Agile Mumbai 2022 Keynote - Impact of Artificial Intelligence in Software Development Life Cycle Dr. Suresh A Shan Chairman - Computer Society of India (Mumbai Chapter) AI Thought Leader

1. AGILE MUMBAI 2022 CONFERENCE
Impact of AI Artificial Intelligence in
software development life cycle.
If you state first ,IT is Technical Feature...
if the end user finds & state’s first, then it is
Bug..,
A little bit about the Speaker
Dr. Suresh A Shan
AI thought Leader, III decades of MMFSS BFSI NBFC Tech Expert,
D.C Consultant, CDBDO – TRCIMPEX
Hon. Chairman Mumbai chapter- Computer Society of India -CSI

2. What is the AI Software Development life cycle?
•Requirements analysis;
•Design; Development;
•Testing; Deployment;
Save Time, Money Efforts,
Creator(developer), Corporate, Customer
Corporate Digital  Customer Digital

3. • Impact of AI Artificial Intelligence in software development life cycle.
• How artificial intelligence can improve software development process?
• #1 – Saves time with automated code generation
• #2 – Runs quick and efficient tests
• #3 – Generates unique software designs
• #4 – Enables rapid prototyping
• #5 – Automated project budgeting
• AI platforms
• Chat-bots
• Deep learning software
• Machine learning software
Developer working for startups or big organization as a fresher
makes huge difference using adopting applying technology.
• With an increasing demand for scalable, secure, and unique applications, there is
tremendous pressure on the developing community.
Impact of AI Artificial Intelligence in
software Design development life cycle.

4. How to design an Artificial Intelligent System.
• Concept development, solution discovery, and resource estimation to get
ready for your first AI system production
• AI capabilities like ML, NLP, expert systems, automation, vision, and
speech; A robust cloud infrastructure.
• Customer empathy; Experiments;
• The AI solution should be consisting of smaller components;
• Avoiding bias arising from wrong data.
• During this phase, you need to evaluate the various AI development
platforms, e.g.: Microsoft Azure AI Platform; Google Cloud AI Platform;
• IBM Watson AI platform; Big-ML; Infosys Nia.
• AI Bihar insurance claims ICU is missing
• AI Based gold loans and model patterns 360 view
•Microsoft Azure AI Platform; Google Cloud AI Platform;
•IBM Watson Developer platform; BigML; Infosys Nia resources.

5. Data Capture, The Model Has
Changed. Diwali apps sale using AI
• The Model of Generating/Consuming Data
Policy Process procedures has Changed
Old Model: Few companies are generating data, all others are consuming data
New Model: all of us are generating data, and all of us are
consuming data

6. Technologies & software professional's
differ & standardization across
In India E– Business is less to do with Electronics & more
& more to do with Emotions.
google maps &
Google earth

7. Technologies in policies for software
development from regulators –RBIH –REBIT
Awareness on IT Policies and process procedures
social web sites, mobility IOT security guidelines

8. Why AI Technology for software
development life cycle
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AI Technologies in process policies procedure implementation.

10. Technologies in policies implementation.
What is the difference between banking and NBFC financial services transactions systems.

11. Main Heading
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AI Technology – – Business benefits to Banks Financial services
AI based customer stories “ earn to pay model” cloud computing.

12. Generic Frame work
Host
Applications
Processing
Layer
ODS & DW

13. OLA /
Uber
Google
data

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Reserved
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Using Right Technology at Right Time
Rural India Financial Services
Impact of AI Artificial Intelligence in software
development life cycle in BFSI Sector

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DNA :- Create new Markets through Service culture Innovation.
DNA: BASICS – 3 B
Innovation: External & Internal users need solutions that
are new and different adopt to Rural in nature as BELIEF
Action: Take 100% responsibility with Integrity on our
commitments and execute them flawlessly as local our -
BEHAVOIR
Triumph – Sense of Accomplishment from every action,
every time resulting in Joy and Happiness for all like our
traditional festivals - BUSINESS
Pushing the boundaries of Minds and Machines If you want to break through look outside
your current environment. A key quality to have is to be authentic
About MMFSS – BITS - Innovations
Business Process Automation for Office Operations

16. Synopsis – What is the Belief base ? Why?
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17. Thesis – Belief Why ? How ? What?
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18. Thesis on Technology
Behavior Assumptions between Urban Rural Globally
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19. Synopsis – Belief  Behavior  Business
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Impact of AI Artificial Intelligence in software
development life cycle.
Project
powered by Geospatial

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Info on Map Pins - just by a click

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 Map Pins were used to express instant information's in abundant to the basic user,
 The maps pins had been designed uniquely for Mahindra Finance’s day to day activities,
These Pins are a state of art design, which gives the details of the customer category by
just visualizing the designed map Pin’s (details like Loan type , Loan product etc).
 Further for attaining all complete details all the branch team has to do was just to click on
the MAP PIN to view it (details like customer name, address, Location, Mobile no# etc).
 These map pins equips the branch team with all the required intelligence on the customer
profile like ..
(a) Loan Type => New , Refinance, Both,
(b) Customer Type => No OD cases (Green pins ),
OD Cases (Yellow pins ),
NPA cases (Red pins )
(c) Product Type => 2W – 2wheller, AS –Auto Sector etc,
(d) Count available => Customer counts were available below the map pin
Following figures will display the complete details of the same…
Innovative Map Pins

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Complete Product wise information..

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Navigation(Route ) was never been such easier before

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Pictographically – AI/BI Dash Board

30. AI Thoughts- case studies 001
7-B’s-Belief Behaviour Business Best Benefits BeE Bharat.
• AI Future online offline transactions. Differentiate
• AI Digital transformation. – corporate to customer
• AI HHD data capture climate update -
• AI base audit tracking
• AI base NOC issuance ( last mile )
• AI Vehicles financed in Jaipur seized in north east
• AI drivers life style when use vehicles and cost of living
• Mathematics – friends should be like no. 9 and not like no.8 – Gandhiji
• Astrology message for receipts
• Info-comm visual graphics – GJ SOMNATH temple / Sai baba shirdi – house
• RAMA KRISHNA bank & NBFC at rural India
• KARNA ARJUN entrepreneur blessed
• For women stand or sit & cook – avoid sisrein
• Cyber security compare with rural ritual goddess
•

31. Technology is neither good nor bad nor it is neutral.
It certainly cant be un-invented – The future & of

32. G
1-06-09 14:55
PROCESS
COMPLETED

33. Rice & Wheat – south & north Indian
respect Indians for excellence from AI

35. Indian AI Artificial Intelligence
understanding..
1. Explosion in unstructured text worldwide:-
2. Ambiguity & Variability of Language
Anything we say in the natural language can mean multiple things depending on the
context in which it is said, who is saying in it, who is listening it, how it’s being said,
and so on. That’s ambiguity.. The variability which we can express the same thing in
different ways, and these two together collude to make this process understanding
natural language so difficult.
3. Machine Learning to understand and interpret Unstructured data:- these are the
areas in India we are still struggling with.
The conventional way fails or falls, then we develop machine learning methods that
are sensitive to context- e learning – less of electronics more of emotions..
Challenges to scale AI solutions.
Adoption to structured from un – structured we have not done much yet..
Annotation today most of the information on supervision, all annotations are not
feasible and unrealistic..

36. Indian AI Artificial Intelligence
understanding..
Building Relevant & Required AI that lives and grows with available and affordable resource in
the real world and solve the problems what we have…, development on analytics tools
Build AI can scales and adopt… different environments beyond the vertical- (climate update ex)
Key challenges and building a sustainable model:- - Finding and retaining the talent.. Less
relevant resources available.
Sustainable revenue Methods and models. – applications of machine learning in E comerce (
auto door close speed printout – no customer requirement- astrology messages:-
IT should discover hidden patterns of data, and leverage the patterns to predict future data.
How AI and IOT, mobility ,Cloud, big data, blend in industrial financial channels build by
innovation opportunities.
The chatbot revolutions:- rise of the conversional user interface.
-Its an interface that enables users to complete a task through conversational interaction with a
machine or human.
-Conversational User Interface:- Ease of doing everything on ONE screen with the GUI and multi-
lingual . It is mostly used interface on the smart phone . Technology that feels or connect like a
friend.. - MMFSL use case on rural using multi-lingual chatbots
- the google play ML cloud ; the IBMs Watson;

41. Traditional business intelligence :-
:: analytics is optimizing decision making in situations of uncertainty
:: analytics is finding the optimal path to a desired future
:: analytics is not more data!
:: optimization means finding the best path among multiple options
:: and inferential statistics to forecast risk
:: stage two uses techniques such as predictive modeling
2. :: analytics stage two predicts the future
3. Analytics is data about the desired future

42. Largely felt where we can really leverage Artificial Intelligence.
•It improves overall team Performance , productive effective and efficient,
•Capture and enhance timely Customer communications with Build transparent Trust.
•Understand the happenings through all entities and capture all the Emotions.
•Ensure the customer Experience is a consistent on going activity.
•Use multi-lingual and Need connect to personalize the content and delivery.
•Market team should work upon the clarity on the branding vision, mission through campaigns.
•Convert as much as un-structured to structure using the components of people & Process.
•Get the Data captured in the systems are analyzed and used at his best.
•Bring the business customer predictions to engage the customer for his life long using content.
•Build the organizations with one voice one message with data based decision making.
•Do execute as much as research on the data to enhance the organization to the next level.
•Bring a professional transparent timely supported system to connect the customer 24/7.

43. Data Management for Analytics:
Five Best Practices
1.Simplify Access to Traditional and Emerging Data.
2.Strengthen the Data Scientist’s tools With
Advanced Analytic Techniques.
3.Scrub Data to Build Quality Into Existing Processes
4. Shape Data Using Flexible Manipulation
Techniques.
5.Share Metadata Across Data Management and
Analytics Domains.
6.Trusted Data, Proven Analytics

44. Data Management for Analytics:
Five Best Practices
1.Simplify Access to Traditional and Emerging Data.
2.Strengthen the Data Scientist’s tools With
Advanced Analytic Techniques.
3.Scrub Data to Build Quality Into Existing Processes
4. Shape Data Using Flexible Manipulation
Techniques.
5.Share Metadata Across Data Management and
Analytics Domains.
6.Trusted Data, Proven Analytics