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PROGRAM 21 · TEAM TRAINING

AI & Data for Insurance Professionals

Faster underwriting, smoother claims, and agents who sell with confidence.

Important: AI supports underwriters, claims officers and agents. It does not accept or reject a proposal, settle or deny a claim, or decide a premium. Policyholder and medical data stays within approved tools.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
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Request a proposalSee the curriculum

Who this course is for

  • Underwriters and underwriting support teams
  • Claims officers, surveyors' coordinators and claims managers
  • Agency managers, bancassurance and corporate sales teams
  • Life and non-life insurers, brokers and bancassurance partners

What your team will be able to do

  • Summarise proposals, survey and medical reports for the underwriter
  • Speed up claims with checklists, summaries and red-flag notes
  • Explain policies in plain Bangla and equip agents to sell honestly
  • Deploy four working automations in your own insurance team
How it runs

3 days at your office, 8 sessions

Three sessions a day plus a hands-on build lab every afternoon. Day 3 ends with capstone presentations.

Day 1

9:00 am – 5:00 pm

AI chatbots for insurance work

9:00–10:30S1Prompt engineering for insurance
10:30Tea break
10:45–12:15S2Underwriting & claims support
12:15Lunch & prayer
1:00–2:30S3Plain-word policies & agent enablement
2:45–4:30LABBuild lab: prompt library on your own files
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Insurance data, then the first two builds

9:00–10:30S4Formulas & insurance data cleaning
10:30Tea break
10:45–12:15S5Insurance analytics & management reports
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant & alerts
2:45–4:30LABBuild lab: dashboard, assistant and alerts on your data
4:30–5:00Q&A and day recap

Day 3

9:00 am – 5:00 pm

Last two builds and the capstone

9:00–10:30S7Project 03: Claims intake workflow
10:30Tea break
10:45–12:15S8Project 04: Claim document extraction
12:15Lunch & prayer
1:00–3:00LABCapstone build clinic
3:15–4:30LABCapstone presentations
4:30–5:00Certificates and next steps
Group: 10–40 people from one organisationSame content and projects in both formatsBangla delivery with English technical termsEvery session ends with a deliverable
Curriculum

8 sessions, one build in each

3 modules · 8 sessions · 4 hands-on projects

PART 1AI Chatbots for Insurance WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for insurance work (long policy wordings, claim file summaries, Bangla explanations, premium tables)
  • Free vs paid tiers; a workflow that needs no international payment card
  • Bangla vs English output quality; when to draft in English and translate
  • Which tool for a long document, which for a formula, which for a polished letter

Prompt Engineering Fundamentals

  • What a prompt is; why the same question gives different answers
  • The four-part structure: role, context, task, output format
  • Role prompting: act as an underwriter, claims officer, agency manager or customer service lead
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own insurance work
  • Step-by-step reasoning for multi-part tasks such as checking a claim file against policy terms or comparing two plans for a customer
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a claim review (documents → checklist → coverage questions → summary note) into a sequence of smaller steps

Iteration & Prompt Library Building

  • Why the second prompt matters more than the first; refining instead of restarting
  • Diagnosing a bad output: vague instruction, missing context or wrong tool
  • Building reusable prompt templates for repeated insurance tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: policyholder names and NID, medical reports, claim files, nominee details, bank account numbers, reinsurance terms
  • Anonymising data before prompting; safe vs unsafe insurance use cases
  • Hallucination awareness; verifying every figure, date, name and legal reference
  • The verification rule: AI drafts, a person checks before anything leaves the building
DELIVERABLEa personal prompt library of 10 templates for your repeated insurance tasks.
PART 2Insurance Data Analysis in Excel & Google SheetsSessions 4–5
PART 3Applied Projects: AI Assistants & AutomationSessions 6–8
Applied projects

Four automations, running in your organisation

01Session 6

Policy Wording & Underwriting Assistant

Underwriters, claims officers, agents and call centre staff get answers from your policy wordings and underwriting guidelines, with the section cited.

  1. INPolicy wordings & guidelines
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Renewal & Regulatory Alert Engine

Policy renewals, premium dues, claim deadlines, IDRA returns and treaty renewals checked daily, with alerts 30, 15 and 7 days ahead.

  1. INRenewal & regulatory tracker
  2. RUNDaily Make scenario
  3. OUTAlert to the right owner
Built with Make · Sheets · Gmail
03Session 7

Claims Intake & Approval Workflow

Claims logged by form, document checklists sent by claim type, approval routed by claim amount and reminders when turnaround targets slip.

  1. INClaim intimation form
  2. RULESApproval routing script
  3. OUTApproved claim with audit trail
Built with Apps Script · Forms
04Session 8

Claim Document Extraction Pipeline

Claim forms, hospital bills and survey reports become clean rows, checked against the policy register and flagged when over the sum insured.

  1. INClaim forms, bills & reports
  2. AIGemini structured extraction
  3. OUTClaim summary for the officer
Built with Gemini API · Drive

Capstone presentation

Each person presents one automation built for their own workplace.

Day 3 afternoon
Applied across every session

Responsible & Ethical AI in Insurance

Fairness & Non-Discrimination

  • Where bias enters insurance decisions: data, wording, criteria and past patterns
  • Proxy discrimination: address, age, gender or background inferred indirectly

Privacy & Data Protection

  • Data minimisation: collect only what the decision requires
  • Retention and deletion of policyholder, nominee and claimant data

Fair Treatment of Policyholders

  • Clear, honest product explanations before a customer signs
  • Claims decided on evidence and policy terms, never on an AI score alone

Accountability & Human Oversight

  • Human-in-the-loop by design: AI recommends, a named person decides
  • Who owns an AI-assisted decision when it is challenged

Workforce Impact & Your AI Use Policy

  • Talking to insurance teams about AI without triggering job-loss fear
  • Reskilling and role redesign as AI absorbs routine work
Outcomes

By the end, your team can

  • Choose the right AI tool and write prompts that work first time
  • Maintain a prompt library covering your repeated insurance tasks
  • Prepare underwriting notes and claim summaries with consistent checklists
  • Explain policies in plain Bangla and equip agents to sell honestly
  • Clean portfolio and claims data and build an insurance dashboard
  • Build and deploy automations with Make, Apps Script and the Gemini API
  • Apply fairness, transparency and privacy to every AI-assisted decision

And leaves with

An underwriting note template and claim review kit
A plain-Bangla policy explainer and agent sales kit
An insurance performance dashboard with checked commentary
A grounded policy wording & underwriting assistant your colleagues can use
A renewal & regulatory alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own insurance team

Tools your team will use

Chatbots
ChatGPTGeminiClaudeCopilotDeepSeek
Content
CanvaGammaCapCutGoogle Slides
Data
Microsoft ExcelGoogle SheetsPower Query
Workspace
GmailCalendarMeetFormsDrive
Automation & AI builds
MakeGoogle AI StudioApps ScriptGemini API
Insurance tools
Looker StudioWhatsApp BusinessCanva

What participants need

  • A laptop with Excel and a Google account
  • Basic Excel comfort and masked sample policy, claim or premium data
  • One real work file to practise on from Session 2
  • No coding background required; free tiers only

How your team will learn

  • build-along classes (you work while the trainer works)
  • practise on your own workplace file, not dummy data
  • every session ends with a deliverable
  • Bangla delivery with English technical terms
  • recordings, prompt library and setup guides
  • certificate after capstone submission
Request a proposal

Bring this program to your insurance team

Tell us about your team. We reply within one working day with a plan built around your own documents and workflows.

  1. 1 · A short discovery call with your insurance lead
  2. 2 · We tailor examples to your masked files
  3. 3 · Offline at your office, or online live classes
Chat on WhatsApp
Request a proposal