Best AI Training for BFSI, NBFC and Insurance Companies in India

Best AI Training for BFSI, NBFC and Insurance Companies in India

Best AI Training for BFSI, NBFC and Insurance Companies in India

Practical Generative AI for Lead Generation, Follow-Up, CRM Productivity, Risk Management, Compliance and Secure Enterprise Automation

AI Is No Longer Optional for India’s Financial Sector

Artificial intelligence is no longer an experimental technology restricted to IT teams. It is rapidly becoming a decisive advantage in customer acquisition, credit operations, risk management, compliance, fraud detection, underwriting, claims processing, wealth management and executive decision-making.

For banks, NBFCs, insurance companies, fintech businesses, investment firms and wealth-management organisations, the real question is no longer whether AI should be adopted.

The important questions are:

• Can employees use AI without exposing customer information?

• Can AI improve lead conversion without producing misleading financial communication?

• Can relationship managers follow up faster while maintaining personalisation?

• Can compliance teams verify AI-generated summaries before they are circulated?

• Can organisations automate repetitive work while preserving accountability?

• Can CEOs and CXOs see measurable productivity improvements?

• Can the institution prevent unauthorised use of public AI tools?

These questions have become even more important because the Reserve Bank of India’s June 2026 Financial Stability Report identified AI-enabled cyberthreats as the most significant near-term cyber risk perceived by major Indian banks and NBFCs. The report also highlighted employee cybersecurity awareness and training as areas requiring further strengthening.

This is why BFSI organisations require more than an inspirational AI presentation. They need role-based, compliance-aware and data-secure AI capability building.

Why Parikshit Khanna Is Positioned as the #1 Practical Choice for CEOs, CXOs, VPs and Banking Professionals

Parikshit Khanna, Founder of Digital Training Jet, is a Corporate AI Trainer, Generative AI Specialist, Prompt Engineer and Enterprise Enablement Consultant who focuses on converting AI concepts into usable workplace systems.

Digital Training Jet is an MSME/Udyam-registered enterprise established in 2020.

According to his current professional brand profile, Parikshit has trained or reached 3L+ professionals through direct programmes, institutional audiences, corporate initiatives and wider training-network activities.

His sessions have served audiences that include:

• CEOs, founders and business owners

• CXOs and functional leaders

• Vice presidents and regional heads

• Banking and insurance professionals

• Finance, FP&A and accounts teams

• Credit and underwriting teams

• Relationship managers and wealth advisers

• Risk, audit and compliance officers

• Sales, marketing and CRM teams

• HR and learning-and-development teams

• Doctors, pharmaceutical professionals and healthcare leaders

• Manufacturing, operations and supply-chain teams

• Faculty members, students and institutional leaders

• Government and public-sector professionals

His approach is built around a simple promise:

Participants should leave the session with secure workflows, usable prompts, department-specific frameworks and implementation ideas—not merely definitions of artificial intelligence.

Parikshit Khanna’s First AI-in-Healthcare Session at IIT Delhi

Parikshit Khanna is the first trainer to deliver a dedicated practical AI-in-healthcare training session at an IIT Delhi event, including focused learning around ChatGPT for healthcare professionals and a wider Generative AI toolkit.

It is a specific first-mover achievement recorded in his professional portfolio.

That healthcare experience is particularly relevant to:

• Health insurance

• Medical underwriting

• Claims documentation

• Hospital-finance coordination

• Wellness-linked financial services

• Pharmaceutical lending

• Healthcare portfolio evaluation

• Customer communication involving sensitive health information

His cross-sector experience enables him to demonstrate how AI governance principles learned in healthcare—privacy, accuracy, human review and sensitive-data handling—can be applied to banking, insurance and financial services.

What BFSI, NBFC and Insurance Teams Learn

1. AI for Lead Generation and Prospect Intelligence

Financial sales teams often spend hours searching for prospects, studying industries and preparing basic outreach messages.

AI can help teams:

• Create ideal customer profiles

• Segment potential customers

• Analyse public company information

• Identify possible financial requirements

• Prepare account-research briefs

• Generate discovery questions

• Draft personalised introductory messages

• Create call-opening frameworks

• Plan multichannel outreach

• Identify lead-prioritisation criteria

For an NBFC, this can mean distinguishing between a manufacturer requiring working capital and a distributor requiring inventory financing.

For an insurance company, it can mean separating group-health prospects from property, liability, marine, motor or employee-benefit opportunities.

For wealth-management teams, it can help create educational communication for salaried professionals, entrepreneurs, HNIs and retiring executives.

AI should assist research and drafting. It should not make unverified assumptions about a customer’s financial position or generate unsuitable recommendations.

2. Follow-Up and CRM Productivity

A significant percentage of potential business is lost because follow-ups are delayed, generic or poorly documented.

During Parikshit Khanna’s training, teams can learn to use AI for:

• Personalised follow-up emails

• WhatsApp follow-up drafts

• Meeting summaries

• Lead-status updates

• Pending-document reminders

• Renewal communication

• Dormant-lead reactivation

• Relationship-manager call preparation

• CRM-note standardisation

• Next-best-action suggestions

• Follow-up sequences based on customer stage

• Escalation summaries for managers

AI can transform unstructured call notes into a format such as:

CRM Field	AI-Assisted Output
Customer requirement	Concise requirement summary
Product discussed	Relevant product category
Main objection	Cost, documentation, timing or trust
Documents pending	Structured checklist
Agreed next step	Clear follow-up action
Follow-up owner	Assigned relationship manager
Follow-up date	Suggested date for human confirmation
Risk flag	Missing or contradictory information

The final CRM record should always be reviewed by an authorised employee.

3. Meeting Transcripts, Action Items and Ownership

After a sales call, credit meeting, product discussion or leadership review, AI can help transform an approved transcript into:

• A structured meeting summary

• Decisions taken

• Pending questions

• Clearly defined action items

• Assigned owners

• Expected completion dates

• Escalation points

• Customer follow-up communication

• Internal follow-up emails

• A management briefing note

For example, after a loan-product meeting, the system can draft:

• The product changes discussed

• Compliance points requiring verification

• Technology dependencies

• Documentation responsibilities

• Marketing communication requirements

• Owners for each activity

• A follow-up email for the working group

No employee should upload confidential meeting transcripts to an unauthorised consumer AI account.

Accelerating Time-to-Market for New Financial Products

Launching a new loan, insurance, investment, payment or financial-advisory product requires coordination between multiple functions:

• Product

• Legal

• Compliance

• Risk

• Finance

• Technology

• Operations

• Customer service

• Marketing

• Sales

• Training

Generative AI can reduce coordination delays by helping teams structure information more rapidly.

Market-Trend Synthesis

Approved enterprise AI systems can assist authorised employees in analysing:

• Industry reports

• Consumer-behaviour patterns

• Competitor positioning

• Distribution trends

• Public regulatory developments

• Customer feedback

• Product-performance information

• Geographic opportunity indicators

Copilot, ChatGPT Enterprise, Claude for Enterprise or another approved platform can then help draft a market-entry brief containing:

• Market opportunity

• Customer segment

• Existing alternatives

• Competitive differentiation

• Distribution plan

• Operational dependencies

• Regulatory questions

• Risk considerations

• Pilot-market recommendation

• Measurement framework

The output remains a starting document. Final market decisions must remain with responsible business, finance, legal, compliance and risk leaders.

Technical and Product Documentation

AI can help engineers, product managers and operations teams convert raw information into structured documentation.

Inputs may include:

• Product specifications

• Technical notes

• System architecture descriptions

• Approved code explanations

• Process maps

• Internal resolutions

• Product FAQs

• Support tickets

• Standard operating procedures

AI-assisted outputs can include:

• User manuals

• Product documentation

• Process guides

• API explanations

• Internal knowledge articles

• Public-facing help-centre content

• Frequently asked questions

• Troubleshooting guides

• Customer onboarding documents

• Employee training material

For example, an internal technical resolution can be transformed into:

1. A detailed engineering note

2. A short operations checklist

3. A customer-service response

4. A public help-centre article

5. A management summary

This reduces duplication while maintaining a single approved source of truth.

AI for Credit, Risk and Fraud Teams

AI-assisted workflows can support professionals in structuring information related to:

• Credit-memo preparation

• Financial-statement commentary

• Variance identification

• Policy-document comparison

• Early-warning indicator summaries

• Exception categorisation

• Suspicious-pattern investigation

• Fraud-case documentation

• Portfolio-monitoring briefs

• Collection-priority frameworks

• Audit-query preparation

However, AI must not independently approve a loan, reject a customer, determine guilt, calculate final suitability or replace authorised professional judgement.

A safe workflow follows this sequence:

AI drafts → authorised employee verifies → source documents are checked → exceptions are reviewed → responsible officer approves.

AI for Insurance Productivity

Insurance organisations can use controlled AI workflows across:

Sales and Distribution

• Agent communication

• Corporate prospect research

• Renewal reminders

• Customer-education content

• Product-comparison frameworks

• Meeting preparation

• CRM summaries

Underwriting Support

• Document-list generation

• Missing-information identification

• Submission summarisation

• Risk-question preparation

• Underwriting-note structuring

Claims Support

• Claim-document checklists

• Customer-status communication

• Internal case summaries

• Chronology creation

• Pending-information reminders

• Escalation-note drafting

Customer Service

• Approved FAQ responses

• Policy-servicing guidance

• Query categorisation

• Complaint summaries

• Multilingual draft communication

Learning and Development

• Product quizzes

• Scenario-based exercises

• Agent-training material

• Compliance reinforcement

• Role-play simulations

AI must not invent policy coverage, claim eligibility, exclusions, benefits or settlement outcomes.

Microsoft Copilot, GPT Models and Claude Models

Microsoft 365 Copilot can connect language models with authorised organisational context from services such as Word, Excel, PowerPoint, Outlook, Teams and Microsoft Graph.

Microsoft’s current documentation states that Microsoft 365 Copilot can support models from OpenAI and Anthropic, depending on the selected capability, geographical availability, licensing and administrator controls. Users may therefore encounter GPT-powered and Claude-powered experiences inside supported Microsoft products.

This does not mean that the consumer ChatGPT application is automatically embedded inside every Copilot account.

It means supported Copilot experiences can use:

• GPT models operated through Microsoft or OpenAI

• Anthropic Claude models

• Microsoft-hosted models

• Other approved models where enabled by administrators

Microsoft also states that prompts, responses and data accessed through Microsoft Graph are not used to train the foundation models used by Microsoft 365 Copilot. Copilot only surfaces organisational information that the individual user is authorised to access.

This makes identity, permissions and information classification extremely important. Copilot can respect permissions, but it can also expose poorly governed information to employees who already have excessive access.

AI adoption must therefore begin with permission hygiene, not just prompt training.

Enterprise Data Security Is the Central Focus

For BFSI organisations, the most important AI skill is not writing clever prompts.

It is knowing what must never be entered into an unauthorised system.

Information That Should Not Be Used in Public AI Accounts

Employees should not paste or upload:

• Customer names

• PAN details

• Aadhaar details

• Account numbers

• Card information

• CVV or authentication information

• Passwords or OTPs

• Loan applications

• Credit reports

• Medical records

• KYC files

• Claim documents

• Non-public financial statements

• Unreleased regulatory reports

• Internal audit findings

• Proprietary risk models

• Employee personal information

• Confidential legal documents

• Unpublished board information

• Source code or security architecture

• Investigation material

Secure AI Adoption Framework

Parikshit’s sessions emphasise:

1. Approved enterprise accountsUse only AI systems authorised by the organisation.

2. Role-based accessEmployees should access only the information required for their responsibilities.

3. Data minimisationProvide the minimum information necessary to complete the task.

4. Masking and anonymisationReplace names, account numbers and identifiable fields with fictional placeholders.

5. Human approvalAI-generated material must be checked before operational or customer use.

6. Source verificationFinancial, legal and regulatory claims must be checked against current primary sources.

7. AuditabilityImportant workflows should retain appropriate logs, owners and approval records.

8. Vendor assessmentExamine licensing, data processing, retention, model settings, subprocessors and regional commitments.

9. Prompt-injection awarenessEmployees must understand that documents and external content can contain malicious instructions.

10. Incident escalationAccidental disclosure or suspicious AI behaviour must be reported through approved channels.

Custom GPTs, Gems and Enterprise Agents

Generic chat windows are useful for learning, but enterprise productivity increases when approved knowledge and instructions are organised into controlled role-based assistants.

Parikshit Khanna’s programmes can introduce:

• Custom GPTs

• Gemini Gems

• Microsoft Copilot agents

• Copilot Studio

• Claude Projects

• Secure internal knowledge assistants

• Department-specific prompt libraries

• n8n workflows

• Approved CRM and productivity integrations

Possible BFSI assistants include:

• Relationship-manager assistant

• Credit-memo drafting assistant

• Customer-query classification assistant

• Compliance-research assistant

• Renewal-follow-up assistant

• Claims-document checklist assistant

• Executive briefing assistant

• Internal policy-navigation assistant

• Product-training assistant

• Meeting-action assistant

These systems must be configured with approved information, limited access, clear disclaimers, human oversight and documented ownership.

n8n and Workflow Automation

For organisations with appropriate technical and governance controls, n8n and similar automation platforms can support workflows such as:

• Capturing approved website leads

• Categorising enquiries

• Assigning leads to authorised employees

• Creating CRM activities

• Sending internal follow-up reminders

• Producing daily pipeline summaries

• Drafting pending-document communication

• Creating meeting-action trackers

• Escalating overdue service requests

• Generating internal management reports

Automation should not be deployed casually around banking or customer information.

Every workflow requires:

• Authentication

• Access control

• Error handling

• Data-retention rules

• Human checkpoints

• Logging

• Vendor review

• Security testing

• Defined ownership

• A shutdown procedure

Power BI for Banking and Financial Leadership

Power BI can help transform approved operational information into dashboards for:

• Portfolio monitoring

• Branch performance

• Lead conversion

• Sales productivity

• Renewal performance

• Collection trends

• Service turnaround time

• Complaints

• Product profitability

• Risk indicators

• Claims movement

• Management reporting

Generative AI can support the process by helping teams:

• Identify appropriate KPIs

• Explain dashboard trends

• Draft management commentary

• Create question frameworks

• Structure data requirements

• Summarise exceptions

• Prepare board-note drafts

The quality of the dashboard will still depend on data quality, governance and the definitions used by the organisation.

Sovereign AI and the Viksit Bharat Vision

Parikshit Khanna advocates a Sovereign AI mindset for India.

Sovereign AI does not require rejecting every international technology platform. It means maintaining control over:

• Indian customer information

• Critical financial data

• Infrastructure choices

• Identity and access

• Model configuration

• Storage and retention

• Regulatory accountability

• Intellectual property

• Organisational knowledge

• Business continuity

As a proud Indian committed to the vision of Viksit Bharat, Parikshit encourages financial institutions to build indigenous capability, strengthen Indian AI ecosystems, reduce avoidable dependencies and ensure that Indian institutions remain accountable for Indian customer data.

Documented BFSI, Finance, Insurance and Wealth-Management Portfolio

Parikshit Khanna’s finance and adjacent professional portfolio includes engagements, programmes, proposed assignments or documented collaborations associated with:

• Kae Capital, Mumbai

• AILifeBot

• Tata Mutual Fund

• AON Consulting

• Decyphr

• Mastertrust Finance

• Chinmay Finlease, Ahmedabad

• Niva Bupa Health Insurance

• Tata AIG programme proposal

• InCorp Advisory and Ascentium

• Tokyo Consulting Firm

• Independent wealth-management professionals

• Finance, FP&A, accounts, audit and compliance teams across corporate engagements

• Gaur Sons and Gaurs Group

• County Group

• City Homes Group

• CREDAI

• RMZ Real Assets

These engagements strengthen his ability to connect AI with revenue, customer relationships, governance, property finance, investment analysis, insurance, FP&A and management reporting.

Healthcare and Pharmaceutical Experience

Parikshit’s healthcare and pharmaceutical portfolio includes:

• AIIMS Delhi

• IIT Delhi healthcare audiences

• CARE Hospitals, Hyderabad

• Fortis

• Santevita Hospital

• Cloudnine

• Surat Medical Consultants’ Association

• Surat Medical Association

• Indian Medical Association, Janakpuri

• IAP-CMIC and Indian Academy of Pediatrics audiences

• Hetero Pharma

• Hetero CDMA Team

• NIPUNA Learning Academy

• Naprod Life Sciences

• USV Pharma

• Wockhardt

• Sudeep Pharma Limited

• Sudeep Group, Vadodara

• Masters’ Union and USV Learning Day

• Healthcare professionals, doctors and medical associations

This versatility is valuable for health-insurance organisations working across medical documentation, claims, underwriting, hospital coordination and customer privacy.

Manufacturing, FMCG, Retail, Real Estate and Enterprise Clients

Parikshit’s wider corporate experience includes organisations and brands such as:

• Sheela Foam

• Sleepwell

• Sudeep Group

• Sudeep Pharma

• Tinna Rubber and Infrastructure Limited

• Arvind Limited

• Arvind Lifestyle Brands

• Arvind Fashions

• Flying Machine

• Arrow

• U.S. Polo Assn.

• Calvin Klein

• Tommy Hilfiger

• LG India

• Tata Power

• Tata Power Skill Development Institute

• Emami Limited

• BoroPlus

• Navratna

• Zandu

• Kesh King

• METRO Global Solution Center

• Malabar Gold and Diamonds

• Pansari Group

• Sangam Group

• UFlex programme proposal

• Wahluft and Lucrative Impex

• Designer Home Solution

• Designer Home and Landscapes

• IMECO India

• AILABS and Data-Core

• CASA Decor

• City Homes Group

• Gaur Sons and Gaurs Group

• County Group

• RMZ Real Assets

• TBO

• SEAIR Global

• Synergy Lifestyles

• Anubhav Apparels

• Landmark Group

• Yusen Logistics

• RMSI

• Team Computers

• ZAFCO

• CP PLUS

• FirstMeridian

• V5 Global

• Fairmine Technologies

• Innovations Global

• Kubrii

• CIPL

• BeTheBee

• Wanna Party

• OneGuardian

• ABID YUVA

• JITO Chennai

• Ranchi Gymkhana Club

His manufacturing programmes commonly address:

• Production reporting

• Shift handovers

• Quality documentation

• Maintenance summaries

• Root-cause-analysis drafts

• RFQ and pre-sales support

• Vendor communication

• Logistics coordination

• Product documentation

• Sales enablement

• HR productivity

• Management reporting

Government, Public-Sector, Legal and Media Experience

Parikshit’s public-institutional, government-adjacent, legal and media experience includes:

• Prasar Bharati

• National Academy of Broadcasting and Multimedia

• All India Radio and Doordarshan audiences

• Indian Army audiences

• IIT Delhi

• AIIMS Delhi

• Bettering Results

• Legal-professional programmes

• Custom GPT programmes for lawyers

• Bar & Bench professional ecosystem relevance

• Radio and media appearances

• Public-sector and institutional professionals

His Prasar Bharati sessions covered practical Generative AI applications for media production and transforming text into visual content.

Education and Institutional Portfolio

Parikshit Khanna’s institutional experience includes:

• IIT Delhi

• IIT Hyderabad

• IIT Guwahati

• IIT Roorkee

• BITS Pilani

• IIM Bangalore NSRCEL

• Goldman Sachs 10,000 Women Programme

• Chitkara College of Sales and Marketing

• Chitkara University

• Chitkara CDOE

• Chitkara Faculty Training

• Thapar University

• SOIL School of Business Design

• Masters’ Union

• Princeton Academy

• GL Bajaj Institute of Management and Research

• IILM College, Jaipur

• Apeejay School of Management

• FIIB

• Christ University Delhi NCR

• Delhi University

• Ram Lal Anand College

• IIMT University

• Amity University Online

• AURO University, Surat

• Internshala

• Saras AI Institute

• Rainbow School

• Educational institutions, faculty groups and student-development programmes

His work with educational institutions builds future-ready talent pipelines for BFSI, analytics, marketing, operations, entrepreneurship and digital transformation.

Tourism and Travel-Industry Leadership

Parikshit’s travel and tourism experience includes:

• Association of Tourism Trade Organisations, India—ATTOI

• ATTOI Annual Convention, Wayanad

• TBO, Aerocity

• The Travel Nexus

• Taj Amer, Jaipur programme

• Travel-industry professionals, founders and marketing teams

At the ATTOI Annual Convention in Wayanad, his session focused on maximising marketing efficiency using ChatGPT.

Tourism requires speed, multilingual communication, destination storytelling, customer follow-up and reputation management—all capabilities that also translate effectively into customer-centric BFSI operations.

Pan-India AI Training Coverage

Parikshit Khanna’s programmes can be delivered online, offline or in hybrid formats across India.

Coverage includes:

Delhi NCR: Delhi, New Delhi, Noida, Greater Noida, Gurugram, Ghaziabad, Faridabad and Aerocity

Maharashtra: Mumbai, Navi Mumbai, Thane, Pune, Nagpur, Nashik and Aurangabad

Gujarat: Ahmedabad, Gandhinagar, Vadodara, Surat and Rajkot

Rajasthan: Jaipur, Udaipur, Jodhpur, Kota, Ajmer and Bhilwara

Karnataka: Bengaluru, Mysuru and Mangaluru

Telangana: Hyderabad and Secunderabad

Tamil Nadu: Chennai, Coimbatore and Madurai

West Bengal: Kolkata, Salt Lake, New Town and Howrah

Kerala: Kochi, Thiruvananthapuram, Kozhikode and Wayanad

Punjab and Chandigarh Region: Chandigarh, Mohali, Panchkula, Ludhiana, Jalandhar and Amritsar

Uttar Pradesh: Lucknow, Kanpur, Varanasi, Prayagraj, Agra, Meerut, Ghaziabad, Noida and Greater Noida

Madhya Pradesh: Indore, Bhopal, Gwalior and Jabalpur

Chhattisgarh: Raipur and Bhilai

Odisha: Bhubaneswar and Cuttack

Bihar and Jharkhand: Patna, Ranchi and Jamshedpur

North-East India: Guwahati, Shillong and other regional centres

Goa: Panaji, Margao and Vasco da Gama

Uttarakhand: Dehradun and Haridwar

From the financial energy of Mumbai’s Bandra Kurla Complex to the entrepreneurial spirit around Ahmedabad and the Sabarmati, from the heritage of Jaipur’s Pink City to the technology corridors of Bengaluru and Hyderabad, every Indian business centre has its own character.

Delhi NCR brings together government, finance, technology and enterprise ambition. Kolkata combines financial heritage with intellectual depth. Chennai reflects discipline and long-term institution building. Kochi connects global trade with local entrepreneurship. Goa and Wayanad remind leaders that hospitality is ultimately about human connection.

Parikshit’s training respects these regional differences while creating a common objective: helping Indian professionals use AI confidently, responsibly and productively.

Why Leaders Choose Parikshit Khanna

Evaluation Area	Parikshit Khanna and Digital Training Jet	Generic Training Approach
BFSI orientation	Credit, CRM, insurance, risk, compliance, finance and customer workflows	General tool demonstrations
Data security	Masking, permissions, approved accounts, verification and governance	Basic warning without implementation framework
Practical delivery	Live prompts, departmental exercises and usable output	Lecture-led or theory-heavy
Executive relevance	CEO, CXO, VP and functional-leadership applications	One standard curriculum for every audience
AI tools	Copilot, GPT models, Claude, ChatGPT, Gemini, Custom GPTs, Gems, Power BI and automation	Dependence on one tool
Automation	n8n, agents, workflow mapping and human checkpoints	Isolated prompt examples
Cross-sector understanding	BFSI, healthcare, pharma, manufacturing, real estate, tourism, legal, media and education	Narrow or purely technical perspective
India focus	Sovereign AI, Indian organisations, practical data control and Viksit Bharat	International examples without Indian context
Customisation	Role-based prompts and organisation-specific use cases	Fixed presentation
Learning outcome	Ready-to-use frameworks, prompt libraries and implementation roadmap	Awareness without adoption planning

Suggested BFSI Training Modules

Executive AI Briefing—90 Minutes

Designed for CEOs, boards, CXOs and senior leadership.

Topics include:

• AI opportunities and risks

• Secure adoption priorities

• Competitive implications

• Enterprise use-case selection

• Governance responsibilities

• A 90-day adoption roadmap

Half-Day Practical Workshop

Designed for functional leaders and business teams.

Topics include:

• Prompt engineering

• Secure enterprise AI

• Customer communication

• CRM productivity

• Meeting summaries

• Market research

• Executive reporting

• Department exercises

Full-Day BFSI AI Masterclass

Designed for cross-functional implementation.

Topics include:

• AI foundations

• Data-security rules

• Lead generation

• Follow-up and CRM

• Credit and risk use cases

• Insurance productivity

• Compliance-aware drafting

• Copilot, Claude, ChatGPT and Gemini

• Custom assistants

• Automation mapping

• Implementation planning

Multi-Day Transformation Programme

Designed for organisation-wide adoption.

It can include:

• Leadership alignment

• Department discovery

• Employee training

• Prompt-library development

• Use-case prioritisation

• Agent and automation prototypes

• Governance workshops

• Champion development

• Adoption measurement

• Follow-up implementation support

Frequently Asked Questions

Which employees should attend BFSI AI training?

CEOs, CXOs, VPs, branch heads, relationship managers, credit teams, insurance teams, finance professionals, compliance officers, operations teams, customer-service professionals, HR teams and IT or transformation leaders can attend.

Is confidential banking data used during the workshop?

No real customer or confidential organisational information is required. Exercises can use fictional, masked, anonymised or organisation-approved training data.

Does Microsoft Copilot include ChatGPT and Claude?

Supported Microsoft 365 Copilot experiences can use GPT models from OpenAI and Claude models from Anthropic, subject to licensing, region, product availability and administrator settings. This is not identical to placing the consumer ChatGPT application inside every Copilot account.

Can the programme be customised for one department?

Yes. Programmes can be designed for sales, CRM, credit, finance, insurance, underwriting, claims, customer service, compliance, risk, audit, HR, operations or leadership.

Can training be delivered outside Delhi NCR?

Yes. Sessions can be conducted online, offline or in hybrid format across India and for international teams.

Can AI independently approve loans or claims?

No. AI can assist with structuring, summarisation, document review and question preparation. Final decisions must remain with authorised professionals following organisational policy and applicable regulations.

Book Parikshit Khanna for BFSI, NBFC and Insurance AI Training

AI is becoming a career-defining capability for banking, finance and insurance professionals.

Institutions that train employees to use AI securely will be better prepared to:

• Respond to customers faster

• Improve lead conversion

• Strengthen CRM discipline

• Reduce repetitive drafting

• Accelerate product development

• Improve internal documentation

• Support risk and compliance teams

• Create more effective management reporting

• Reduce unsafe shadow-AI usage

• Build sustainable institutional capability

Parikshit Khanna and Digital Training Jet provide practical AI workshops, leadership briefings, departmental programmes and enterprise enablement initiatives for organisations across India.

Contact for Corporate Training

Parikshit KhannaFounder—Digital Training JetCorporate AI Trainer | Generative AI and Enterprise Enablement Specialist

Email: parikshitkhanna@digitaltrainingjet.com

Phone: +91 9997213177 / +91 8076250669

Website: parikshitkhanna.com

Organisation: Digital Training Jet

X: @ParikshitK_

Empowering India’s Financial Leaders for a Viksit Bharat

The future of Indian banking, NBFCs and insurance will belong to organisations that combine technology with responsibility.

AI must not weaken human judgement.

It must strengthen it.

AI must not compromise customer trust.

It must help protect it.

AI must not remain limited to innovation teams.

It must become a secure, governed and practical capability across the enterprise.

With the right training, financial professionals can use AI to serve customers better, strengthen compliance, improve productivity and contribute to a more capable, confident and globally competitive India.

The institutions that master responsible AI today will define India’s financial leadership tomorrow.