Ai Personal Financial Assistant

1. Challenge Name: AI-driven financial companion

2. Context

In the digital era, customers expect banks to be not just a place to store money, but a companion that truly understands them. Vietcombank currently possesses the VCB Digibank digital banking ecosystem with a large amount of customer data and a solid technology platform. We are moving towards an “Empathetic Banking” model – where services go beyond payment transactions to focus on financial health care, being present as a capable assistant at every milestone in customers’ lives.

3. Pain Points & Problems to Solve

Despite possessing large amounts of data, customer interactions on VCB Digibank still face limitations:

• Lack of personal context: The system has not fully leveraged behavioral data to identify which life stage customers are in, leading to product suggestions that remain too generic.
• Lack of planning tools: Customers do not have intuitive tools to set up and track long-term financial goals (buying a car, getting married, studying abroad…) directly in the application.
• Passive interaction: Spending alerts or financial advice do not yet function as a proactive “virtual assistant,” failing to provide timely reminders when customers “overspend” or neglect their savings plans.

4. Desired Solution

Vietcombank is seeking AI/Big Data solutions to build a VCB LifeMap module integrated into VCB Digibank, including core capabilities:

• Analysis & Understanding
  • Use AI to analyze transaction history and spending behavior to automatically build LifeMap.
  • Classify cash flows and accurately identify customers’ current life stages.
• Virtual Assistant & Advisory
  • AI Chatbot acting as an advisor: Alert when spending exceeds thresholds, remind about savings progress.
  • Suggest appropriate financial products (savings, investments, insurance, loans) for each life stage.
• Goal Planning
  • Allow customers to set specific financial goals with real-time timelines.

5. Technology & Implementation Requirements

• Technology: AI/Machine Learning applications with the ability to train on large datasets, ensuring high accuracy and continuous updates.
• Integration: The solution must integrate seamlessly (via API/SDK) into the VCB Digibank ecosystem without disrupting the current experience.
• Security & Compliance: Strictly comply with personal data protection regulations (Decree 13) and banking information security; internally processed data must not generate credit risk.
• MVP Roadmap: Ability to build a pilot version (MVP) for internal customers (Vietcombank employees) within 6 months before scaling up.

6. Evaluation Criteria

Solution proposals will be evaluated based on a combination of creativity and quantitative performance indicators:

A. Business Impact:

• Conversion Rate: How much is the solution expected to increase the cross-sell conversion rate of financial products compared to traditional methods?
• Portfolio Share: Ability to increase the average number of products used per customer.

B. Customer Engagement Metrics:

• Interaction Frequency: Does the solution increase the frequency of customers accessing Digibank (beyond transfer transactions) for the purpose of tracking financial plans?
• Retention Rate: Ability to retain users who continuously use LifeMap features after 3-6 months.

C. Technical Metrics:

• Model Accuracy: Accuracy rate in identifying “Life Stage” and classifying spending behavior (Target: >95%).
• Response Speed: Ensure the ability to process and provide suggestions with low latency to avoid affecting user experience.

D. Feasibility:

• Time-to-market: Complete MVP for internal testing within a maximum of 12 months.
• Scalability: System architecture ready for mass deployment to millions of Digibank users after the MVP phase.

We sincerely thank you for your cooperation! This detailed information will serve as a solid foundation for creating breakthrough AI solutions.

1. Startups must submit Solutions in PDF file format

2. The Solution needs to clearly demonstrate the following elements:

• Introduction about the Enterprise
• Proposed Technology suitable for the customer
• Case studies of successful Solution implementations
• Estimated implementation timeline