Artificial Intelligence and Machine Learning
Implementing Artificial Intelligence and Machine Learning in BFSI means navigating legacy infrastructure, fragmented data, and regulatory complexity. Entelect brings experience rooted in domain knowledge to help navigating these realities. Whether it's conversational banking, agentic workflows, dynamic risk scoring, or MLOps that keeps models accurate over time, we bring the experience to take AI from proof-of-concept to production.
Our Work
Discovery Vitality sought to create hyper-personalised health guidance for their members on their app.
To achieve this, they needed a hyper-personalised recommendation engine that had access to multiple data sources from different business units, enabling a comprehensive view of each member’s wellbeing.
We developed a data orchestration engine to power the recommendations – integrating clinical, behavioural, and lifestyle data across multiple sources in real time.
The engine surfaces three hyper-relevant next-best health actions for each member, paired with a personalised reward.
Higher engagement: Members can now complete health recommendations directly in the app and earn loyalty points increasing in-app engagement.
Lower risk: The recommendations contribute to early intervention and healthier behaviours, resulting in fewer chronic condition claims, and better long-term outcomes for members and insurer alike.
What We Do
Intelligent Assistants and Chatbots
Conversational AI that handles customer queries, guides users through complex processes, and reduces pressure on service teams.
Agentic AI
Agentic systems can autonomously execute multi-step workflows, coordinate across enterprise systems, tools, and data sources, and orchestrate complex tasks with minimal human intervention – with configurable guardrails, oversight, and control mechanisms that ensure safe and reliable execution.
Retrieval-Augmented Generation (RAG)
Ground large language models in your own data and knowledge bases to deliver accurate, context-aware responses – without the hallucinations or generic outputs of off-the-shelf models.
Large Language Model (LLM) Integration
Deploy and orchestrate foundation models within your enterprise environment – customised and governed to meet your specific use cases, security requirements, compliance obligations, and operational guardrails.
Customer Sentiment Analysis
Automatically analyse customer feedback, reviews, and interactions to surface insights that inform product decisions, service improvements, and retention strategies.
Conversational Banking
Implement AI-powered conversational banking experiences across chat, voice, and digital channels. Intelligent assistants can securely handle customer queries, guide users through complex financial processes, support transactional interactions, and deliver personalised assistance in real time.
Hyper-Personalisation
Deliver individualised experiences across digital channels by using machine learning to understand customer behaviour, preferences, and intent.
Fraud Detection and Prevention
Identify suspicious patterns and anomalies across transactions and behaviour in real time, reducing financial exposure while minimising friction for legitimate customers.
Risk Assessment and Scoring
Replace manual, rule-based risk processes with dynamic ML models that assess credit, operational, or compliance risk more accurately and consistently at scale.
Dynamic Pricing
Adjust pricing in response to market conditions, customer segments, and demand signals – powered by models that optimise for margin, conversion, or competitive positioning.
Automated Claims Handling
Accelerate claims processing by automating document intake, classification, and decision-making, reducing handling time and improving the customer experience.
Computer Vision
Extract meaning from images and video – whether that's verifying identity documents, inspecting assets, automating quality control, or processing visual data at a scale humans can't match.
Optical Character Recognition (OCR)
Digitise and extract structured data from documents, forms, and images, eliminating manual data entry and accelerating downstream workflows.
MLOps and Model Lifecycle Management
Build, deploy, monitor, and retrain models at scale with a robust MLOps framework – ensuring your AI investments remain accurate and aligned to business outcomes over time.
KEY PARTNERS
