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PROGRAM 07 · TEAM TRAINING

AI & Data for Banking Professionals

Faster credit memos, sharper risk checks, better customer service. Safely.

Important: This course covers productivity, analysis and communication support only. Credit, KYC, AML and compliance decisions stay with authorised bank officers under the bank's own policy and Bangladesh Bank rules. Only masked or sample customer data is used in class, and participants follow their bank's approved-tool policy.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
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Who this course is for

  • Relationship Managers, credit analysts and credit administration teams
  • Branch managers, operations and customer service officers
  • Risk, compliance, AML/CFT and internal control teams
  • Officers in commercial banks, Islamic banks, NBFIs and MFS providers

What your team will be able to do

  • Use AI safely within bank confidentiality and approved-tool rules
  • Draft credit memos and commentary faster from masked financials
  • Turn circulars into checklists and build early-warning sheets
  • Deploy four working automations in your own bank 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 credit, compliance and service

9:00–10:30S1Prompt engineering for banking
10:30Tea break
10:45–12:15S2Credit analysis, memos & risk commentary
12:15Lunch & prayer
1:00–2:30S3Regulations, compliance & communication
2:45–4:30LABBuild lab: masked credit memo and circular checklist
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Portfolio analytics, then the first two builds

9:00–10:30S4Formulas & banking data cleaning
10:30Tea break
10:45–12:15S5Branch, portfolio & risk reporting
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant & alerts
2:45–4:30LABBuild lab: dashboard, assistant and alerts on masked 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: Branch approval workflow
10:30Tea break
10:45–12:15S8Project 04: Statement & trade 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 Banking WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for banking work (credit commentary, circular summaries, customer letters in Bangla and English, ratio 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 a credit analyst, relationship manager, compliance officer or branch manager
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own banking work
  • Step-by-step reasoning for multi-part tasks such as ratio analysis across three years of financials or checking a file against a circular's requirements
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a credit memo (business profile → financial analysis → risks → mitigants → recommendation draft) 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 banking tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: customer names, account numbers, NID numbers, CIB reports, loan files, transaction data, internal limits and any confidential circular or audit report
  • Anonymising data before prompting; safe vs unsafe banking 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 banking tasks.
PART 2Banking 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

Banking Policy & Circular Assistant

Branch and credit colleagues ask about policy, charges or a circular and get an answer from approved documents, with the section cited.

  1. INCredit policy & circulars
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Regulatory & Renewal Alert Engine

Limit renewals, insurance, guarantee and LC expiry, KYC reviews and regulatory returns checked daily, with alerts 30, 15 and 7 days ahead.

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

Branch Request & Approval Workflow

Charge waivers, rate concessions and deviations routed by delegation authority, with maker and checker kept separate and every approval logged.

  1. INBranch request form
  2. RULESDelegation routing script
  3. OUTLogged approval with conditions
Built with Apps Script · Forms
04Session 8

Statement & Trade Document Extraction

Financial statements and trade documents become rows in your spreading template, with totals cross-checked and value mismatches flagged for an analyst.

  1. INFinancials & trade documents
  2. AIGemini structured extraction
  3. OUTSpreading template for review
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 Banking

Fairness & Non-Discrimination

  • Where bias enters banking 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 customer, borrower and guarantor data

Credit Fairness & Customer Confidentiality

  • No AI scoring that uses gender, religion, area or family background
  • Explaining a credit outcome in terms the customer can understand

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 banking 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 banking tasks
  • Mask customer data and use AI within bank confidentiality rules
  • Draft credit memos, circular checklists and customer replies faster
  • Clean portfolio data and build a branch and risk 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

A credit memo template and early-warning checklist
A circular checklist and a 20-question customer reply library
A branch and portfolio dashboard with checked commentary
A grounded banking policy & circular assistant your colleagues can use
A regulatory & renewal alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own bank department or branch

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
Banking tools
Power BI basicsCopilot (where the bank approves it)

What participants need

  • A laptop with Excel and a Google account
  • Basic Excel comfort (VLOOKUP, Pivot Tables) and masked or sample branch and loan 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 bank 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 bank 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