INTERAGO AS

Facts

Source: Firmafakta, with business data from public registers.

organisasjonsnummer:

913185412

navn:

INTERAGO AS

organisasjonsform:

kode:

AS

beskrivelse:

Aksjeselskap

naeringskode1:

kode:

62.200

beskrivelse:

Konsulentvirksomhet tilknyttet informasjonsteknologi og forvaltning og drift av it-systemer

antallAnsatte:

25

hjemmeside:

www.interago.no

epostadresse:

post@interago.no

telefon:

not reported by source

forretningsadresse:

adresse:

Innspurten 13A

poststed:

OSLO

postnummer:

0663

kommune:

OSLO

stiftelsesdato:

2014-01-27

registreringsdatoenhetsregisteret:

2014-02-06

aktivitet:

Informasjons- og kommunikasjonstjenester.

vedtektsfestetFormaal:

Salg av rådgivnings- og konsulenttjenester innen områdene Business, Intelligence og Information Management, herunder applikasjonsutvikling, og IT-teknisk rådgivning, medvirke i andre selskap som tilbyr det, samme, samt å forvalte selskapets verdier gjennom investeringer eller, annet som anses formålstjenlig.

View the address in Geonorge

Board and other roles

Source: Firmafakta. Also see the separate Brønnøysund lookup under related lookups.

Daglig leder

• Daglig leder: Svein Henriksen

Regnskapsfører

• Regnskapsfører: PETIM REGNSKAP 1 AS

Revisor

• Revisor: VEKST REVISJON AS

Styre

• Styremedlem: Fredrik Grumstad
• Styremedlem: Svein Henriksen
• Styrets leder: Thomas Rønbeck

Owners

Source: Firmafakta shareholder dataset.

1. ZEMA AS – 38.46 % (15500 shares, share class: Ordinære aksjer)
2. KONFIDO CONSULTING AS – 34.74 % (14000 shares, share class: Ordinære aksjer)
3. JOJUMA INVEST AS – 16.87 % (6800 shares, share class: Ordinære aksjer)
4. EIIN INVEST AS – 9.93 % (4000 shares, share class: Ordinære aksjer)

Fetch a longer owner list

Company holdings

No holdings found.

Grants and support

Sources provided through Firmafakta: Innovation Norway, the EU, the Research Council of Norway and SkatteFUNN.

Innovasjon Norge (0)

No registered grants.

EU-tildelinger (0)

No registered grants.

Forskningsrådet (1)

1 results

1. id:

   76907

   prosjektnummer:

   346306

   prosjekttittel:

   Interpretable and compliant artificial intelligence to combat money-laundering

   prosjektstart:

   2023

   prosjektslutt:

   2027

   prosjektansvarlig_navn:

   INTERAGO AS

   organisasjonsnummer:

   913185412

   sokt_belop:

   Algoritmer og beregnbarhetsteori

   tildelt_belop:

   0.0

   virkemiddel:

   Frittstående prosjekter

   aktivitet:

   Andre frittstående prosjekter

SkatteFUNN (1)

1 results

1. id:

   68262

   innsendt_dato:

   2023-08-28

   prosjektnummer:

   347955

   bedriftsnavn:

   INTERAGO AS

   prosjekttittel:

   Forklarbar kunstig intelligens for å bekjempe hvitvasking

   organisasjonsnummer:

   913185412

   fylke:

   Oslo

   kommunenavn:

   Oslo

   poststed:

   OSLO

   soknad_godkjent:

   JA

   soknad_avslatt:

   NEI

   vedtaksdato:

   2023-11-03

   prosjekt_fra_ar:

   2023

   prosjekt_til_ar:

   2024

   sammendrag:

   Numerous banks have in recent years faced substantial fines due to ineffective anti-money-laundering (AML) controls. One such control is based on transactions monitoring systems (TM systems), designed to detect suspicious money transfers. Today's TM systems are predominantly based on defining a set of if-then rules with predefined thresholds. If a threshold is exceeded, the TM systems trigger alerts that are forwarded to AML specialists for evaluation. Unfortunately, with an estimated false-positive rate ranging between 95 to 98%, banks find themselves struggling to comply with financial regulation. Although deep learning has been proposed as a remedy, a major obstacle must be overcome, namely the lack of interpretability within deep learning models. Financial institutions are obligated to be able to explain the reasoning behind a decision to their clients, regulators, and other stakeholders. Deep learning models, however, typically involve thousands if not millions of parameters that do nonlinear computations, making it difficult for humans to follow the reasoning behind a model's predictions. Deploying a deep learning model into a live environment without a comprehensive understanding of its decision-making process places banks at risk of discriminating against their customers. The consequences of such biases include legal liability, reputational damage, and loss of customers' trust. Recent advances in interpretable deep learning theory offer some promising tools in this regard. Techniques such as saliency maps and gradient-based methods offer avenues for extracting meaningful interpretations. Yet another interesting approach is the concept of 'attention as explanation'. In this project, our aim is to build effective and interpretable deep learning algorithms to combat money laundering. We will do so by combining theory on interpretable deep learning with theory on financial crime.

Subunits

• INTERAGO AS (913220803)

Open positions

count:

0

stillinger:

No results.

Related lookups

• Doffin notices where INTERAGO AS is the buyer
• Search broadly for INTERAGO AS in Doffin
• Open positions related to INTERAGO AS
• Latest financial statement
• Patents and trademarks
• Official entity information from the Brønnøysund Register Centre
• Official roles from the Brønnøysund Register Centre
• Corporate group structure from the Brønnøysund Register Centre