In Banking & Lending sector AI has played vital role in transforming the way Banking & lending sector works. The most important factor is to enable the seamless customer experience by enhancing the business processes with low cost. AI & ML has made it easier for customers to interact with Banking without any problem. Looking to implement AI in your banking & lending businesses, write to layak@artivatic.ai

1. Financial Advisory
Financial Intelligence from Multiple Accounts
Persona Scenario
Alex is 25. He has good job
and so got many accounts,
investments. He needs to
asses his financials.
He gets introduced to financial advisory
system with Bank X. He immediately logins
himself and attach all accounts. He gets all
necessary critical advise for his financials –
investment, spending, saving etc.
Process Flow Steps
Mutual fund, credit,
debit, demit, trading,
insurance & Bank
accounts of other
institutions can be
logged in and data
will be gathered to
Bank X.
Source of transaction,
amount, data is
identified while
segregating in to
investment, insurance,
expenses, saving,
income and more.
Alex logins to Bank’s
Account and
authorize other
financial institution
in same place
Aggregation of all
accounts is analysed
with use of in-house
algorithms &
Machine Learning
Engine.
Types of activities are
recorded. Anomalies &
Fraud is identified. Asset
value is built over period
of time. Asset
evaluation is then done
based on intelligent data
generated.
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Self serviced – Real
Time intelligent
analysis
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Simple, Frictionless and
in-depth financial
profiling & cross selling
ML based predictive
financial behavioural
insights
Key takeaways
Alex’s financial
intelligence advisory
system is prepared
where all advises on
savings, income,
expenditure &
investment if provided.
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Intelligent
financial analysis
for wealth
management, risk
& in-depth
financial behavior
prediction .
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2. Documents & Photo Fraud
Computer Vision & NLP based documents, photo Validation
Persona Scenario
Applicants in Bank, uploads
many documents with photos
or while sending video person.
Matching documents & photo
is complex and tidy job.
Banks find it operationally challenge to
validate all data & photo manually. This
causes lots of time & costs and also
increases chances of error resulting in to
fraud.
Process Flow Steps
System then gets
train with Bank’s
existing documents,
photos of the
applicants stored on
the central data
server. Accuracy is
monitored.
In real time, all
documents are
validated, cross
checked. Photos in all
documents are also
validated using
technology.
Computer Vision
SDK/API gets
integrated with
Bank’s processes
while uploading
documents or taking
photo/video online.
New applicant’s for
loan, accounts,
credit card etc.
uploads documents,
photos, videos on
the Bank’s
platform/app.
Photo in documents also
matched to the online
video shooting while
applying and
creditability score is
generated for Bank’s to
make fraud check
easier.
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4
Technology
empowered digital
experience.
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Enables Bank in
reducing processing
time
Future ready fraud
detection system with
computer vision & NLP
Key takeaways
Bank’s operation team
do not need to spend
time & money for
manual check,
validate. This helps in
reducing fraud, error
and automating the
process much faster.
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Reducing time &
costs for
processing.
Reduces fraud &
risks with 0%
errors.
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3. Consumer Credit Risk Scoring
Digital, Interaction & Historical Data based Risk scoring & Prediction
Persona Scenario
More than 50% of the
consumer who apply to bank
do not have right data points
for risk scoring & personalized
predictions.
Consumers while applying to Bank has lack
of data points, past history and so bank find
it difficult to provide right credit, product,
services and enable for real time banking
interactions.
Process Flow Steps
Past historical data is
analyzed from Bank’s
database and
anonyms patterns
are built. These
patterns are mixed
with new consumer’s
data & patterns.
Predictive insights are
generated to map the
futuristic goals of the
consumer for financial
outcome &
personalized offerings.
In-depth technology
platform as API/SDK
gets integrated to the
Bank’s platform and
data capturing starts
in real time from
digital prescience,
KYC & interaction.
New insights are
generated form
multiple data sources
in real time to build in-
depth consumer
profiling, risk scoring,
interest & financial
sentiment.
Credit risk scoring is
derived from multiple
insights, data, super-
imposition, behavioral
analysis & fraud analysis
for predictive credit,
products, personalized
finance & wealth.
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4
Intelligent & real time
platform to asses
consumers
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Predicting social,
financial, interest,
credibility level
Real time consumer
profiling for automated
decision making
Key takeaways
This entire product
enables Bank to asses
consumer in real time with
alternative data sources to
build in-depth consumer
profiling, credit scoring,
fraud detection to increase
ROI & quick decisions.
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Intelligent risk &
credit scoring in
real time.
Multiple sources
data focused
fraud, prediction
& consumer
profiling.
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