Stay Competitive, Comply with Regulations
AI in Banking & Finance
The financial services industry is adopting AI at an unprecedented pace to supercharge revenue growth, minimize operating expenses and risk, and improve customer experience. According to Accenture, banks could increase revenue 34% by 2022 if they invest more readily in artificial intelligence. Operating in a highly regulated industry, financial institutions often have to trade-off between model performance and explainability. TurinTech helps organisations navigate this optimally; enabling the building of AI at scale with minimum effort, while meeting financial regulations by enabling full transparency and explainability of processes and models.
USE CASES
Top AI use cases in Banking and Finance
Use cases include but are not limited to, improving trading strategies and portfolio management, assess credit worthiness of loan applicants accurately, detect fraud and misconduct, deliver a hyper-personalised customer experience.
Risk and Compliance
- Detect transaction fraud faster, at scale
- Reduce false alerts in anti-money laundering
- Individualise credit scoring to increase revenue and minimise risk
.
Investment and Trading
- Generate trading signals in real time for optimal decisions
- Optimise asset portfolio to increase profitability
- Accelerate algorithmic trading speed and improve accuracy
Customer Experience
- Predict customer churn and recommend effective customer retention initiatives
- Prioritise customer complaints and recommend the right actions
- Anticipate client needs and recommend the right offer
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