Powering Operational Excellence

A leading commercial insurance carrier was increasingly reliant on a shrinking pool of seasoned adjustors to create detailed claims reports—an effort that required synthesizing data from police and fire reports, damage assessments, policy documents, photos, repair estimates, and even contextual factors like weather and property history.

Tredence partnered with the client to build a GenAI-powered claims report generator that elevated both quality and speed. The solution auto-generated executive summaries, structured tables, and descriptive narratives. It intelligently inserted evidence into relevant sections and replicated industry-best report formats—ensuring every claim read like it was crafted by a top adjustor.

This AI-driven application didn’t just automate tasks—it infused consistency, intelligence, and scale into claims documentation. It enabled junior and mid-level adjustors to deliver reports with significantly less effort and greater accuracy. Work like this is why insurers increasingly file claims automation under financial services AI rather than treat it as a standalone reporting tool.

A regional bank with a complex sales structure—spanning digital originations, third-party partners, contact centers, and field sales—struggled to measure sales ROI or allocate investments effectively across channels. The absence of a unified client database made attribution and decision-making difficult.

Tredence stepped in to create a robust Client 360 solution, beginning with the integration of multiple internal identifiers (Digital ID, SFDC ID, Email ID) into a unified internal ID base. This was further matched with third-party commercial databases to enhance the bank’s prospect visibility.

The solution introduced a single B2B Client Master table to map entities across internal systems, an omni-channel sales journey mapper to identify high-performing and high-drop-off channels, and a dynamic Sales Investment ROI network tree to guide strategic investments—be it in marketing campaigns, field sales efforts, or digital expansion.

This unified data model became a foundational asset, driving greater ROI and enabling advanced analytics across functions. It's the type of foundational rebuild banking analytics consulting companies get called in for once attribution problems start costing real budget.

A regional bank set out to transform its customer engagement strategy—shifting from fragmented interactions to an always-on, personalized experience. The goal was to deepen customer relationships, deliver timely offers, and improve retention. But to get there, the bank needed a robust and scalable data and insights foundation.

Tredence partnered with the bank to build a unified data platform, fully integrated with core banking systems and third-party sources. Leveraging a prefab Customer 360 analytical model, the solution curated a trusted, governed dataset. The team embedded data quality checks into pipelines, enabled retrospective insights, and deployed AI/ML models with a decisioning engine for real-time personalization.

Critically, the platform integrated with the customer journey orchestration layer—activating insights across digital and physical touchpoints. It also replaced a rigid, vendor-driven Blackbox tool with a flexible, business-managed insights platform.

The result was a data and AI backbone that made customer engagement smarter, faster, and more dynamic. Replacing a rigid, vendor-locked tool with a business-managed solution is exactly the kind of transformation that leading banking analytics services firms like Tredence are increasingly being asked to lead, not just support.

A large regional bank set out to modernize its anti-money laundering (AML) investigations—traditionally a manual, time-intensive process. Tredence partnered with the bank to create a GenAI-powered investigator copilot, built with agentic principles to support analysts across the entire case lifecycle.

The copilot dynamically created customer profiles using historical transaction data and extracted relevant details from KYC documents, RFIs, and STRs. It processed inputs from the bank’s enterprise data warehouse and document management systems to deliver context-rich case summaries.

For counterparty analysis, the copilot automated adverse media searches across platforms like LexisNexis, Orbis, and S&P, and generated real-time risk scores with transparent factors. Investigators could also run ad-hoc analyses using natural language—classifying outcomes as STR, false positive, or requiring internal review.

The solution even auto-generated regulator-facing STR documents, complete with editable drafts for investigator input.

The GenAI copilot didn’t just speed up investigations, it elevated quality, reduced false positives, and let analysts focus on judgment, not paperwork. This is the kind of end-to-end case lifecycle coverage that banking AI consulting services are increasingly measured on, not just alert volume.