Banking and Finance
Power Smart Banking with Customer Intelligence
Customers today in the digital world leave a lot of interesting footprints on the internet. To track and understand what their needs are banks need to operate a robust and intelligent platform that can help identify customers want in advance. With AI & ML techniques, segment your customers as per their profile to offer customized services. This can help you achieve lower customer retention rate thereby providing superior customer experiences. Banks also need a next best recommendation engine to help customers bank smarter. Aspire Systems helps banks worldwide build a digitally connected, customer intelligence platform.
Customer Intelligence with AI and ML Techniques
Customer intelligence (CI) is the process of gathering and analyzing information regarding customers, and their details and activities, to build deeper and more effective customer relationships and improve decision-making. CI helps businesses create an ideal customer profile, predict their wants and dislikes and engage customers at an emotional level. It also gives a better insight into the customer persona thus enabling improved targeted marketing and better analysis of customer complaints.
Where can AI help in Customer Intelligence for Banks?
- Dynamic profile management - Build customer profiles based on different attributes like age, work profile, family profile and more. The profile will be dynamic as it keeps learning and tweaking the profile.
- Smart Content Generation - Display relevant content once the profile is built. Content will be dynamic and can be a blog/video/banners based on prospect behavior.
- Customized Product Offering - Build custom products based on profiles.
- Propensity Modelling - Direct consumers to the right message and product as well as generate outbound personalized content.
- Ad- Targeting - Effective content placement at the right stage in the buying cycle with relevant product offering.
- Predictive Analytics - Predict the product the prospect might choose and the right price that needs to be offered for a better conversion possibility.
- Dynamic Pricing - Personalize pricing for prospects using various business models so that they become a customer.
- Re-Targeting - Bring them back to your site by building models which predicts relevant content for effective conversions.
- Personalized Journeys - Personalize web/mobile pages and the use of chat bots. AI models can predict and build ultra-personalized content on the website for each visitor at different stages of the prospect cycle.
Engage Loyal & lapsed Customers
- Customer Service - Predictive analytics driven by AI can determine which customers are most likely to either become dormant or leave altogether. With this insight, attractive offers or content can be used to prevent them from churning.
- Build predictive customer profile - Every customer journey can be used to enhance the customer profile and which will inturn can build a powerful profile of future customers.
- Dynamic Communication - This will help in communicating to the customer through the right medium, right digital channels to get maximum efficiency and best possible result in increasing revenue.
Aspire Systems believes at providing end-to-end business solutions when it comes to CI implementation for banks.
Business Opportunity Assessment (2 to 4 Weeks)
In the first 2 to 4 weeks we promise our customers to analyze the need, context, and scope. Once we identify the business metrics, and have devised a preliminary solution approach, we go ahead and identify suitable data resources and finally we recommend a project plan.
Pilot Solution Development (6 to 8 weeks)
We have the expertise to complete our Pilot Solution Development in the next 6 to 8 weeks. During this phase, we identify sample data for the purpose of data testing, and develop a predictive model. Based on the predictive model we prepare a detailed report on the findings along with recommendations for enterprise-wide solution.
Business Value Realization (3 to 6 months)
The Business Value Realization phase is the most crucial because this is the time when the developed solution goes live in sync with the existing infrastructure of the banks after confirmation from stake holders. During this phase, key performance metrics are tracked and the business benefits are evangelized. Aspire also takes in the responsibility of maintaining the solution depending on the changing business requirement.
Artificial Intelligence & Machine Learning Use cases for Banks
Predict Customer Segmentation with RFM & Customer Lifetime Value
Data Source: Customer Transactions
Challenge: Quality of Data and Identifying Machine Learning models
- Deliver Enhanced and Intuitive customer experience
- Derive Insights with 360 degree customer information
- Improve Customer Conversations
- Recommended Changes in Customer touch points
Forecast Customer Sentiments
Data source - Customer complaints or queries and other sources
Challenge - Collate data, retrieve insights and act on it
- Amplified customer service
- Predict a Good Loan or a Bad Loan
- Better understanding of customer personas
- Support excellent decision making