AI training for Productivity Training for Banking, NBFC, Insurance and Finance Teams in Nepal

AI Productivity Training for Banking, NBFC, Insurance and Finance Teams in Nepal

AI training for Productivity Training for Banking, NBFC, Insurance and Finance Teams in Nepal

For banking, NBFC, insurance and finance leaders, artificial intelligence is no longer an optional experiment. It is becoming a decisive advantage in risk management, regulatory documentation, fraud detection, customer experience, credit analysis, financial reporting, operational efficiency and executive decision-making.

The real question is no longer, “Should our organisation use AI?”

The real questions are:

• Which finance and banking processes should be improved first?

• What information can safely be shared with an AI platform?

• How can teams prevent confidential customer data from entering unapproved tools?

• Which tasks require human approval?

• How should AI-generated calculations, summaries and recommendations be verified?

• Can AI reduce turnaround time without creating compliance, privacy or reputational risks?

This is where Parikshit Khanna, Founder of Digital Training Jet, brings a practical, enterprise-focused approach to AI capability building.

His updated professional profile reports 1,21,000+ professionals trained through corporate programmes, institutional workshops, leadership sessions, healthcare programmes, government-linked engagements and cross-functional AI interventions.

Instead of limiting training to generic prompt-writing demonstrations, Parikshit connects AI tools with the actual work performed by CEOs, CXOs, CFOs, VPs, branch heads, relationship managers, underwriters, auditors, risk teams, compliance professionals, FP&A teams, operations managers and customer-service leaders.

Why AI Productivity Matters to Banking, NBFC, Insurance and Finance Teams

Financial organisations operate in an environment where accuracy, confidentiality, speed and accountability must work together.

A delayed credit memo can slow down loan approval. An incomplete compliance report can create regulatory exposure. A poorly documented customer interaction can affect service quality. An incorrectly interpreted spreadsheet can influence a high-value business decision.

Practical AI adoption can help teams improve these processes without removing human responsibility.

Banking and NBFC Use Cases

AI-supported workflows can help banking and NBFC teams with:

• Preliminary credit-appraisal summaries

• Borrower-profile analysis

• Loan-document checklists

• KYC document categorisation

• Early-warning indicator narratives

• Delinquency follow-up communication

• Branch-performance summaries

• Collection-call preparation

• Customer complaint classification

• Policy and circular summarisation

• Credit committee presentation drafts

• Relationship-manager meeting preparation

• Portfolio-risk commentary

• Management information system reporting

• Standard operating procedure development

AI should support professional judgement, not replace an authorised credit, legal, compliance or risk decision.

Insurance Use Cases

Insurance teams can apply controlled AI workflows to:

• Policy-document comparison

• Claims-document summarisation

• Underwriting question preparation

• Medical-document organisation

• Customer communication

• Claims-status explanation

• Fraud-indicator investigation support

• Renewal-campaign planning

• Agent productivity

• Product-training material

• Complaint categorisation

• Escalation summaries

• Regulatory documentation

• Health-insurance hospital coordination

Parikshit’s experience with healthcare and pharmaceutical audiences adds valuable context for health insurance, medical claims, hospital documentation and sensitive policyholder information.

Finance and FP&A Use Cases

Finance teams can use approved AI environments for:

• Budget-versus-actual commentary

• Variance analysis

• Monthly business-review narratives

• Cash-flow explanations

• Management-report drafting

• Reconciliation support

• Audit-preparation checklists

• Expense classification

• Working-capital analysis

• Vendor-payment follow-ups

• Board-presentation preparation

• Scenario analysis

• Forecast commentary

• Policy and contract review

• Financial-data storytelling

AI-generated calculations and financial interpretations must be validated against approved source data before being used for decision-making.

Lead Generation, Follow-up and CRM Productivity

Banking, NBFC, insurance, wealth, real estate, industrial and B2B finance teams frequently lose opportunities because leads are not qualified properly, follow-ups are delayed, meeting notes remain unstructured or CRM records are incomplete.

Parikshit’s training helps teams build practical AI workflows for the entire lead lifecycle.

1. Lead Research and Qualification

AI can help relationship managers and business-development teams:

• Research a company before the first meeting

• Identify its industry, revenue model and geographic presence

• Understand potential financing, insurance or investment requirements

• Analyse publicly available expansion signals

• Prepare discovery questions

• Develop account-specific value propositions

• Prioritise leads using defined scoring criteria

• Identify potential cross-selling opportunities

A commercial banker can use AI to prepare for a manufacturing client meeting. An insurance professional can study the client’s operational risks. A wealth manager can create a structured discussion brief based on the customer’s approved profile.

2. Meeting Preparation and Conversation Intelligence

Before a meeting, AI can create:

• Client background briefs

• Previous interaction summaries

• Suggested discovery questions

• Product-comparison talking points

• Objection-handling frameworks

• Industry-risk questions

• Cross-selling possibilities

• Meeting agendas

After an authorised transcript is available, AI can extract action items, assign proposed owners, identify deadlines and draft follow-up communication. The output should be reviewed before it is entered into the CRM or sent to a customer.

3. Follow-up Communication

AI can draft personalised:

• Meeting follow-up emails

• Document-request messages

• Loan-application reminders

• Policy-renewal messages

• Premium-payment reminders

• Proposal summaries

• Relationship-nurturing messages

• Internal escalation notes

• Management updates

The goal is not to send robotic messages. It is to give relationship managers more time for meaningful customer conversations.

4. CRM Productivity

AI-supported CRM workflows can help teams:

• Convert meeting notes into structured fields

• Recommend the next action

• Identify inactive opportunities

• Detect incomplete records

• Prepare account summaries

• Group leads by priority

• Draft pipeline-review commentary

• Identify opportunities requiring escalation

• Create branch-wise follow-up reports

• Prepare weekly conversion summaries

CRM automation must operate within approved access controls. Sensitive personal, financial and customer information should never be transferred to an unauthorised consumer AI account.

Accelerating Time-to-Market for New Financial Products

Accelerating the time-to-market for new products requires rapid market alignment, coordinated reviews and disciplined technical documentation.

This is particularly important when banks, NBFCs and insurers launch:

• Digital lending products

• Insurance riders

• Wealth-management offerings

• Co-branded financial products

• SME lending programmes

• Supply-chain finance products

• Embedded finance solutions

• Customer-service platforms

• Mobile application features

• New branch campaigns

Market Trend Synthesis

Microsoft Copilot, ChatGPT, Claude and Gemini can help approved teams synthesise industry reports, customer research, competitor information and internal insights into structured market-entry briefs.

A typical market brief can include:

• Target customer segment

• Market problem

• Competitor positioning

• Distribution strategy

• Customer objections

• Regulatory considerations

• Operational requirements

• Product risks

• Communication strategy

• Pilot success metrics

AI should not invent market statistics. Teams must retain the source links, publication dates and supporting evidence.

Technical Documentation

AI can help engineers, product designers, operations specialists and finance teams convert raw specifications, process notes, code structures and architectural documentation into readable materials such as:

• User manuals

• Product requirement documents

• Process maps

• Operational checklists

• Training guides

• Implementation instructions

• Customer onboarding documents

• Internal control documentation

• Frequently asked questions

• Help-centre articles

AI can also transform approved internal technical resolutions or support FAQs into polished, public-facing help-centre content. Confidential internal details, security configurations and customer information must be removed before publication.

Meeting-to-Execution Workflow

After a product meeting, an approved AI workflow can:

1. Summarise the discussion.

2. Extract decisions.

3. Separate confirmed decisions from open questions.

4. Draft clear action items.

5. Propose responsible owners.

6. Identify deadlines.

7. Prepare follow-up communication.

8. Create a management-status summary.

Human approval remains essential before owners or deadlines are formally assigned.

AI Productivity for Coal, Mining, Power and Industrial Finance Teams

The coal, mining, power, steel, cement and heavy-engineering sectors have complex financial and operational requirements.

These industries power homes, factories, transportation networks and national infrastructure. Behind every production target are finance professionals managing contractors, equipment, fuel, logistics, inventory, maintenance, capex and regulatory documentation.

Parikshit’s cross-sector experience enables him to connect financial AI with industrial realities.

Coal and Mining Finance Workflows

Training can be customised for:

• Mine-wise budget analysis

• Production-versus-dispatch reconciliation

• Contractor-billing summaries

• Royalty and levy documentation

• Equipment-maintenance cost analysis

• Fuel supply agreement review

• Tender comparison

• Procurement-spend classification

• Inventory-ageing analysis

• Capex proposal summaries

• Working-capital planning

• Railway and road logistics reporting

• Vendor-risk assessment

• Safety-document summarisation

• ESG and sustainability reporting

• Management information system preparation

• Board and ministry presentation support

Industrial Lead Generation and CRM

Coal, mining and industrial companies can also use AI to improve B2B lead generation for power plants, cement manufacturers, steel companies, engineering contractors, logistics providers and equipment suppliers.

AI can help commercial teams:

• Identify potential industrial buyers

• Prepare account-research briefs

• Create tender-monitoring summaries

• Draft capability presentations

• Personalise follow-ups

• Maintain distributor and dealer CRM records

• Prepare quotation comparison tables

• Analyse customer complaints

• Create renewal and maintenance reminders

• Build technical-sales knowledge bases

Programmes can be delivered for teams in Delhi NCR, Dhanbad, Ranchi, Bokaro, Jamshedpur, Asansol, Durgapur, Kolkata, Bhubaneswar, Angul, Talcher, Rourkela, Jharsuguda, Raipur, Korba, Bilaspur, Singrauli, Nagpur, Chandrapur and other mining and industrial clusters.

Data Security Comes Before AI Productivity

Banking and finance organisations cannot approach AI governance as an afterthought.

India’s Digital Personal Data Protection Act requires data fiduciaries to implement appropriate technical and organisational measures and take reasonable security safeguards to prevent personal-data breaches. It also places responsibility on the data fiduciary for processing undertaken on its behalf by a data processor.

Parikshit’s enterprise training places data classification and safe tool selection before automation.

A Practical AI Data-Security Framework

Green Data

Information that may be suitable for an approved AI platform:

• Public information

• Published annual reports

• Public product descriptions

• Anonymised sample data

• Approved marketing material

• Generic templates

Amber Data

Information requiring internal approval, masking or controlled access:

• Internal procedures

• Vendor information

• Operational reports

• Employee information

• Non-public performance data

• Draft policies

• Internal meeting transcripts

Red Data

Information that should not enter an unauthorised AI environment:

• Customer account details

• PAN or Aadhaar information

• Card information

• Passwords and authentication codes

• Unmasked KYC documents

• Confidential transaction data

• Medical records

• Investigation material

• Privileged legal communication

• Unreleased financial results

• Restricted defence or government information

Security Controls Covered in the Training

Depending on the organisation’s technology environment, sessions can address:

• Enterprise account selection

• Tenant-level administration

• Role-based access

• Single sign-on

• Data-loss-prevention policies

• Retention controls

• Audit logging

• Approved connector management

• Redaction and anonymisation

• Human approval checkpoints

• Vendor-risk assessment

• Prompt-injection awareness

• Output verification

• Incident escalation

• Model and agent governance

OpenAI states that business data from ChatGPT Business, ChatGPT Enterprise and its API platform is not used for model training by default. Enterprise offerings also provide access, retention and authentication controls. Organisations must still configure these features according to their own risk, legal and compliance requirements.

Copilot, ChatGPT, Custom GPTs, Claude, Gemini and Enterprise AI

Parikshit’s programmes are tool-neutral. The objective is to teach teams how to select the correct approved platform for a defined task.

Microsoft 365 Copilot

Microsoft 365 Copilot can support work inside Word, Excel, PowerPoint, Outlook, Teams and approved organisational data environments.

Microsoft now provides OpenAI GPT models through Microsoft 365 Copilot. Eligible environments can also use approved Anthropic Claude models within supported Copilot experiences, subject to region, licensing, organisational settings and tenant-administrator controls. Microsoft provides indicators when Claude models are being used and allows administrators to restrict provider access to selected users or security groups.

Training use cases include:

• Excel analysis and commentary

• Word document drafting

• PowerPoint presentation preparation

• Outlook email support

• Teams meeting summaries

• Internal research

• Organisational search

• Copilot agents

• Workflow automation

It is more accurate to distinguish between the ChatGPT application and the OpenAI GPT models available through Copilot. Parikshit explains this difference so that employees understand the platform, model, licence and data boundary they are using.

ChatGPT and Custom GPTs

Training can cover:

• Advanced prompt engineering

• Data analysis

• Deep research

• Custom GPT creation

• Knowledge-grounded assistants

• Role-specific finance tools

• Internal FAQ assistants

• Report-generation workflows

• Customer communication

• Presentation and document development

• Controlled connector usage

Claude

Claude is useful for:

• Long-document analysis

• Policy comparison

• Contract review

• Audit preparation

• Reasoning-intensive tasks

• Structured writing

• Reusable Projects

• Research and planning

• Complex management reports

Where enabled, Claude models can also be accessed within supported Microsoft 365 Copilot experiences. Admin controls and provider-specific data terms must be reviewed before deployment.

Gemini and Gems

Gemini and custom Gems can support:

• Research

• Google Workspace productivity

• Document summarisation

• Presentation preparation

• Role-specific assistants

• Multimedia understanding

• Reusable instructions

Power BI

Power BI training can help finance and leadership teams develop:

• Portfolio dashboards

• Branch-performance dashboards

• Collections dashboards

• Risk-monitoring views

• Sales-pipeline reports

• Budget-versus-actual analysis

• Claims dashboards

• Executive summaries

• Vendor-payment reports

• Industrial finance dashboards

n8n and Workflow Automation

For technically prepared organisations, sessions can introduce controlled automation for:

• Lead capture

• CRM updates

• Follow-up reminders

• Approval routing

• Report generation

• Customer onboarding

• Compliance documentation

• Reconciliation workflows

• Internal notifications

• Google Sheets and Microsoft 365 integrations

Automation should not be activated in a production environment without security review, testing, error handling and approval controls.

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

1. Business Workflows, Not Generic Demonstrations

Each programme is built around the organisation’s departments, roles, approved tools and real productivity barriers.

2. Banking, Finance and Cross-Sector Understanding

Financial institutions serve manufacturing, healthcare, real estate, tourism, logistics, energy, pharmaceutical, retail and technology clients.

Parikshit’s cross-sector experience helps banking and insurance professionals understand the industries they finance, insure, analyse and support.

3. Leadership and Employee-Level Capability Building

Sessions can be designed separately for:

• Boards and CEOs

• CXOs and business heads

• CFO and FP&A teams

• Risk and compliance teams

• Branch and relationship teams

• Operations professionals

• IT and digital-transformation teams

• Sales and customer-service teams

4. Secure AI Adoption

The training covers what employees should do, what they should never do and when a request must be escalated to legal, compliance, information security or technology teams.

5. Live Building

Participants develop usable prompts, templates, dashboards, assistants and workflows during the session.

6. Indian Enterprise Context

The programme can incorporate Indian banking realities, data-protection expectations, approval hierarchies, customer diversity, branch operations and sector-specific terminology.

7. Sovereign AI and Viksit Bharat

Parikshit champions the development of Indian AI capability using responsible data practices, appropriate infrastructure choices, Indian organisational context and human accountability.

Sovereign AI does not mean selecting a platform based only on where a company originated. It requires evaluating data location, contracts, model access, deployment architecture, organisational controls, security requirements and national interest.

The First Dedicated AI-in-Healthcare Training at IIT Delhi

Parikshit Khanna is recorded in Digital Training Jet’s documented professional portfolio as the first trainer to deliver a dedicated AI-in-Healthcare training session at IIT Delhi.

The programme focused on practical applications of ChatGPT and generative AI for healthcare professionals. This milestone is especially relevant to banking and insurance because healthcare AI requires the same disciplines needed in high-stakes financial environments:

• Sensitive-data protection

• Verification

• Human oversight

• Responsible communication

• Clear limitations

• Escalation protocols

• Professional accountability

Digital Training Jet’s published professional record consistently identifies this as IIT Delhi’s first dedicated AI-in-Healthcare training intervention.

Consolidated Corporate, Government and Institutional Portfolio

The following portfolio combines direct corporate training, institutional sessions, programme cohorts, collaborations, conference engagements and professional learning platforms. The format and scope of work differ by organisation.

Banking, Finance, NBFC, Insurance, Investment and Advisory

Parikshit’s reported finance-sector portfolio includes Kae Capital, Tata Mutual Fund, AILifeBot, AON Consulting, Decyphr, Mastertrust Finance, Ambit Capital, Edelweiss, Hem Securities, Chinmay Finlease Ahmedabad, Visa, Tata AIA, DMI Finance, Fairmine Group, Green Earth Advisory, ICICI Prudential Mutual Fund, InCorp Advisory, Ascentium and finance, underwriting, valuation, asset-liability management, portfolio, FP&A and HR teams across enterprise clients.

Recent portfolio additions include Malabar Gold & Diamonds, Dubai branch, and the Goldman Sachs 10,000 Women Programme through NSRCEL, IIM Bangalore. The Goldman Sachs reference relates specifically to the NSRCEL programme association and its participant cohort.

Real Estate, Construction and Infrastructure

His real-estate and infrastructure portfolio includes CITY HOMES GROUP, Gaur Sons, Gaursons India, Gaurs Group, County Group, CREDAI, CREDAI Chhattisgarh, RMZ Real Assets Corporation, Homeland Group, Golden Grande, Imperial Group, Kanakia Group, Abhinandan Ventures, PropEquity, Designer Home Solution, Designer Home & Landscapes and property-sector business audiences.

This experience supports use cases involving project finance, mortgage products, lead qualification, broker productivity, customer follow-up, CRM discipline, construction reporting and investor communication.

Healthcare, Hospitals, Medical Associations and Pharmaceuticals

His healthcare and pharmaceutical portfolio includes AIIMS Delhi, CARE Hospitals Hyderabad, Fortis, Santevita Hospital, Cloud 9, Cloudnine Hospitals, Dr Agarwal’s Eye Hospital, Surat Medical Consultants’ Association, Surat Medical Association, IMA Janakpuri, IMA South Delhi, 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, Sudeep Group Vadodara, Hearzap, JPCON 2026 and IIT Delhi healthcare cohorts.

Manufacturing, Automotive, Engineering, Energy and Industrial Organisations

Parikshit’s manufacturing and industrial portfolio includes Tata Power, Tata Power Skill Development Institute, LG India, LG Electronics, Siemens, Waaree Group, Sheela Foam, Sleepwell, Bonfiglioli, Tinna Rubber & Infrastructure, Sudeep Group Vadodara, Sudeep Pharma, Sangam Group Bhilwara, Tracks & Towers, PolyWorks India, Sanden Vikas Group, River Engineering, Johnnette Technologies, WSL Auto, VULKAN Technologies, Aries Agro, Jenson & Jenson Lubricants, Z Premium Oil, Z Premium Lubricants, Emami Limited, OCS Services, BW Offshore, Planet Group, Wahluft, Lucrative Impex, IMECO India, Writer Corporation, SEAIR Global, Pansari Group, CIPL, Corporate Infotech, Innovations Global, Kubrii, ZAFCO, Yusen Logistics, RMSI, Team Computers, CP Plus, MEP Consulting Engineers, Hero Future Energies, Philip Morris, Deki, Dekin Electronics, VEGA, KnitPro, Anubhav Apparels, Arvind Lifestyle Brands, Arvind Fashions, Tommy Hilfiger, Calvin Klein, Landmark Group, Casa Decor, BeTheBee, AILABS, Data-Core, Micros IT Solutions, OneGuardian, FirstMeridian, V5 Global, Fairmine Technologies, Tokyo Consulting Group, Sinokor India, Knack Group and other operational, procurement, maintenance, HR, finance and leadership audiences.

Government, Defence and Public Institutions

His reported government, defence and public-institution experience includes Indian Army, Prasar Bharati, Doordarshan, All India Radio, National Academy of Broadcasting and Multimedia, AIIMS Delhi, State Mental Health Authority Uttarakhand, IIT Delhi, IIT Roorkee, IIT Hyderabad, IIT Guwahati, Delhi University, Ram Lal Anand College at the University of Delhi, Delhi Technological University and government-linked learning audiences.

Universities, Colleges and Education Institutions

His education and institutional portfolio includes IIT Delhi, IIT Roorkee, IIT Hyderabad, IIT Guwahati, BITS Pilani, IIM Bangalore through NSRCEL, Goldman Sachs 10,000 Women Programme cohorts, Thapar Institute of Engineering and Technology, Chitkara University, Chitkara College of Sales and Marketing at Delhi and Zirakpur, Chitkara CDOE, GL Bajaj Institute of Management and Research, GL Bajaj Institute of Technology and Management, SOIL School of Business Design, Masters’ Union, IILM College Jaipur, Princeton Academy, Princeton Consultants, Apeejay School of Management, IIMT, Christ University, Amity University Online, Gaurs International School, Eicher School, Bettering Results and legal-professional learning communities.

Tourism, Travel and Hospitality

His travel and tourism portfolio includes:

• ATTOI Annual Convention, Wayanad

• TBO and TBO Aerocity

• The Travel Nexus at Taj Amer, Jaipur

• Kyra Tours

• Nijhawan Group

• LAP Travel

• SEAIR Global

• Tourism, travel-sales and hospitality professionals

His ATTOI keynote focused on maximising marketing efficiency with ChatGPT while retaining the human warmth that makes travel memorable.

Technology, GCCs, Professional Services and Industry Platforms

Additional portfolio references include METRO Global Solution Center, Innovatiview, Economic Times HRWorld, ETHRWorld, CII New Delhi, JITO Chennai, JITO Raipur, ABID YUVA, Bettering Results, Bar & Bench ecosystem collaborations, Princeton Consultants, AILABS, Data-Core, Team Computers, RMSI, Micros IT Solutions, Fairmine Technologies, Tokyo Consulting Group and other enterprise learning communities.

Pan-India and Global Delivery

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

Coverage includes:

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

North India: Chandigarh, Mohali, Zirakpur, Rajpura, Jaipur, Jodhpur, Udaipur, Kota, Ajmer, Bikaner, Alwar, Bharatpur, Bhilwara, Pali, Sikar and Sri Ganganagar.

West and Central India: Mumbai, Navi Mumbai, Pune, Ahmedabad, Gandhinagar, Vadodara, Surat, Raipur, Nagpur and Goa.

South India: Bengaluru, Hyderabad, Chennai and Wayanad.

East India: Kolkata, Salt Lake, Durgapur, Asansol, Ranchi, Jamshedpur, Dhanbad, Bokaro, Bhubaneswar, Angul, Talcher and Rourkela.

International delivery: Dubai, Abu Dhabi, the wider UAE and global online audiences.

From Mumbai’s financial heartbeat and Bengaluru’s technology corridors to Hyderabad’s pharmaceutical strength, Kolkata’s enterprise heritage, Jaipur’s hospitality, Ahmedabad and Vadodara’s entrepreneurial energy, and the coal and steel belts that power Indian industry, each programme is adapted to the people and business realities of the region.

Comparison: Parikshit Khanna and Typical AI Training Programmes

Evaluation Area	Parikshit Khanna and Digital Training Jet	Typical General AI Training
Banking relevance	Credit, FP&A, compliance, customer service, insurance, portfolio and branch workflows	Generic prompts with limited financial context
Data security	Data classification, approved platforms, access controls, redaction and human review	Basic privacy warning without implementation guidance
Delivery style	Live building using realistic departmental scenarios	Lecture or demonstration-focused
Model coverage	Copilot, OpenAI GPT models, ChatGPT, Custom GPTs, Claude, Gemini, Gems and agents	Focus on a single public tool
Automation	n8n, Copilot agents, structured workflows and approval checkpoints	Simple content automation
Cross-sector understanding	Finance, healthcare, pharma, manufacturing, government, real estate, tourism, logistics and education	Narrow examples with limited industry connection
Leadership capability	CEO, CXO, VP, finance, risk, compliance and operational pathways	One programme for every participant
Indian context	Data protection, approval structures, regional operations and Viksit Bharat	Global examples with limited local adaptation
Outputs	Prompts, templates, reports, dashboards and implementation frameworks	Notes or certificates without usable workflows
Post-training direction	Adoption roadmap, use-case prioritisation and implementation guidance	Limited follow-through

Suggested Training Formats

Executive AI Briefing

A focused session for boards, CEOs, CXOs and senior leadership covering:

• Competitive implications

• Business-case prioritisation

• AI governance

• Data-security questions

• Model and vendor evaluation

• Adoption roadmap

• Risk controls

Full-Day BFSI Productivity Workshop

A hands-on programme for finance, risk, compliance, customer-service, operations and business teams.

Two-Day AI Implementation Programme

Day one develops prompting, research, reporting and analysis capability.

Day two focuses on agents, automation, dashboards, governance and team-level implementation plans.

Department-Specific Labs

Separate labs can be created for:

• Credit and underwriting

• Finance and FP&A

• Risk and compliance

• Insurance claims

• Wealth management

• Branch operations

• Customer experience

• Lead generation and CRM

• IT and automation

Frequently Asked Questions

Is this programme suitable for employees who have never used AI?

Yes. The training can begin with foundational concepts and progress toward advanced workflows without assuming prior technical knowledge.

Can the programme be customised for a bank or NBFC?

Yes. Scenarios can be developed around the organisation’s products, departments, policies, approved platforms and maturity level.

Will employees be asked to upload confidential data?

No. Training should use anonymised, synthetic, public or organisation-approved sample data.

Does the programme include Microsoft Copilot?

Yes. The workshop can cover Copilot Chat, Word, Excel, PowerPoint, Outlook, Teams, agents and supported model-selection options based on the organisation’s licences and admin settings.

Does Copilot include Claude and OpenAI technology?

Microsoft 365 Copilot provides OpenAI GPT models and supports selected Claude models in eligible environments. Claude availability depends on region, licensing, feature support and tenant-administrator configuration.

Does the training include ChatGPT and Custom GPTs?

Yes. ChatGPT, Custom GPTs, data analysis, research, reusable assistants and controlled connector workflows can be included.

Can coal, mining and industrial finance teams attend?

Yes. The programme can be customised for mine finance, contractor billing, procurement, inventory, maintenance costs, logistics, dispatch, tenders, compliance and management reporting.

Is AI allowed to make final credit, underwriting or compliance decisions?

AI can support research, documentation and analysis. Final consequential decisions should remain with authorised professionals operating under the organisation’s policies and applicable regulations.

Book AI Productivity Training for Your Team

AI productivity is not about replacing bankers, financial analysts, underwriters, relationship managers or compliance professionals.

It is about helping capable professionals spend less time searching, formatting, summarising and repeating administrative work, so they can spend more time exercising judgement, serving customers, managing risk and building trusted relationships.

Book Parikshit Khanna and Digital Training Jet for:

• Banking and NBFC AI workshops

• Insurance productivity programmes

• Finance and FP&A training

• CEO and CXO AI briefings

• Coal and mining finance workshops

• Lead-generation and CRM productivity sessions

• Microsoft Copilot enablement

• ChatGPT and Custom GPT training

• Claude and Gemini workshops

• Secure agentic AI and automation programmes

Official Email: parikshitkhanna@digitaltrainingjet.com

Phone: +91 9997213177 / +91 8076250669

Website https://www.parikshitkhanna.com/

Official Brands: Parikshit Khanna and Digital Training Jet

X: @ParikshitK_

Empowering India’s Financial Leaders for a Viksit Bharat

India’s banks, NBFCs, insurers, industrial organisations and financial institutions have the opportunity to build AI capability that is productive, secure, responsible and relevant to Indian realities.

The future will not belong to organisations that use the largest number of AI tools.

It will belong to organisations that know which tools to use, which data to protect, which outputs to verify and which decisions must always remain human.

Parikshit Khanna helps leadership teams turn that responsibility into practical capability.