1. Computer vision and biometric technology in credit risk
User experience

2. Result
Biometric solutions for financial institutions will become the fastest growing market segment in 2014 – 2019 according to research of Transparency Market Research

3. SAFI as a part of Credit Factory (anti-fraud)
Front-office
Application processing
Front-office
Minimum requirements/Visual check
Automated systems
Underwriter
New Application
Client notification
Graphics files processing
Automatic system Photoalbum
Automated processing
Manual processing
AS SAFI
AS ODR
Portrait review
There is no generic system for fraud prevention: there should be unique approach for each type of fraud (credit history manipulation, forgery, internal fraud, etc.).
There is no such mathematical model that could stop fraudsters if they have gained access to personal data of good customer (passport details, social security number, etc.).

4. System diagram Disadvantages of the approach:
Current level of biometric systems (based on facial recognition) does not allow to solve the problem of fraud straight forward, comparing every new client to the whole database.
Segmentation of customer database and using information from credit systems and stop-lists in application processing helped to resolve this issue.
Disadvantages of the approach:
high quality of IT infrastructure (complex integration)
Well established business processes
Advantages of the approach :
Raising efficiency of security officers because of their interaction with analytics (decision science) team.

5. SAFI business rules: STOP-LIST
SAFI rule: match with a stop-list
underwriter indicated document forgery
as a result criminal case was opened against fraudster.

6. Case «STOP-LIST»: in details
application date
credit issued
result of investigation: fake passport. Client has been added to the stop-list
application date
application rejected
reject reason: fraud detection
Fake
Fake
Violations in application processing:
visual check – positive results
fake passport was checked by special technical equipment – passed check.
fraud was prevented only by SAFI
Original

7. Arbitrary image search – a powerful tool for investigations
Arbitrary image search provides security officer with unique opportunities for investigations

8. Case «Search for an arbitrary image»: in details
Additional information on the number of visits of fraudsters to the Bank *
application date , credit was not issued. Reject reason: decision of fraud detection model
Application date , credit was not issued . Reject reason: decision of the underwriter
… from account in social network
* information attached to criminal case

9. SAFI business rule: current photo does not match previous photo
SAFI rule: current photo does not match previous photo
according to investigation results, criminal was detained.
criminal case was opened against fraudster.

10. Case «Current photo does not match previous photo»: details
application date
credit was not issued. Reject reason scoring
Application was found using the tool «search on the arbitrary image»
After application rejection, customer decided to get money in illegal way
application date
fraudsters used lost passport of Sberbank client
application date
photo and passport of Sberbank client
Fake
Original

11. Forgery detection: criminalistics examination of photo
If the underwriters cannot make an expert decision about fraud, materials are transferred to security officers and the problem was solved with use of specialized software «Portrait Expertise»
Case details:
underwriter has noticed the discrepancy in client`s appearance and client`s age
using special software security officer has detected a face mismatch
trying to cheat Bank`s system fraudster used the makeup and wig

12. SAFI business rule: New Customer Reducing operational risk
SAFI rule: New customer`s matches another customer`s photo who looks like new cutsomer
20 cases are of wrongly attached documents and several hundred of typos in client`s name are fixed daily.