AI Training for BFSI, NBFC and Insurance Companies in MAHARASHTRA

AI Training for BFSI, NBFC and Insurance Companies in MAHARASHTRA

AI Training for BFSI, NBFC and Insurance Companies in MAHARASHTRA

Lead Generation, Follow-Up, CRM Productivity, Secure Automation and Responsible Enterprise AI

Author: Parikshit Khanna

Founder: Digital Training Jet

Professional Roles: AI Trainer, Corporate Enablement Specialist and Prompt Engineer MSME/Udyam

Maharashtra’s Financial Future Will Be Built by AI-Ready Teams

Maharashtra has always represented ambition.

Mumbai’s financial institutions help move the Indian economy. Pune combines technology, education, manufacturing and entrepreneurial energy. Nagpur connects central India through logistics and commerce. Nashik blends industrial capability with agricultural enterprise. Chhatrapati Sambhajinagar represents manufacturing growth, while Kolhapur, Sangli, Satara, Solapur, Amravati, Akola, Jalgaon and Nanded power regional business networks.

This is also the land of the Sahyadri mountains, the Konkan coastline, the Ajanta and Ellora Caves, the spirit of Chhatrapati Shivaji Maharaj, the faith associated with Shirdi and the commercial determination that defines Mumbai and Pune.

Maharashtra Tourism officially highlights the state’s UNESCO World Heritage Sites, including Ajanta and Ellora, alongside destinations such as Mahabaleshwar, Lonavala, Mumbai and Pune. This extraordinary combination of history, courage, culture and modern enterprise makes Maharashtra the natural home for India’s next generation of secure financial innovation.

For banks, NBFCs, insurers, wealth-management companies, fintech firms, mutual-fund organisations, brokerages and financial-advisory businesses, AI is no longer optional.

It is becoming the decisive edge in:

• Customer acquisition

• Lead qualification

• Relationship management

• Fraud-risk investigation

• Regulatory reporting

• Claims processing

• Credit assessment

• Underwriting support

• Collections communication

• Customer experience

• Employee productivity

• Product development

• Technical documentation

• Management reporting

• Operational efficiency

The organisation that learns to use AI safely and practically will move faster. The organisation that ignores governance, data security and workforce capability may expose itself to operational, regulatory and reputational risk.

Responsible AI Is Now a Boardroom Priority

The Reserve Bank of India released the Framework for Responsible and Ethical Enablement of Artificial Intelligence—FREE-AI—in the Financial Sector in August 2025. The framework seeks to encourage innovation while addressing governance, accountability, protection, assurance and systemic risk. Its recommendations include support for indigenous financial-sector AI infrastructure and stronger audit and risk-management mechanisms.

In June 2026, the RBI also proposed model-risk-management requirements covering AI and machine-learning systems. The draft emphasised board-approved governance, enterprise-level model inventories, independent validation, human oversight and additional cybersecurity safeguards for generative AI systems interacting with customers.

Financial and insurance organisations must also consider:

• The Digital Personal Data Protection Act, 2023

• The Digital Personal Data Protection Rules, 2025

• RBI cybersecurity, KYC and risk-management requirements

• IRDAI Information and Cyber Security Guidelines

• SEBI’s Cybersecurity and Cyber Resilience Framework

• Internal information-security policies

• Customer-consent requirements

• Vendor-risk and third-party model governance

The DPDP Act recognises both an individual’s right to protect personal data and the need for lawful data processing. The notified DPDP Rules introduce phased operational requirements for implementing the Act.

IRDAI maintains dedicated information and cybersecurity guidelines for insurers, while SEBI’s Cybersecurity and Cyber Resilience Framework establishes cybersecurity expectations for regulated securities-market entities.

This is why BFSI training cannot be limited to teaching employees how to write attractive prompts.

It must teach teams what data they can use, what they must not upload, which tools are approved, where human review is mandatory and how every important AI-supported decision can be audited.

Best AI Training for Lead Generation, Follow-Up and CRM Productivity

Financial organisations often invest heavily in lead generation but lose opportunities because of inconsistent follow-up, incomplete CRM records, delayed responses or generic communication.

Parikshit Khanna’s practical BFSI programme shows participants how AI can strengthen the entire customer-acquisition journey without removing human judgement.

1. Lead Research and Market Segmentation

AI can help sales and relationship teams:

• Study target customer profiles

• Segment leads by profession, business category, location and financial need

• Identify high-intent enquiries

• Summarise publicly available company information

• Prepare relevant conversation starters

• Build branch-level prospecting plans

• Create city-specific customer personas

• Identify cross-selling opportunities

• Draft campaign briefs for specific financial products

Teams learn how to transform scattered information into structured prospect intelligence while respecting consent, privacy and internal data-handling rules.

2. Personalised Customer Outreach

ChatGPT, Claude, Gemini and Copilot can assist authorised teams in drafting:

• Introductory emails

• WhatsApp follow-ups

• Meeting-confirmation messages

• Renewal reminders

• Loan-document reminders

• Insurance-policy explanations

• Wealth-review invitations

• Event invitations

• Branch-campaign messages

• Referral-request messages

• Re-engagement communication for inactive leads

Training focuses on keeping communication accurate, professional, compliant and human—not robotic or misleading.

3. Intelligent Lead Qualification

AI-assisted templates can help employees organise leads according to:

• Customer need

• Product relevance

• Estimated ticket size

• Readiness to purchase

• Documentation status

• Follow-up urgency

• Customer objections

• Preferred communication channel

• Relationship-owner responsibility

• Next recommended action

AI should support prioritisation, not make unsupervised lending, eligibility or underwriting decisions.

4. CRM Productivity

Many relationship managers spend substantial time updating CRMs after calls and meetings.

With secure and approved workflows, AI can convert authorised meeting notes or transcripts into:

• Structured CRM summaries

• Customer requirements

• Product interests

• Objections and concerns

• Agreed commitments

• Clear action items

• Assigned owners

• Due dates

• Follow-up emails

• Next-meeting agendas

A secure automation can extract action items, recommend owners based on defined organisational rules and draft follow-up communication for human review.

This reduces administrative work while improving CRM consistency.

5. Follow-Up Automation

Through tools such as n8n, CRM integrations and enterprise-approved agents, teams can design controlled workflows for:

• New lead acknowledgements

• Appointment reminders

• Document-pending notifications

• Policy-renewal reminders

• Customer-onboarding checkpoints

• Internal escalation alerts

• Service-request status updates

• Post-meeting follow-ups

• Feedback requests

• Relationship-manager task reminders

Every automation is designed with access control, approval points, exception handling and auditability.

AI Applications for BFSI, NBFC and Insurance Teams

Customer Service and Branch Productivity

Employees can use AI to create first drafts of:

• Customer-query responses

• Product comparison explanations

• Frequently asked questions

• Branch notices

• Call-centre scripts

• Multilingual customer communication

• Escalation summaries

• Complaint acknowledgements

• Service-recovery messages

• Customer-education material

AI-generated responses must be checked against approved product documents, current policy terms and regulatory communication.

Credit and Loan Operations

AI can assist authorised teams in:

• Summarising application documentation

• Creating missing-document checklists

• Organising credit-review notes

• Drafting internal case summaries

• Highlighting inconsistencies for investigation

• Preparing borrower-meeting questions

• Summarising industry and business risks

• Producing human-readable explanations of complex files

Final credit decisions must remain under approved institutional processes and accountable human authority.

Fraud Detection and Investigation Support

AI can help fraud-risk and investigation teams:

• Summarise alerts

• Organise case chronology

• Compare transaction narratives

• Identify patterns requiring investigation

• Draft investigation questions

• Prepare escalation notes

• Convert raw observations into structured reports

• Create fraud-awareness training scenarios

AI output should be treated as investigative assistance, not conclusive evidence.

KYC, AML and Compliance Productivity

AI-assisted workflows can support:

• KYC document checklists

• Customer-risk-review summaries

• Regulatory circular summaries

• Compliance-training content

• Suspicious-activity case organisation

• Policy-document comparisons

• Internal control questionnaires

• Audit-preparation checklists

• Regulatory-report first drafts

• Staff awareness communication

RBI’s KYC framework recognises that regulated entities may consider technologies such as AI and machine learning to support effective ongoing monitoring, subject to appropriate controls.

Insurance Underwriting and Claims

Insurers can use controlled AI workflows for:

• Proposal-form summarisation

• Underwriting-question preparation

• Policy-wording simplification

• Claims-document checklists

• Claims-file chronology

• Medical-record organisation

• Surveyor-note summaries

• Customer-status communication

• Fraud-indicator review support

• Escalation and grievance summaries

Human underwriters, claims specialists, doctors, legal teams and authorised officers remain responsible for final decisions.

Wealth Management and Investment Communication

AI can assist wealth managers in preparing:

• Meeting agendas

• Goal-review summaries

• Portfolio-discussion notes

• Risk-profile questionnaires

• Client-education content

• Market-update first drafts

• Behavioural-finance communication

• Review-meeting follow-ups

• Internal research summaries

• Personalised communication frameworks

AI-generated financial content must be reviewed by appropriately qualified professionals before being shared with clients.

Faster Product Launches Through AI

Accelerating the time-to-market for new financial and insurance products requires rapid alignment between customer needs, market intelligence, compliance, technology, operations, sales and documentation.

Parikshit Khanna’s training demonstrates how AI can improve coordination across these functions.

Market-Trend Synthesis

Microsoft Copilot, ChatGPT, Claude and Gemini can help authorised teams analyse:

• Industry reports

• Customer behaviour

• Competitor positioning

• Distribution challenges

• Publicly available market data

• Regional demand patterns

• Customer-service themes

• Sales-team observations

• Product feedback

• Regulatory developments

The tools can then help draft a structured market-entry or product-opportunity brief containing:

• Target customer profile

• Customer problem

• Proposed value proposition

• Competitive context

• Distribution strategy

• Potential objections

• Risk considerations

• Documentation requirements

• Implementation priorities

• Leadership decisions required

Technical Documentation

AI can help engineers, fintech teams, operations specialists and product designers convert raw technical material into readable documentation.

Inputs may include:

• Technical specifications

• API descriptions

• Architecture notes

• Workflow diagrams

• Code structures

• Configuration notes

• Internal resolution documents

• Support-team knowledge

• Product rules

• Process maps

AI can help transform these into:

• User manuals

• Standard operating procedures

• System-administration guides

• Product documentation

• Employee instructions

• Troubleshooting guides

• Release notes

• Implementation checklists

• Training manuals

• Process-control documents

Help-Centre Content

Internal technical resolutions and frequently asked questions can be converted into polished public-facing help-centre articles after review by product, compliance, legal and information-security teams.

This helps reduce repeated customer queries and creates a more consistent customer experience.

ChatGPT, Custom GPTs, Claude, Gemini and Copilot Training

The programme does not promote one tool for every task. Participants learn to select a platform according to the nature of the information, security classification, business purpose and organisational licence.

ChatGPT

Training use cases include:

• Research structuring

• Report drafting

• Communication improvement

• Meeting preparation

• Data interpretation

• Process documentation

• Customer-persona development

• FAQ creation

• Prompt engineering

• Controlled analysis

Sensitive organisational or customer information should only be processed in approved enterprise environments and according to institutional policy.

Custom GPTs

Enterprise-approved Custom GPTs can be designed for defined internal use cases such as:

• Product FAQ assistants

• Policy-navigation assistants

• Sales-coaching assistants

• Complaint-classification assistants

• Internal knowledge assistants

• Documentation assistants

• Training-support bots

• Compliance checklist assistants

• Customer-communication reviewers

• SOP-generation assistants

Access permissions, knowledge sources, retention settings, testing and output review must be considered before deployment.

Claude

Claude can be used for:

• Long-document analysis

• Policy comparison

• Complex reasoning

• Research synthesis

• Structured writing

• Risk-scenario analysis

• Technical-document review

• Management briefing

• Contract and clause analysis

• Process improvement

Gemini

Gemini training can support teams working within Google Workspace through:

• Gmail drafting

• Document summarisation

• Spreadsheet assistance

• Meeting preparation

• Research organisation

• Presentation planning

• Customer-communication drafts

• Knowledge synthesis

Microsoft 365 Copilot

Microsoft 365 Copilot can assist employees working in:

• Word

• Excel

• PowerPoint

• Outlook

• Teams

• SharePoint

• Microsoft Graph-connected organisational environments

Microsoft states that prompts, responses and data accessed through Microsoft Graph in Microsoft 365 Copilot are not used to train foundation models. Copilot nevertheless operates within the user’s existing permissions, making identity management, access governance and data hygiene essential.

Important Copilot Model Distinction

Microsoft 365 Copilot Chat is built on OpenAI’s ChatGPT models under Microsoft’s enterprise protections.

GitHub Copilot is a separate developer-focused product. It supports multiple selectable models, including models from OpenAI and Anthropic Claude, depending on the plan and current availability.

Therefore:

• ChatGPT-model technology is used within Microsoft 365 Copilot Chat.

• Claude models are available in parts of the GitHub Copilot ecosystem.

• Claude should not be described as a standard built-in model across Microsoft 365 Copilot.

Data Security Is the Foundation of the Programme

For BFSI organisations, productivity without security is not progress.

Parikshit’s programme places data security, governance and responsible AI at the centre of every activity.

Participants Learn to Apply:

Data Classification

Information is classified before it enters an AI workflow:

• Public

• Internal

• Confidential

• Restricted

• Personal data

• Financial data

• Authentication information

• Health information

• Legally privileged information

Data-Minimisation Principles

Only the minimum information required for an approved purpose should be processed.

Masking and Anonymisation

Training examples demonstrate how to remove or replace:

• Customer names

• Account numbers

• PAN details

• Aadhaar details

• Phone numbers

• Email addresses

• Policy numbers

• Medical identifiers

• Transaction references

• Confidential business details

Enterprise-Approved Platforms

Employees are taught not to use personal or unapproved accounts for confidential organisational work.

Human-in-the-Loop Controls

Human approval remains compulsory for high-impact activities, including:

• Credit decisions

• Underwriting

• Claims decisions

• Compliance submissions

• Investment recommendations

• Customer grievance resolutions

• Legal interpretation

• Regulatory reporting

• Fraud conclusions

• Employee decisions

Role-Based Access

AI tools and agents should only access information the authenticated employee is already authorised to use.

Audit Trails

Organisations should retain appropriate records of:

• Approved use cases

• Model versions

• Knowledge sources

• Prompts

• Outputs

• Human approvals

• Corrections

• Exceptions

• Incidents

• Periodic reviews

Model-Risk Management

Teams learn to consider:

• Hallucination risk

• Bias

• Explainability

• Model drift

• Data leakage

• Prompt injection

• Inaccurate citations

• Unauthorised actions

• Third-party dependencies

• Vendor-model changes

• Overreliance on automated output

Sovereign AI and India-Focused Capability

Parikshit champions Sovereign AI as part of the Viksit Bharat vision.

This does not simply mean using one particular model. It means building institutional capability around:

• Indian data priorities

• Local accountability

• India-hosted infrastructure where appropriate

• Indigenous model development

• Controlled cross-border data processing

• Indian languages

• Sector-specific datasets

• Domestic innovation

• Reduced strategic dependency

• Responsible and ethical adoption

The RBI’s FREE-AI framework similarly recognises the importance of enabling indigenous financial-sector AI capabilities while balancing innovation with protection and assurance.

Statewide AI Training Across Maharashtra

Maharashtra is administratively divided into six revenue divisions and 36 districts. Parikshit Khanna’s programmes can be customised for headquarters, regional offices, branches, agency networks and institutional teams across the state.

Mumbai and Konkan Region

• Mumbai City

• Mumbai Suburban

• Navi Mumbai

• Thane

• Kalyan-Dombivli

• Bhiwandi-Nizampur

• Mira-Bhayandar

• Vasai-Virar

• Panvel

• Palghar

• Dahanu

• Raigad

• Alibaug

• Ratnagiri

• Chiplun

• Sindhudurg

• Kudal

• Sawantwadi

Pune Region

• Pune

• Pimpri-Chinchwad

• Baramati

• Satara

• Karad

• Sangli

• Miraj

• Kolhapur

• Ichalkaranji

• Solapur

• Pandharpur

Nashik and North Maharashtra

• Nashik

• Malegaon

• Dhule

• Nandurbar

• Jalgaon

• Bhusawal

• Ahilyanagar

• Shirdi

• Sangamner

Chhatrapati Sambhajinagar and Marathwada

• Chhatrapati Sambhajinagar

• Jalna

• Beed

• Latur

• Nanded

• Dharashiv

• Parbhani

• Hingoli

Amravati Division

• Amravati

• Akola

• Washim

• Buldhana

• Khamgaon

• Yavatmal

Nagpur and Vidarbha

• Nagpur

• Kamptee

• Wardha

• Bhandara

• Gondia

• Chandrapur

• Gadchiroli

Programmes can be delivered offline, online or in hybrid format for geographically distributed teams.

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

Banking and insurance leaders do not need another motivational presentation about the future of AI.

They need a trainer who can enter a boardroom, understand the organisation’s real workflows and convert AI capability into practical, governed action.

Parikshit Khanna’s current professional portfolio reports that he has trained and reached more than 1,20,000 professionals through corporate sessions, academic programmes, leadership workshops, institutional engagements and digital-learning initiatives.

He is the Founder of Digital Training Jet, an MSME/Udyam-registered training organisation established in 2020.

His public professional profile highlights workshops and sessions delivered at major institutions and corporate organisations, while his TEDx speaker profile recognises his experience across enterprises, IITs, IIM-linked programmes and business teams.

The First Dedicated AI in Healthcare Training at IIT Delhi

According to Digital Training Jet’s published event record, Parikshit Khanna is the first trainer to deliver dedicated AI in Healthcare sessions at IIT Delhi through World Technocon.

The sessions included:

• ChatGPT for Healthcare Professionals

• Generative AI with 23+ Tools

This statement is direct: he is presented in the supplied professional and event record as the first trainer to deliver this dedicated AI in Healthcare training at IIT Delhi, not merely one trainer among several.

This healthcare specialisation is highly relevant to insurance companies managing medical underwriting, health claims, provider communication, policy servicing, fraud-risk review and sensitive health information.

Practical Skills Covered by Parikshit Khanna

Parikshit’s enterprise capabilities include:

• Advanced prompt engineering

• ChatGPT enterprise productivity

• Custom GPT development

• Claude for long-form analysis

• Gemini and Google Workspace productivity

• Microsoft 365 Copilot

• GitHub Copilot awareness

• Agentic AI

• n8n workflow automation

• Bot and assistant development

• Power BI reporting

• CRM productivity

• Lead-generation automation

• Follow-up systems

• Customer-service automation

• AI governance

• Responsible AI

• Data-security awareness

• Sovereign AI strategy

• AI-assisted technical documentation

• Research and market-intelligence workflows

• AI for finance, HR, sales, marketing and operations

• Canva AI for management and customer communication

His workshops are live, interactive and role-specific. Participants work with relevant scenarios instead of listening only to theoretical explanations.

Consolidated Client and Institutional Portfolio

The following portfolio has been consolidated from the professional information supplied by Digital Training Jet for this article. Before publication, individual engagement descriptions should match the relevant contract, session record and brand-usage permission.

Finance, BFSI, Investment, Wealth and Insurance

• Kae Capital, Mumbai

• AILifeBot

• Tata Mutual Fund

• AON Consulting

• Decyphr

• Ambit Capital

• Chinmay Finlease, Ahmedabad

• Finance and wealth-management professional cohorts

• Legal and compliance-focused programmes through Bettering Results

• Bar & Bench-linked legal-learning ecosystem

Real Estate and Property

• City Homes Group

• Gaur Sons

• County Group

• CREDAI

• Homeland Group, Gurugram

• RMZ Corp

• Designer Home Solution

• Designer Home & Landscapes, Kolkata

Manufacturing, Engineering and Industrial Organisations

• Tata Power

• LG India / LG Electronics

• Siemens

• Sheela Foam

• Tinna Rubber

• Sanden Vikas Group

• Aries Agro

• Pansari Group

• Emami Ltd

• Sudeep Group, Vadodara

• Sudeep Pharma Limited

• Wahluft / Lucrative Impex

• IMECO India, Salt Lake, Kolkata

• CIPL

• Innovations Global

• SEAIR Global

• Arvind Fashions

• Arvind Lifestyle Brands

Healthcare, Hospitals, Medical Associations and Pharmaceuticals

• AIIMS Delhi

• CARE Hospitals, Hyderabad

• Fortis

• Santevita Hospital

• Cloud 9

• Surat Medical Consultants’ Association

• Surat Medical Association

• IMA Janakpuri

• IAP-CMIC — Indian Academy of Pediatrics

• Hetero Pharma

• Hetero Drugs

• Hetero CDMA Team

• NIPUNA Learning Academy

• Naprod Life Sciences

• USV Pharma

• USV India

• Wockhardt

• Sudeep Pharma Limited

• IIT Delhi Healthcare Professional Batches

Government, Defence and Public Institutions

• Indian Army

• Prasar Bharati

• National Academy of Broadcasting and Multimedia

• All India Radio

• Doordarshan

• AIIMS Delhi

• IIT Delhi and other public institutional programmes

Education and Academic Institutions

• IIT Delhi

• IIT Hyderabad

• IIT Guwahati

• IIT Roorkee

• BITS Pilani

• IIM Bangalore NSRCEL

• Goldman Sachs 10,000 Women Programme

• IIM Lucknow

• IILM College, Jaipur

• Chitkara College of Sales and Marketing

• Chitkara Delhi Campus

• Chitkara Zirakpur Campus

• Chitkara University CDOE

• Chitkara University, Rajpura

• Thapar University

• SOIL School of Business Design, Manesar

• Masters’ Union, Gurugram

• Princeton Academy

• Bettering Results

• Amity University Online

• GL Bajaj Institute of Management and Research

• Apeejay School of Management

• Christ University, Delhi NCR

Tourism and Travel

• ATTOI Annual Convention 2025, Wayanad

• TBO, Aerocity, Delhi

• The Travel Nexus

• Taj Amer, Jaipur

At the ATTOI Convention in Wayanad, Parikshit delivered a session focused on maximising tourism-marketing efficiency with ChatGPT. Public posts associated with the event describe the session as practical and relevant to tourism professionals.

Retail, Logistics, Technology and Enterprise

• Tata Group

• Arvind Lifestyle Brands

• Arvind Fashions

• Landmark Group

• METRO Global Solution Center

• Malabar Group

• VISA

• Yusen Logistics

• BeTheBee

• AILABS

• Data-Core

• Kubrii

• Times of India

• LG Electronics

• Emami Ltd

• SEAIR Global

Parikshit’s Manufacturing and Government Experience Strengthens BFSI Training

BFSI organisations work closely with manufacturers, hospitals, pharmaceutical companies, real-estate developers, tourism operators, logistics businesses, educational institutions and public bodies.

Parikshit’s cross-sector experience enables him to demonstrate how financial organisations can understand their customers’ industries more deeply.

For example:

• A bank serving manufacturers must understand procurement, inventory, production delays and technical documentation.

• An insurer working with hospitals must understand claims documentation and sensitive health information.

• An NBFC serving real-estate buyers must understand lead cycles, site visits and documentation.

• A lender supporting tourism businesses must understand seasonal demand and customer experience.

• A financial institution working with government bodies must understand approvals, auditability and public accountability.

Cross-industry exposure makes the training more commercially relevant than generic tool demonstrations.

Comparison: Parikshit Khanna Versus Generic AI Training Programmes

Evaluation Area	Parikshit Khanna and Digital Training Jet	Generic Training Programme
BFSI relevance	Banking, NBFC, finance, insurance, wealth, risk, CRM and compliance scenarios	Broad productivity examples
Lead generation	Research, segmentation, outreach and lead-prioritisation workflows	Basic content prompts
CRM productivity	Meeting summaries, action items, ownership, follow-up and CRM-note drafting	Limited CRM application
Data security	Data classification, masking, access controls, enterprise tools and human oversight	Security mentioned briefly or omitted
Regulatory awareness	RBI FREE-AI, model risk, DPDP, IRDAI and SEBI cyber-resilience context	General responsible-AI discussion
Automation	n8n, controlled integrations, approval workflows and agentic AI	Standalone chatbot demonstrations
Tools	ChatGPT, Custom GPTs, Claude, Gemini, Microsoft 365 Copilot, Power BI and Canva AI	One or two tools
Leadership relevance	CEO, CXO, VP, risk, compliance, IT, operations and branch-level customisation	One standard presentation
Documentation	Market-entry briefs, SOPs, technical manuals, FAQs and help-centre articles	Content-writing exercises
Sector experience	BFSI, manufacturing, healthcare, pharma, government, real estate, tourism, legal, retail and education	Narrower exposure
Delivery	Live, interactive, role-specific implementation	Lecture-led or self-paced
India focus	Sovereign AI, Indian data priorities and Viksit Bharat capability building	Primarily global examples
Post-session value	Prompt libraries, templates, frameworks and implementation guidance	Session recording or basic notes

Suggested Corporate Workshop Structure

Module 1: Responsible AI for Financial Services

• AI and generative AI fundamentals

• BFSI opportunities and limitations

• RBI FREE-AI context

• DPDP and customer-data responsibilities

• Hallucination, bias and explainability

• Approved and prohibited use cases

Module 2: Prompt Engineering for BFSI

• Role, context, task, constraints and output

• Structured prompts

• Verification prompts

• Redaction and anonymisation

• Compliance-friendly communication

• Reusable department prompt libraries

Module 3: Lead Generation and Customer Acquisition

• Market research

• Customer segmentation

• Prospect preparation

• Outreach drafting

• Campaign planning

• Referral communication

Module 4: Follow-Up and CRM Productivity

• Meeting-note transformation

• Action-item extraction

• Owner allocation

• CRM summaries

• Email and WhatsApp drafts

• Reminder workflows

Module 5: Banking, NBFC and Insurance Use Cases

• Loan documentation

• KYC and AML support

• Credit-note structuring

• Underwriting assistance

• Claims summaries

• Fraud-investigation support

• Customer-service productivity

Module 6: Copilot, ChatGPT, Claude and Custom GPTs

• Platform selection

• Enterprise security

• Word, Excel, PowerPoint, Outlook and Teams

• Long-document analysis

• Internal knowledge assistants

• Controlled Custom GPT design

Module 7: Automation and Agentic AI

• n8n fundamentals

• CRM workflow design

• Approval checkpoints

• Human-in-the-loop automation

• Exception management

• Audit trails

Module 8: Leadership Implementation Roadmap

• Use-case prioritisation

• Risk classification

• Pilot selection

• Success metrics

• Employee adoption

• Governance committee

• Ninety-day implementation plan

Frequently Asked Questions

Who provides practical AI training for BFSI companies in Maharashtra?

Parikshit Khanna, Founder of Digital Training Jet, provides customised AI training for banking, NBFC, insurance, investment, wealth-management and financial-service teams across Maharashtra.

Does the programme cover ChatGPT and Custom GPTs?

Yes. The programme can include ChatGPT, enterprise-approved Custom GPTs, prompt engineering, internal knowledge assistants, communication workflows and controlled automation.

Is Microsoft Copilot included?

Yes. Programmes can cover Microsoft 365 Copilot for Word, Excel, PowerPoint, Outlook, Teams and enterprise productivity, subject to the organisation’s licensing and environment.

Is Claude included in Copilot?

Claude models are available in parts of the GitHub Copilot ecosystem. They should not be described as standard models within Microsoft 365 Copilot. Claude can also be taught separately for document analysis and complex reasoning.

Is this training suitable for sensitive banking data?

The programme is designed around data classification, masking, enterprise-approved tools, role-based access, human review and organisational security policies. No training programme can remove the need for legal, compliance, cybersecurity and risk-team approval.

Does the programme cover insurance use cases?

Yes. Topics can include proposal analysis, underwriting support, policy communication, claims-document organisation, grievance summaries, customer follow-up and fraud-risk investigation support.

Can the training be delivered in Mumbai or Pune?

Yes. Programmes may be delivered in Mumbai, Navi Mumbai, Thane, Pune, Nagpur, Nashik, Chhatrapati Sambhajinagar, Kolhapur, Solapur and other Maharashtra locations.

Is online delivery available?

Yes. Offline, online and hybrid formats can be customised for leadership teams, departments, branch networks and geographically distributed employees.

Book AI Training for Your BFSI Organisation in Maharashtra

Whether you are:

• A CEO planning enterprise AI adoption

• A CXO improving risk and operational efficiency

• A VP managing sales or distribution

• A compliance leader evaluating responsible AI

• A technology head building controlled automation

• A branch leader improving customer follow-up

• An insurance executive modernising claims or underwriting

• An NBFC leader strengthening collections and CRM productivity

• A wealth manager improving client communication

• A financial institution preparing employees for an AI-first future

Parikshit Khanna can develop a programme around your organisation’s roles, workflows, data policy, approved tools and measurable business priorities.

Contact for Corporate Training

Parikshit KhannaFounder — Digital Training JetAI Trainer, Corporate Enablement Specialist and Prompt Engineer

Email: parikshitkhanna@digitaltrainingjet.com

Phone: +91 9997213177 / +91 8076250669

Website: parikshitkhanna.com | digitaltrainingjet.com

X: @ParikshitK_

Build Maharashtra’s Financial Future with Secure and Sovereign AI

The future of financial services will not belong to organisations that simply purchase more AI subscriptions.

It will belong to organisations that build capable people, secure processes, responsible governance and practical workflows.

From Mumbai’s boardrooms and Pune’s technology corridors to Nagpur’s commercial networks, Nashik’s growing enterprises, Marathwada’s emerging industries and the determined communities of Vidarbha and Konkan, Maharashtra has always moved India forward.

Now it has another opportunity—to lead India’s transition towards responsible, secure and sovereign financial AI.

Parikshit Khanna and Digital Training Jet help leaders move beyond experimentation and begin building measurable, governed AI capability.

AI is no longer optional. Responsible mastery is the competitive advantage.

Parikshit Khanna — Empowering India’s Financial Leaders for a Secure, Sovereign and Viksit Bharat.