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About this guide

Capturing some example use cases where the Demyst Platform was used to solve for a specific use case in the banking industry.

Customer onboarding streamlined with Fraud Automation

Context

A global bank wanted to help automate manual verification processes, which could take upwards of two weeks per customer, resulting in high costs and customer drop-offs. The bank wanted to automate the checks the assessment team was doing today as part of a bank-wide push to real-time customer onboarding.

Methodology

Demyst mapped the current state processes and then worked with the risk team to design and implement automated checks;

• Email: Email status, fraud history, and reverse match to person
• Employment: Verify using work email address
• Phone: Valid, registered and reverse match to person

Outcomes

• Time to launch product: 3 months
• Straight through processing: 80%
• Time to roll out to new regions: 4 weeks

Identifying affluent customers at a retail bank

Context

A Retail banking client needed to better estimate the affluence and life stage of its existing retail banking customers to enable better conversions and ROI for its cross-selling efforts.

Methodology

• Collected initial data sets of potential leads
• Appended third-party data from over 80 different data sources to build deeper customer profiles
• Made available via API for batch or real-time calls

Outcomes

• Model accuracy: >80%
• Data sources leveraged: 80

Powering automation of KYB at a commercial bank

Context

A large commercial bank suffering from time-intensive manual reviews of potential customers which included KYB requirements, basic credit worthiness checks, and owner verification.

Methodology

• Compared client’s current process to best in class KYB solutions including verification of physical location, phone, ownership, licensing, revenue, size, and more
• Automated access to data sources used by client while adding incremental new sources for a complete KYB solution
• Designed automated workflow to automate verification process of KYB requirements as well as common underwriting criteria
• Implemented automated solution seamlessly without impacting other processes

Outcomes

• Application automation ratio achieved: 50%
• Conversion rate increase: 4%

Faster and more effective credit scoring for online lender

Context

An online lender was looking to expand its nascent SME lending and cash advance products and depended on just a single external bureau and off-the-shelf score to price risk. However approval rates were low and first payment default rates high. The firm was also heavily relying on cross-sell to existing customers for which ample internal data existed. It faced growth hurdles in its inability to:

• effectively score existing customers
• evaluate risk of new-to-institution applicants

Methodology

• Optimized the next 100 vendors (bureau and more), configured and validated against at ~250K loans
• Leverage top attributes: e.g. Employer verification; Employer attributes; Negative employer sentiment; Alternative financial services activity; Multi source credit utilization and scores; Rent history; Utility payments; Telco carrier, billing and top-ups
• Incorporated incremental attributes at real-time on the DemystData platform

Outcomes

• ROI (revenue increase and costs reduction): 14x
• Business bureaus integrated: 3
• Non traditional sources: 12
• Customer records enriched: 40k