MuleShield Advanced API

Overview

The MuleShield API is designed to enhance the security and integrity of banking institutions by identifying potential mule accounts. Mule accounts are used by fraudsters to facilitate illegal activities, often resulting in substantial financial losses and reputational damage for banks. The MuleShield API leverages advanced data enrichment techniques to analyze a wide range of customer data, providing a comprehensive solution for detecting these accounts.

This API has one endpoint:

signzy.app/api/v3/muleshield-advanced-score: The API takes eleven inputs, that are phone number, name, email ID, PAN, Pincode, IP Address etc as a record to search and validate whether this record corresponds to a fraud account or not.

API Description

API cURL

curl --location 'https://api-preproduction.signzy.app/api/v3/muleshield-advanced-score' \
--header 'Authorization:' \
--header 'Content-Type: application/json' \
--data-raw '{
    "phoneNumber": "",
    "name": "",
    "pan": "",
    "email": "",
    "pincode": "",
    "ipAddress": "",
    "strictness": "",
    "dob": "",
    "gender": "",
    "demographicScore": "",
    "pdfReport":""
}'

Input Table

Parameter Name	Required	Type	Description / Constraints
phoneNumber	Yes	String	The user's phone number.
name	Yes	String	The user's full name.
pan	No	String	Permanent Account Number (PAN) for identity verification.
email	No	String	The user's email address.
pincode	No	String	Pincode for location.
ipAddress	No	String	The IP address from which the request originated.
strictness	No	String	Defines the validation level for data matching. Must be one of: all, strict, moderate, lenient.
dob	No	String	Date of Birth (DOB). Format (dd/mm/yyyy)
gender	No	String	The user's gender. Must be one of: male, female.
demographicScore	No	String	Defines whether to include a demographic score. Must be one of: all, true, false.
pdfReport	No	String	Defines whether to generate a PDF report. Must be one of: true, false.
version	No	String	The API version to use for the request. Must be one of v3.0, v3.1, latest
onboardingDate	No	String	The date the user was onboarded.Format -dd/mm/yyyy

Note: Strictness parameter will be used to set the strictness for the calculating the score.

API Output

{
    "result": {
        "trustScore": {
            "strict": {
                "score": "",
                "riskCategory": "",
                "nameMatch": "",
                "age": ""
            },
            "moderate": {
                "score": "",
                "riskCategory": "",
                "nameMatch": "",
                "age": ""
            },
            "lenient": {
                "score": "",
                "riskCategory": "",
                "nameMatch": "",
                "age": ""
            }
        },
        "cyberCrimeCheck": {
            "impact": "",
            "phoneNumber": "",
            "email": ""
        },
        "cyberFraudCheck": {
            "impact": "",
            "isSuspected": "",
            "reportingDate": "",
            "reportingEntity": "",
            "totalNoCount": ""
        },
        "epfo": {
            "impact": "",
            "uan": "",
            "establishmentName": "",
            "isEmployed": "",
            "name": "",
            "dateOfBirth": "",
            "gender": "",
            "dateOfJoining": "",
            "dateOfExit": ""
        },
        "pan": {
            "impact": "",
            "panAllotmentDate": "",
            "panAllotmentAge": "",
            "panStatus": "",
            "name": "",
            "number": "",
            "firstName": "",
            "middleName": "",
            "lastName": "",
            "typeOfHolder": "",
            "gender": "",
            "isIndividual": "",
            "category": "",
            "dateOfBirth": "",
            "maskedAadhaarNumber": "",
            "aadhaarLinked": ""
        },
        "digitalIdentityDetails": {
            "impact": "",
            "digitalIdentityScore": "",
            "samePhoneNameCount": "",
            "diffPhoneNameCount": "",
            "totalPhoneNameCount": "",
            "sameEmailNameCount": "",
            "diffEmailNameCount": "",
            "totalEmailNameCount": "",
            "morePhonesMappedWithEmail": "",
            "moreEmailsMappedWithPhone": "",
            "digitalFootprint": "",
            "fintechCount": "",
            "ageBand": "",
            "gender": "",
            "firstNameMatch": "",
            "lastNameMatch": "",
            "phoneFirstSeenYear": "",
            "emailFirstSeenYear": "",
            "phoneEmailMatch": "",
            "phoneEmailFirstSeenYear": "",
            "phoneEmailLastSeenYear": "",
            "phoneNameFirstSeenYear": "",
            "phoneNameLastSeenYear": "",
            "emailNameFirstSeenYear": "",
            "emailNameLastSeenYear": ""
        },
        "financeDetails": {
            "impact": "",
            "dmatAccount": "",
            "hasMutualFund": "",
            "hasCreditCard": "",
            "occupation": "",
            "businessOwner": ""
        },
        "phoneDetails": {
            "impact": "",
            "customerName": "",
            "isValid": "",
            "connectionType": "",
            "currentServiceProvider": "",
            "originalServiceProvider": "",
            "networkRegion": "",
            "phoneDeactivatedDays": "",
            "phoneDeactivationCount": "",
            "phoneDisposable": "",
            "phoneTenure": {
                "min": "",
                "max": ""
            },
            "isPorted": ""
        },
        "phoneFootprint": {
            "impact": "",
            "registeredProfiles": "",
            "toi": "",
            "gaana": "",
            "oyoRooms": "",
            "noBroker": "",
            "instagram": "",
            "microsoft": "",
            "housing": "",
            "flipkart": "",
            "altBalaji": "",
            "facebook": "",
            "twitter": "",
            "shaadi": "",
            "digiLocker": "",
            "irctc": "",
            "samsung": "",
            "indaneGas": "",
            "timesPrime": "",
            "jeevanSathi": "",
            "indianExpress": "",
            "swiggy": "",
            "whatsApp": "",
            "linkedIn": "",
            "policyBazar": "",
            "byju": "",
            "zee5": ""
        },
        "emailDetails": {
            "impact": "",
            "status": "",
            "freeEmail": "",
            "subStatus": "",
            "domain": "",
            "domainAgeDays": "",
            "smtpProvider": "",
            "emailTenure": "",
            "emailBreach": []
        },
        "emailFootprint": {
            "impact": "",
            "registeredProfiles": "",
            "gaana": "",
            "scripbox": "",
            "adobe": "",
            "trivago": "",
            "housing": "",
            "flipkart": "",
            "jeevanSathi": "",
            "microsoft": "",
            "github": "",
            "freelancer": "",
            "shaadi": "",
            "tumblr": "",
            "firefox": "",
            "twitter": "",
            "quora": "",
            "spotify": "",
            "eventBrite": "",
            "bitmoji": "",
            "wordpress": "",
            "snapdeal": "",
            "codeAcademy": "",
            "apple": "",
            "vimeo": "",
            "pinterest": "",
            "flickr": "",
            "instagram": "",
            "facebook": "",
            "linkedIn": "",
            "patreon": "",
            "envato": ""
        },
        "pincode": {
            "impact": "",
            "blacklisted": "",
            "phonePincodeFirstSeenDays": "",
            "phonePincodeLastSeenDays": "",
            "phonePincodeMatchCount": "",
            "phoneUniquePincodesCount": "",
            "emailPincodeFirstSeenDays": "",
            "emailPincodeLastSeenDays": "",
            "emailPincodeMatchCount": "",
            "emailUniquePincodesCount": ""
        },
        "ipBlacklist": {
            "impact": "",
            "isHijacked": "",
            "isSpider": "",
            "isTor": "",
            "isDshield": "",
            "isVpn": "",
            "isSpyware": "",
            "isSpamBot": "",
            "isBot": "",
            "isListed": "",
            "isProxy": "",
            "isMalware": "",
            "isExploitBot": "",
            "blocklists": [],
            "listCount": "",
            "sensors": [],
            "city": "",
            "regionCode": "",
            "region": "",
            "country": "",
            "latitude": "",
            "longitude": ""
        },
        "summary": {
            
        },
        "mnrlCheck": {
            "impact": "NA",
            "tsp": "",
            "disconnectionReason": "",
            "dateOfDisconnection": "",
            "incorporationDate": "",
            "mobileNo": "",
            "lsa": "",
            "dateOfReactivation": "",
            "reactivationReason": "",
            "deactivatedDays": ""
        },
        "friCheck": {
            "impact": "NA",
            "mobileNo": "",
            "status": "",
            "reason": "",
            "dateFlagged": "",
            "lsa": "",
            "tspName": "",
            "sensitivityIndex": ""
        },
        "apiStatuses": {
            "getBasicEmploymentVerification": "FAILURE",
            "digitalIdentityScore": "SUCCESS",
            "getPhoneKycDetails": "SUCCESS",
            "getEmailValidation": "SUCCESS",
            "digitalIntegrity": "NOT_APPLICABLE",
            "panExtensive": "SUCCESS",
            "compliance206IndividualSearch": "SUCCESS",
            "emailSocial": "SUCCESS",
            "phoneSocial": "SUCCESS",
            "phoneToPan": "SUCCESS",
            "emailBreach": "FAILURE",
            "pincodeToPopulation": "NOT_APPLICABLE",
            "cyberCrimeRecords": "SUCCESS",
            "cyberFraudRecords": "FAILURE",
            "mnrlCheck": "SUCCESS"
        }
    }
}

Output Table

Field Name	Sub Field	Type	Description
result		Object	The root object containing all verification checks and scores.
trustScore		Object	Contains trust scores calculated under different strictness levels.
	strict	Object	Trust score details under a strict evaluation criteria.
	score	String	Numerical score indicating trust level under strict criteria.
	riskCategory	String	Categorization of risk based on the strict trust score.
	nameMatch	String	Score or indicator of how well the provided name matches other records.
	age	String	Calculated age derived from the data under strict criteria.
	moderate	Object	Trust score details under a moderate evaluation criteria.
	score	String	Numerical score indicating trust level under moderate criteria.
	riskCategory	String	Categorization of risk based on the moderate trust score.
	nameMatch	String	Score or indicator of how well the provided name matches other records.
	age	String	Calculated age derived from the data under moderate criteria.
	lenient	Object	Trust score details under a lenient evaluation criteria.
	score	String	Numerical score indicating trust level under lenient criteria.
	riskCategory	String	Categorization of risk based on the lenient trust score.
	nameMatch	String	Score or indicator of how well the provided name matches other records.
	age	String	Calculated age derived from the data under lenient criteria.
cyberCrimeCheck		Object	Details of checks against cyber crime records.
	impact	String	Overall impact/finding from the cyber crime check.
	phoneNumber	String	Result of phone number check in cybercrime databases.
	email	String	Result of email check in cybercrime databases.
cyberFraudCheck		Object	Details of checks against cyber fraud records.
	impact	String	Overall impact/finding from the cyber fraud check.
	isSuspected	String	Indicates if the entity is suspected of fraud.
	reportingDate	String	Date the fraud was reported.
	reportingEntity	String	Entity that reported the fraud.
	totalNoCount	String	Total number of negative fraud counts associated.
epfo		Object	Employment details verified via Employees' Provident Fund Organisation (EPFO).
	impact	String	Overall impact/finding from the EPFO check.
	uan	String	Universal Account Number (UAN) associated.
	establishmentName	String	Name of the employer/establishment.
	isEmployed	String	Indicates if the individual is currently employed/active.
	name	String	Name verified via EPFO.
	dateOfBirth	String	Date of birth verified via EPFO.
	gender	String	Gender verified via EPFO.
	dateOfJoining	String	Date of joining the establishment.
	dateOfExit	String	Date of exiting the establishment.
pan		Object	Details verified via Permanent Account Number (PAN) records.
	impact	String	Overall impact/finding from the PAN check.
	panAllotmentDate	String	Date the PAN was allotted.
	panAllotmentAge	String	Age of the PAN record.
	panStatus	String	Status of the PAN (e.g., 'Valid', 'Inactive').
	name	String	Full name on PAN record.
	number	String	The verified PAN number.
	firstName	String	First name on PAN record.
	middleName	String	Middle name on PAN record.
	lastName	String	Last name on PAN record.
	typeOfHolder	String	Type of holder (e.g., 'Individual').
	gender	String	Gender on PAN record.
	isIndividual	String	Indicates if the holder is an individual.
	category	String	Category of the PAN holder.
	dateOfBirth	String	Date of Birth on PAN record.
	maskedAadhaarNumber	String	Masked Aadhaar number linked to PAN.
	aadhaarLinked	String	Indicates if the PAN is linked to Aadhaar.
digitalIdentityDetails		Object	Information about the user's overall digital footprint and identity.
	impact	String	Overall impact of digital identity findings.
	digitalIdentityScore	String	Calculated digital identity score.
	samePhoneNameCount	String	Count of same names mapped to phone.
	diffPhoneNameCount	String	Count of different names mapped to phone.
	totalPhoneNameCount	String	Total count of names mapped to phone.
	sameEmailNameCount	String	Count of same names mapped to email.
	diffEmailNameCount	String	Count of different names mapped to email.
	totalEmailNameCount	String	Total count of names mapped to email.
	morePhonesMappedWithEmail	String	Indicates if multiple phones map to the email.
	moreEmailsMappedWithPhone	String	Indicates if multiple emails map to the phone.
	digitalFootprint	String	Summary of the digital services found.
	fintechCount	String	Number of Fintech services associated.
	ageBand	String	Inferred age band (e.g., '30-40').
	gender	String	Inferred gender.
	firstNameMatch	String	Match status for first name.
	lastNameMatch	String	Match status for last name.
	phoneFirstSeenYear	String	Year phone was first seen digitally.
	emailFirstSeenYear	String	Year email was first seen digitally.
	phoneEmailMatch	String	Indicates if phone and email are digitally linked.
	phoneEmailFirstSeenYear	String	Year phone-email match was first seen.
	phoneEmailLastSeenYear	String	Year phone-email match was last seen.
	phoneNameFirstSeenYear	String	Year phone-name match was first seen.
	phoneNameLastSeenYear	String	Year phone-name match was last seen.
	emailNameFirstSeenYear	String	Year email-name match was first seen.
	emailNameLastSeenYear	String	Year email-name match was last seen.
financeDetails		Object	Inferred financial attributes of the user.
	impact	String	Overall impact of finance findings.
	dmatAccount	String	Indicates presence of a Demat account.
	hasMutualFund	String	Indicates presence of Mutual Fund activity.
	hasCreditCard	String	Indicates presence of Credit Card use.
	occupation	String	The inferred occupation.
	businessOwner	String	Indicates if the person is inferred to be a business owner.
phoneDetails		Object	Detailed checks on the provided phone number.
	impact	String	Overall impact of phone details check.
	customerName	String	Name associated with the phone number.
	isValid	String	Validity status of the phone number.
	connectionType	String	Type of connection (e.g., 'Mobile', 'Landline').
	currentServiceProvider	String	Current network operator.
	originalServiceProvider	String	Original network operator.
	networkRegion	String	Geographical region of the network.
	phoneDeactivatedDays	String	Days since phone was deactivated (if applicable).
	phoneDeactivationCount	String	Count of deactivation events.
	phoneDisposable	String	Indicates if it's a disposable/burner phone.
	phoneTenure	Object	Range of inferred tenure for the phone number.
	min	String	Minimum inferred tenure.
	max	String	Maximum inferred tenure.
	isPorted	String	Indicates if the number was ported.
phoneFootprint		Object	Indicates presence of the phone number on various services/websites.
	impact	String	Overall impact of phone footprint findings.
	registeredProfiles	String	Total number of services the phone is registered with.
	toi	String	Presence on The Times of India.
	gaana	String	Presence on Gaana.
	oyoRooms	String	Presence on OYO Rooms.
	noBroker	String	Presence on NoBroker.
	instagram	String	Presence on Instagram.
	microsoft	String	Presence on Microsoft services.
	housing	String	Presence on Housing.com.
	flipkart	String	Presence on Flipkart.
	altBalaji	String	Presence on AltBalaji.
	facebook	String	Presence on Facebook.
	twitter	String	Presence on Twitter.
	shaadi	String	Presence on Shaadi.com.
	digiLocker	String	Presence on DigiLocker.
	irctc	String	Presence on IRCTC.
	samsung	String	Presence on Samsung services.
	indaneGas	String	Presence on Indane Gas services.
	timesPrime	String	Presence on Times Prime.
	jeevanSathi	String	Presence on JeevanSathi.
	indianExpress	String	Presence on Indian Express.
	swiggy	String	Presence on Swiggy.
	whatsApp	String	Presence on WhatsApp.
	linkedIn	String	Presence on LinkedIn.
	policyBazar	String	Presence on Policybazaar.
	byju	String	Presence on Byju's.
	zee5	String	Presence on ZEE5.
emailDetails		Object	Detailed checks on the provided email address.
	impact	String	Overall impact of email details check.
	status	String	Status of the email (e.g., 'Deliverable').
	freeEmail	String	Indicates if it's a free email domain (e.g., Gmail).
	subStatus	String	Detailed sub-status of the email.
	domain	String	Email domain name.
	domainAgeDays	String	Age of the email domain in days.
	smtpProvider	String	SMTP service provider.
	emailTenure	String	Inferred email tenure.
	emailBreach	Array	List of data breaches the email was found in.
emailFootprint		Object	Indicates presence of the email address on various services/websites.
	impact	String	Overall impact of email footprint findings.
	registeredProfiles	String	Total services email is registered with.
	gaana	String	Presence on Gaana.
	scripbox	String	Presence on Scripbox.
	adobe	String	Presence on Adobe.
	trivago	String	Presence on Trivago.
	housing	String	Presence on Housing.com.
	flipkart	String	Presence on Flipkart.
	jeevanSathi	String	Presence on JeevanSathi.
	microsoft	String	Presence on Microsoft services.
	github	String	Presence on GitHub.
	freelancer	String	Presence on Freelancer.
	shaadi	String	Presence on Shaadi.com.
	tumblr	String	Presence on Tumblr.
	firefox	String	Presence on Firefox.
	twitter	String	Presence on Twitter.
	quora	String	Presence on Quora.
	spotify	String	Presence on Spotify.
	eventBrite	String	Presence on EventBrite.
	bitmoji	String	Presence on Bitmoji.
	wordpress	String	Presence on WordPress.
	snapdeal	String	Presence on Snapdeal.
	codeAcademy	String	Presence on Code Academy.
	apple	String	Presence on Apple services.
	vimeo	String	Presence on Vimeo.
	pinterest	String	Presence on Pinterest.
	flickr	String	Presence on Flickr.
	instagram	String	Presence on Instagram.
	facebook	String	Presence on Facebook.
	linkedIn	String	Presence on LinkedIn.
	patreon	String	Presence on Patreon.
	envato	String	Presence on Envato.
pincode		Object	Pincode (postal code) association and risk details.
	impact	String	Overall impact of pincode findings.
	blacklisted	String	Indicates if the pincode is blacklisted for fraud.
	phonePincodeFirstSeenDays	String	Days since phone/pincode association first seen.
	phonePincodeLastSeenDays	String	Days since phone/pincode association last seen.
	phonePincodeMatchCount	String	Count of phone/pincode matches.
	phoneUniquePincodesCount	String	Count of unique pincodes associated with the phone.
	emailPincodeFirstSeenDays	String	Days since email/pincode association first seen.
	emailPincodeLastSeenDays	String	Days since email/pincode association last seen.
	emailPincodeMatchCount	String	Count of email/pincode matches.
	emailUniquePincodesCount	String	Count of unique pincodes associated with the email.
ipBlacklist		Object	Details of checks performed on the IP address.
	impact	String	Overall impact of IP blacklist check.
	isHijacked	String	Indicates if the IP is hijacked.
	isSpider	String	Indicates if the IP is a search engine spider.
	isTor	String	Indicates if the IP is a Tor exit node.
	isDshield	String	Indicates if the IP is on the DShield list.
	isVpn	String	Indicates if the IP is a VPN.
	isSpyware	String	Indicates if the IP is associated with spyware.
	isSpamBot	String	Indicates if the IP is a spam bot.
	isBot	String	Indicates if the IP is a bot.
	isListed	String	Indicates if the IP is on any blacklist.
	isProxy	String	Indicates if the IP is a proxy server.
	isMalware	String	Indicates if the IP is associated with malware.
	isExploitBot	String	Indicates if the IP is an exploit bot.
	blocklists	Array	List of specific blocklists found on.
	listCount	String	Total number of blocklists found on.
	sensors	Array	List of sensors that detected the IP.
	city	String	Geo-located city of the IP.
	regionCode	String	Geo-located region code.
	region	String	Geo-located region/state.
	country	String	Geo-located country.
	latitude	String	Geo-located latitude.
	longitude	String	Geo-located longitude.
summary		Object	Placeholder for summary or meta-data.
mnrlCheck	—	Object	Mobile Number Revocation List (TRAI/DoT) check result. Present only on latest. Negative-only impact, can reduce the trust score, never add.
mnrlCheck	impact	String	Derived flag. Negative if the phone is found on MNRL
mnrlCheck	tsp	String	Telecom Service Provider that held the mobile number at the time of disconnection.
mnrlCheck	disconnectionReason	String	Reason the number was disconnected/revoked (e.g. fraud-related disconnection, non-usage), as reported in the MNRL registry.
mnrlCheck	dateOfDisconnection	String	Date on which the mobile number was disconnected by the TSP.
mnrlCheck	incorporationDate	String	Date the number was incorporated (listed) into the MNRL registry.
mnrlCheck	mobileNo	String	The mobile number found in the MNRL registry (echo of the queried number).
mnrlCheck	lsa	String	Licensed Service Area (telecom circle) of the mobile number.
mnrlCheck	dateOfReactivation	String	Date the number was reactivated after disconnection, if it has been reissued.
mnrlCheck	reactivationReason	String	Reason for reactivation (e.g. reactivated to the same customer, reissued to a new customer).
mnrlCheck	deactivatedDays	String	Number of days the mobile number remained deactivated before reactivation.
friCheck	—	Object	Financial fraud Risk Indicator (DoT) check result. Present only on latest.
friCheck	impact	String	Derived flag. Negative if the phone is flagged in the FRI registry with data, else NA.
friCheck	mobileNo	String	The mobile number flagged in the FRI registry.
friCheck	status	String	Current FRI status of the mobile number in the registry.
friCheck	reason	String	Reason the number was flagged as a fraud risk.
friCheck	dateFlagged	String	Date on which the number was flagged in the FRI registry.
friCheck	lsa	String	Licensed Service Area (telecom circle) of the flagged number.
friCheck	tspName	String	Telecom Service Provider currently serving the flagged number.
friCheck	sensitivityIndex	String	Fraud-risk sensitivity grading assigned by the registry (e.g. Low / Medium / High).
apiStatuses	—	Object	Status of each API used. Each entry in apiStatuses can be "SUCCESS" (if successful), "FAILURE" (if failed) or "NOT_APPLICABLE" (if not used).

Mule Scores

Score Range	Risk Category	Description
Greater than 750	Very Low Risk	Entities that pose minimal or no risk based on the evaluation criteria.
501 - 750	Low Risk	Entities with some risk, but generally acceptable with standard due diligence.
301 - 500	Moderate Risk	Entities with noticeable risk, requiring enhanced due diligence and monitoring.
Less than 300	High Risk	Entities with high risk, necessitating stringent monitoring and comprehensive mitigation measures.

Status Codes

Code	status	Description
200	Success	The request id was successfully generated.
404	Data not found	No record was found
409	Upstream Error	Usptream down, please try again
400	Bad request	Error in input parameters
500	Internal Server Error	Internal Server Error Please contact support

FAQ How is the final score determined? The score is calculated using a dual-factor evaluation methodology. First, the profile is assigned a score based on its positive attributes. Then, points are deducted for any negative indicators. For example, if a user scores 700 points but has certain negative traits—such as using a disposable email address or having a low digital presence—the overall score will be reduced accordingly. The final score reflects these adjustments, with each parameter contributing according to its assigned weight. What is the impact parameter? The impact parameter for each check indicates how much that particular check influences the overall score. If the impact is negative, it means that some negative flags have been found, resulting in a reduction of the score. What is the strictness parameter? The strictness parameter controls how strictly negative scores are applied. If set to "strict," 100% of the negative score for that particular check is deducted. If set to "moderate," this percentage is reduced, and it is reduced further for "lenient." What is demographic logic? Demographic logic is used to calculate the trust score using demographic parameters such as date of birth, gender, and pincode. This helps segment users into different categories and define the ideal user behavior for each category. The strictness logic is then applied on top of this, following the same principles. This approach makes our solution adaptable for users in tier 2 cities and below. Can the weightage of parameters be adjusted? Yes, the weightage assigned to each parameter, along with the risk categories, can be adjusted to meet specific requirements. These adjustments are typically based on the bank's Target Group (TG) or insights gained from a Proof of Concept (POC) analysis. Customizing the weightages allows institutions to fine-tune the scoring model to align with their specific risk tolerance and operational needs. How should this score be used? The Trustscore should be used during the onboarding process of new customers to assess their risk of being involved in money mule activities. If a user is categorized as high risk, the bank should perform additional due diligence. This may involve conducting manual verifications, seeking additional documentation, or escalating the case to a specialized queue for further screening. By incorporating this score into the onboarding process, banks can mitigate potential risks and ensure compliance with anti-fraud and anti-money laundering regulations. Are any assumptions considered while generating the score? Yes, one key assumption is made: all the provided information belongs to a single individual and represents their primary, authentic details. This assumption is crucial for the integrity of the analysis, as inaccuracies in input data can impact the validity of the generated Trustscore. What happens if a check fails to return an output? If an API or parameter check fails to provide an output, the corresponding impact parameter for that check is marked as "NA" (not applicable). The AI/ML model compensates for this by redistributing the weightages across the other successfully retrieved parameters. This ensures that the final score remains valid even if some data points are unavailable, albeit with a slightly reduced level of granularity.

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