat the market by nearly 3x.

Benefit #1

The data science work that DataRobot automated for TC Capital would have cost the company $10 million and three years to do without DataRobot’s help.

Benefit #2

In backtesting, the models beat the market by nearly 3x.

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Overview

Innovation in Investment Banking Through AutoML

Operational Impact

Quantitative Benefit