DataRobot Case Studies Nigerian Bank Reduces Risk, Cost with ML Driving Decisions

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	Nigerian Bank Reduces Risk, Cost with ML Driving Decisions DataRobot

Nigerian Bank Reduces Risk, Cost with ML Driving Decisions

DataRobot

Technology Category	Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Use Cases	Fraud Detection
Services	Data Science Services
Challenge	Carbon Digital Bank, a financial institution serving the underserved African market, needed a way to quickly determine credit risk for individuals without prior credit. The bank also wanted to empower its data science team to take on additional business challenges. The bank had committed to a data-first strategy and looked to AI as an integral part of its decision-making. However, assessing customers' credit worthiness was a major challenge. The bank needed to expedite decisions on hundreds of thousands of loan applications every month. Read More
About Customer	Carbon Digital Bank provides access to financial services for all Africans. The bank empowers individuals with access to credit, simple payment solutions, high-yield investment opportunities, and easy-to-use tools for personal financial management. Carbon Digital Bank is headquartered in Lagos, Nigeria, with operations extending to Ghana and Kenya. The bank was launched in 2012 by financial industry veterans Ngozi Dozie and Chijioke Dozie to serve the underserved Nigerian market, where 40 percent of Nigerians lacked bank accounts and only about five percent held credit cards. In 2020, the bank processed $240 million in payments. Read More
Solution	Carbon Digital Bank chose DataRobot’s AI Cloud platform to amplify the efforts of its global data science team. The platform automates much of the process and is continuously evolving with new capabilities. When a consumer submits an application on the Carbon Digital Bank mobile app, models leverage a diverse set of data from first-, second-, and third-party sources to build a credit score within five minutes. Those with better scores gain access to better rates and higher limits. The bank has developed multiple models to help expedite decisions on loan applications. The Carbon Digital Bank algorithms also take into account fraud and anti-money laundering practices, which are prevalent in the Nigerian market, serving numerous guardrails. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Services

Data Science Services

Challenge

Carbon Digital Bank, a financial institution serving the underserved African market, needed a way to quickly determine credit risk for individuals without prior credit. The bank also wanted to empower its data science team to take on additional business challenges. The bank had committed to a data-first strategy and looked to AI as an integral part of its decision-making. However, assessing customers' credit worthiness was a major challenge. The bank needed to expedite decisions on hundreds of thousands of loan applications every month.

About Customer

Carbon Digital Bank provides access to financial services for all Africans. The bank empowers individuals with access to credit, simple payment solutions, high-yield investment opportunities, and easy-to-use tools for personal financial management. Carbon Digital Bank is headquartered in Lagos, Nigeria, with operations extending to Ghana and Kenya. The bank was launched in 2012 by financial industry veterans Ngozi Dozie and Chijioke Dozie to serve the underserved Nigerian market, where 40 percent of Nigerians lacked bank accounts and only about five percent held credit cards. In 2020, the bank processed $240 million in payments.

Solution

Carbon Digital Bank chose DataRobot’s AI Cloud platform to amplify the efforts of its global data science team. The platform automates much of the process and is continuously evolving with new capabilities. When a consumer submits an application on the Carbon Digital Bank mobile app, models leverage a diverse set of data from first-, second-, and third-party sources to build a credit score within five minutes. Those with better scores gain access to better rates and higher limits. The bank has developed multiple models to help expedite decisions on loan applications. The Carbon Digital Bank algorithms also take into account fraud and anti-money laundering practices, which are prevalent in the Nigerian market, serving numerous guardrails.

Impact #1	Carbon Digital Bank reduces risk while the data science team performs at about 25% leaner.
Impact #2	The bank has developed multiple models to help expedite decisions on hundreds of thousands of loan applications every month.
Impact #3	The Carbon Digital Bank algorithms also take into account fraud and anti-money laundering practices, which are prevalent in the Nigerian market, serving numerous guardrails.

Impact #1

Carbon Digital Bank reduces risk while the data science team performs at about 25% leaner.

Impact #2

The bank has developed multiple models to help expedite decisions on hundreds of thousands of loan applications every month.

Impact #3

The Carbon Digital Bank algorithms also take into account fraud and anti-money laundering practices, which are prevalent in the Nigerian market, serving numerous guardrails.

Benefit #1	The bank processed $240 million in payments in 2020.
Benefit #2	The data science team performs at about 25% leaner.
Benefit #3	The bank is able to make decisions on hundreds of thousands of loan applications every month.

Benefit #1

The bank processed $240 million in payments in 2020.

Benefit #2

The data science team performs at about 25% leaner.

Benefit #3

The bank is able to make decisions on hundreds of thousands of loan applications every month.

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Overview

Nigerian Bank Reduces Risk, Cost with ML Driving Decisions

Operational Impact

Quantitative Benefit