1. Superior digital customer engagement powered with AI.
- The right CRM solution designed specifically for banking can deliver a holistic customer 360 view that tracks customer transactions, purchase patterns, current cases and more – all in a single window.
- “Quick action” links and streamlined processing can enable relationship managers to handle routine queries and requests with expediency.
- And AI with machine learning applied to customer data can produce guided next-best actions that deliver improved service and engagement.
2. Tighter risk management.
- How banks control risk can be a great differentiator when it comes to success. Accurate risk assessment empowers financial institutions make the right decisions, quickly.
- Tighter risk control mechanisms can also improve asset quality and help banks capture more customers with higher credit quality.
3. Pricing excellence backed by analytics.
- With the unified data and extensive modeling that a quality banking CRM provides, bankers can identify and capitalize on better, more effective pricing opportunities for their financial products.
- Such a solution delivers advanced analytics on customer profile and competition intelligence at a drilled-down, granular level.
- Ensuring effective pricing can prevent revenue and customer leakage.
4. Best-in-class customer segmentation.
- Powerful analytics built into CRMs for banks and credit unions enable them to have customer-centric segmentation with personalized value propositions across products, service and channels.
- Such targeted segmentation can empower bankers to embrace agile practices and eliminate silos.
- They can also quickly reconfigure marketing campaigns without compromising on convenience, value and speed.
5. Higher performance management.
- Highly successful banks have high revenue-to-cost ratios, thanks to a super productive sales workforce. Effective performance management modelers in banking CRM solutions can act as a catalyst to the overall sales process.
- Such modelers help in keeping a track of previous set targets vs achieved numbers for further sales forecasting.