Banking – AI Transcend

A Top Bank

Credit Card Fraud Detection

The financial industry, especially credit card services, faces tough competition and rising fraud risks. Challenges include evolving fraud methods, regulatory pressure to cut losses and balancing security with user experience.

Core pain points: Legacy rule-based systems detect only 60% of transactions with 0.1% accuracy, missing sophisticated fraud and generate high false positives, straining resources with manual reviews.

Core Problems Solved

The machine learning model we built for the client addresses fraud detection inefficiencies by leveraging advanced algorithms to analyze transaction patterns. It replaces static rules with dynamic, data-driven predictions to identify fraudulent activities at scale.

Key Features of the Solution

Achievements and Benefits

$2.5 Million

The model prevented $2.5 million in additional fraud losses beyond traditional rules with monthly gains of $1.8 million (27% of total fraud amount) at 90%.

5.94x

The model’s accuracy at 25% coverage (75.24%) was 1.85x higher than Visa’s traditional model and at 90% coverage (6.42%), it was 5.94x more accurate.

Reduced manual review Strengthened fraud resilience

Operational Efficiency:
Reduced manual review workload by minimizing false positives, allowing fraud teams to focus on high-risk cases.
Enhanced Security:
Strengthened fraud resilience against emerging threats, improving customer trust in card services.

Ready to Transcend?

Empower your enterprise to think faster, operate smarter and grow stronger.

A Top Bank

Anti-Money Laundering

The financial industry faces strict regulatory pressures and rising money laundering risks, with competitors boosting compliance efficiency. Challenges include exploding transaction data, evolving laundering methods and balancing monitoring with efficiency.

Core pain points: Traditional rule-based systems cause inefficient manual reviews (over 60% false alerts) and incomplete risk prioritization, delaying detection of sophisticated schemes and risking penalties.

Core Problems Solved

The solution we built for the client employs machine learning to analyze rule-based alarm data, assigning suspiciousness scores to transactions. This enables the bank to prioritize reviews based on risk levels, addressing the inefficiencies of manual sorting and improving the accuracy of suspicious transaction reporting.

Key Features of the Solution

Achievements and Benefits

99.6%

The top 30% of scored cases achieved a 90% recall rate, while the top 70% achieved 99.6% recall, allowing a 50% reduction in manual review workload.

97.9%

Precision in the top 30% of cases reached 97.9%, significantly higher than baseline rule-based systems.

Regulatory Compliance Operational Optimization

Regulatory Compliance: Enhanced ability to identify high-risk transactions reduces the risk of regulatory penalties and reputational damage. Operational Optimization: Frees compliance teams to focus on complex cases, improving overall anti-money laundering effectiveness and responsiveness.

A Top Bank

Transaction Installment and Precision Marketing

The financial services industry, especially credit card operations, faces fierce competition to maximize service fees and optimize marketing costs. Challenges include low response rates to mass campaigns, intense customer engagement competition and service differentiation in a saturated market.

Core pain points: Inefficient mass marketing (e.g., 0.63% response from random targeting) wastes resources, and manual/rule-based screening misses low-value transaction opportunities, leaving revenue untapped.

Core Problems Solved

The solution we built for the client uses machine learning to predict which credit card transactions are most likely to convert to installment plans, enabling targeted SMS marketing. This addresses the inefficiency of mass campaigns and enhances precision in customer engagement.

Key Features of the Solution

Achievements and Benefits

1.6x

Response Rate Improvement: The model achieved a 1.23% response rate, generating $1 in service fee income per SMS sent, 1.6x higher than expert rules ($0.6) and 5.6x higher than random ($0.2).

$0.4 Million

Cost Efficiency: By targeting only 21% of eligible transactions, the model covered 91% of installment fees, reducing marketing costs while increasing revenue by $0.4 million monthly.

Enhanced Customer Relevance

Enhanced Customer Relevance: Targeted campaigns improved customer experience by reducing irrelevant SMS, increasing trust in the brand’s communication.
Strategic Focus on Micro Transactions: Unlocked new revenue streams from low-value transactions, previously considered unprofitable to target, diversifying the business’s income base.

Ready to Transcend?

Empower your enterprise to think faster, operate smarter and grow stronger.

A Top Bank

Intelligent Customer Service

The financial services industry faces intense competition, driven by the need to boost customer engagement, cut costs and differentiate services. Digital transformation and customers’ demand for instant, personalized support challenge traditional customer service models.

Core pain points: Inefficient manual support for high-volume, repetitive inquiries causes long response times (>5 mins) and low satisfaction (60%). Fragmented knowledge management leads to inconsistent answers, with 30% of inquiries needing escalation.

Core Problems Solved

The solution leverages LLM and knowledge graph technologies to automate repetitive inquiries and centralize product knowledge. This addresses the inefficiencies of manual support and ensures consistent, accurate responses at scale.

Key Features of the Solution

Achievements and Benefits

$2 Million

Cost Reduction: Cut call center labor costs by $2 million annually with AI handling 60% of incoming inquiries (up from 15% previously).

82%

Efficiency Gains: Reduced average response time to 45 seconds with first-contact resolution rate increasing from 55% to 82%.

$1.5 Million

Revenue Uplift: Generated $1.5 million in incremental sales through proactive product recommendations via chatbots.