Traditional core banking platforms often trap institutions in rigid processes and outdated infrastructure. These systems are expensive to maintain, struggle to scale, and are unable to keep up with changing regulatory standards.

We build custom, API-first banking platforms that unify account management, loans, deposits, withdrawals, currency exchange, and remittance into a centralized system. We architect these platforms using Kubernetes microservices for independent scaling, PostgreSQL and Oracle for ACID-compliant ledgers, and Kafka for event-driven reconciliation.

Our designs also integrate real-time reporting modules and role-based access controls, ensuring transparency for auditors and compliance teams. The result is a system that performs daily banking operations effortlessly and adapts quickly to new products and evolving regulations.

Example: Banks, depending on monolithic reconciliation modules, often wait days for settlement. By replacing batch jobs with Kafka-powered event processing and PostgreSQL-backed ledger management, they can reduce settlements from 48 hours to near real-time. This, in turn, can improve liquidity planning and customer confidence.

Customers increasingly demand around-the-clock digital access, yet many existing online platforms are static, insecure, and hard to personalize.

Codewave designs custom internet and mobile banking applications that prioritize security, speed, and usability. We build personalized dashboards and PFM (Personal Financial Management) tools using AI/ML recommendation models, and integrate biometric authentication APIs for secure access. Our experts also enable WebRTC-based conversational banking for real-time engagement.

By adopting cloud-native architectures, we ensure that performance remains consistent even under heavy loads. At the same time, modular APIs make it easy to extend services to IoT devices, such as wearables and voice assistants. These systems give customers confidence to manage their money anywhere, anytime, while helping banks build loyalty through richer digital experiences.

Example: A regional digital bank experienced a dip in customer engagement as users found its app repetitive and inconvenient. After implementing biometric logins, AI-driven savings insights, and real-time chat through WebRTC, they will be able to increase daily active usage manifold, while also significantly improving the adoption of savings products.

Financial institutions often treat CRMs as generic data repositories, which limits their impact on growth. Off-the-shelf solutions don’t capture the complexity of banking interactions, from onboarding to loan servicing.

We customize Salesforce and Dynamics 365 to align with financial workflows, integrating them directly with core banking systems, mobile apps, and call center platforms. Furthermore, we enhance CRMs with AI-powered lead scoring and nurturing, journey mapping, customer profiling, and document automation, ensuring that sales and service teams work on real-time, unified data.

Dashboards built with Power BI and Tableau give executives visibility into customer lifetime value, churn indicators, and campaign performance. Instead of fragmented records, you get a single, intelligent system that turns customer data into an actionable strategy.

Example: A retail bank was losing high-value loan leads because manual follow-ups took several days. After connecting Salesforce with their loan origination system and applying AI-driven prioritization, they will be able to reduce response times from three days to less than thirty minutes. Moreover, they’ll see a rise in loan conversions.

Banks collect massive volumes of customer, transaction, and channel data, but outdated reporting often leaves leaders with static or delayed insights.

Our experts develop analytics pipelines that transform raw data into real-time intelligence for more thoughtful decision-making. We utilize Spark-based ETL workflows to process high volumes, TensorFlow models to predict credit, market, and liquidity risks, and Power BI or Looker dashboards to give executives live visibility. Every system is built with encryption, lineage tracking, and role-based access to meet strict compliance standards.

Our solutions include customer analytics (segmentation, churn, and cross-sell effectiveness), channel analytics (branch traffic, clickstream behavior, and mobile feature adoption), marketing analytics (campaign ROI and product uptake), and performance analytics (sales efficiency and branch profitability). With this unified view, banks can reduce risk, optimize operations, and identify new growth opportunities.

Example: A lender facing rising defaults was unable to identify high-risk borrowers until it was too late. With a TensorFlow-driven credit-risk model trained on historical borrower behavior and integrated into Spark pipelines, the lender will be able to flag at-risk customers months in advance. This will help reduce default rates.