Experiential Learning Program by E-Cell-1.pdf

Live projects

1. ELP Program
by E-Cell Bridging Talent with Real-World
Business Challenges

2. About
DBE & MBA
PROGRAM
The Department of Business Economics (DBE),
University of Delhi, is a premier institution known
for its strong foundation in economics, finance,
and analytics.

Established in 1973, DBE blends rigorous
academic training with real-world industry
exposure, equipping students with analytical
and strategic thinking skills. The department’s
flagship MBA (Business Economics) program
focuses strongly on developing future - ready
professionals capable of navigating the
evolving business landscape with data-driven
insights and economic foresight.
Our MBA program offers
dual specializations in:
Marketing + Finance: Equips students
to design go-to-market strategies with
a solid understanding of financial
feasibility and ROI.
Marketing + Analytics: Enables data-
driven campaign planning and
customer insights to optimize
marketing performance.
Finance + Analytics: Prepares students
to make informed financial decisions
through predictive modeling and
performance analysis.

3. What is ELP?
Experiencial Learning
Program
The ELP is a live project opportunity for companies to engage with
MBA students who work as consultants-in-training. Through short-
term, outcome-driven projects, our students help solve real
business problems across domains.
Duration: 4–6 weeks
Teams: 2–4 students per project
Delivery: Remote or Hybrid
Outcome: Actionable recommendations
+ final presentation/report
It’s a win-win: Companies get fresh solutions, and students gain hands-on experience.

4. Why Partner With Us?
Brand Your
Company On
Campus
Enhance your
employer brand
among future
hires through
visible
collaboration.
Reconnect
With Alumni
Roots
Your company
once shaped
our alumni —
now let us
return the
value through
this academic-
industry bridge.
Quick, High-
Impact
Results
Get quality
output in just
a few weeks —
perfect for
pilot studies,
exploratory
analysis, or
problem
backlogs.
Fresh, Data-
Backed
Insights
Students apply
classroom
knowledge in
strategy,
finance, and
analytics to
solve real
business cases.
Solve Business
Problems at
Zero Cost
Get smart,
motivated
minds to work
on your
pressing
business
challenges —
no hiring or
overhead.

5. Domains & Capabilities of
Our Students
Marketing + Finance
Campaign ROI &
budgeting
Market entry analysis
Channel sales
profitability
Consumer financing
strategies
Marketing + Analytics
Customer segmentation
Campaign performance
dashboards
A/B testing & digital
analytics
Web/social sentiment
analysis
Profitability models &
cost benchmarking
Fraud/anomaly
detection
Investment & risk
analysis
Predictive financial
modeling
Finance + Analytics
Tools used: Excel, Python, SQL, Power BI, Google Analytics, Tableau, SPSS

6. How the ELP Works:
Engagement Model
1
You provide a business
challenge or theme
2
We match a student
team based on domain fit
3
Feedback and certificate (if
applicable)
4
Weekly check-ins +
mentorship (optional)
Final report + presentation
of actionable solutions.
5
✔ Confidentiality assured
✔ NDA can be signed
✔ Zero administrative burden for you

7. Commerce
31.6%
Engineering
19.7%
Management
17.1%
Economics
17.1%
Science
11.8%
Others
2.6% Academic Background
STUDENT PROFILE
2 YEAR
ND
23.68%76.32%
Summer Internships

8. Timeline &
Expectations
You drive the problem statement — we deliver the solutions.
Preferred
Window: August–
November 2025
Project Length:
4–8 weeks
Time Commitment
from Students: ~8
hours/week
Company Input:
Only 1–2 check-ins
+ initial briefing

9. Manhar Sahil Vishu
Arcesium Moody’s HDFC Bank
1. Excel Model Automation: Built a
dynamic tool for automating
subscription/redemption entries,
reducing manual effort.
2. TRS Financing Analysis: Documented
reporting conventions & improved
process documentation.
3. Repo Process Optimization:
Enhanced trade reconciliation through
prime broker analysis.
Climate Stress Testing Automation:
Automated LGD stress testing for
AmBank (Malaysia), forecasting climate
scenario impacts (NZE, DNZ, NDC) on
property loans using R.
Data Science for Banking:
Developed a Python tool to auto-
calculate client net profit.
Built an AI-driven product
recommendation system & account
balance prediction with Streamlit &
Random Forest.
Hands-on with Cheque Clearing &
ENET ops.
Experiential Learning:
Student Projects at Leading
Financial Institutions