An agent-based, context-aware large language model platform purpose-built for collections, recovery, receivables, and operational analytics teams, powered by Kollect*AI GPT.
Across collections, recovery, and receivables, the gap between asking a question and acting on the answer has been the slowest part of the day. Kollect*AI GPT closes it. Ask in plain English, get structured insights, predictive scores, and treatment recommendations grounded in your own operational data.
From siloed data warehouses to the long queue between business question and answer, the operational reality of analytics has changed. The systems supporting it, in many institutions, have not.
Every business question becomes a ticket. SQL requests pile up with the data team. By the time the report lands, the moment to act has passed.
Dashboards show what happened last week. They rarely flag what is about to happen. Without predictive layers, recovery teams chase yesterday's problems.
"Broken PTP" means three different things in three different reports. Manual reconciliation eats hours that should go to action.
Black-box models give answers without sources. Compliance, audit, and risk teams cannot stand behind a number they cannot explain.
Voice bots, dialers, and collections systems each generate their own logs. Without a unified analytics layer, learning loops stay broken.
BNM expects responsible AI adoption with structured access control, monitoring, and human oversight. Most pilot tools were not built for that bar.
Bank Negara Malaysia's AI Survey 2024 found that 71% of Malaysian banks and development financial institutions had at least one AI application in production by year-end 2024, up from 56% the year before. The shift from awareness to deployment is happening in plain sight.
BNM's 2025 Discussion Paper on AI in the Financial Sector, alongside the industry's first AI Governance Framework led by AICB and ABM, sets out the bar: responsible adoption, structured oversight, and traceable outcomes. Kollect*AI GPT was designed against that bar.
Source: Bank Negara Malaysia, Discussion Paper on Artificial Intelligence in the Malaysian Financial Sector (Aug 2025); BNM AI Survey 2024
Six quick questions on data, workflows, and governance. No data leaves your browser. At the end you'll see where Kollect*AI GPT can help most.
Kollect*AI GPT is Kollect's agent-based, context-aware large language model platform, designed specifically for collections, recovery, receivables, and operational analytics environments.
It enables natural-language querying, real-time dashboards, automated report generation, predictive analytics, risk and payment probability scoring, and treatment recommendations, all grounded in your operational data and learning continuously from outcomes.
Whether your operation is still "reactive" or already moving toward "predictive," Kollect*AI GPT integrates tightly with Kollect*Apps for Lenders and other Kollect platforms, so call outcomes, transcripts, classifications, and notes flow into one unified history for centralised analytics.
Kollect*AI GPT serves business users and operational teams across lending, finance, and collections, no SQL required.
Each capability stands on its own and combines with the others to turn raw operational data into structured, traceable, and predictive insight. Click any tab to explore.
Operations leaders, supervisors, and reporting teams who currently wait on Monday-morning reports. For organisations where the gap between question and answer is measured in days, not minutes.
Talk to UsRisk managers, recovery strategists, and operations heads who need to move from reactive collections to predictive intervention. Built for institutions ready to layer AI scoring on top of their existing portfolios.
Talk to UsBusiness users and operational teams without SQL skills. Anyone who has ever waited days for a "quick data pull" from the analytics team can ask the question themselves and act on the answer in the same hour.
Talk to UsCTOs, heads of data, and AI/ML leads at lenders and finance organisations who need flexibility on model choice, deployment topology, and data residency. For institutions where one-size-fits-all AI does not pass the architecture review.
Talk to UsChief Risk Officers, compliance heads, and internal audit teams responsible for AI governance and regulatory readiness. For institutions preparing for BNM's evolving expectations on responsible AI in financial services.
Talk to UsEvery team listed in "Who It's For", from collections supervisors to CFOs. The library gives users a starting point for the questions worth asking, and the assistant grows with them as they explore deeper analysis.
Talk to UsEvery prompt flows through the same agentic pipeline. The platform learns from outcomes and feeds them back into future queries through a continuous evaluation layer.
Almost 3 decades of deep banking, government, receivables, cash flow, and treasury experience, engineered into a single AI-driven platform.
Agentic LLMs, multi-model intelligence, and self-healing query generation, woven through every interaction with operational data.
Decades of banking, government, receivables, cash flow, and treasury knowledge embedded in every prompt template, model choice, and output format.
Dedication, innovation, and commitment as integral attributes, focused teams that deliver value, not just software.
Engage as SaaS, on-premise, or hybrid. The choice depends on your data residency, latency, and governance requirements.
